UC Berkeley, in partnership with former California Gov. Edmund G. Brown Jr. and China’s top climate change official, Xie Zhenhua, today (Monday, Sept. 23) announced the launch of a new campus institute to bring together top researchers and policymakers from both sides of the Pacific to stop the rise of greenhouse gases.
The new California-China Climate Institute will be jointly hosted by Berkeley Law and the College of Natural Resources. Berkeley experts will work closely with colleagues at the Institute of Climate Change and Sustainable Development at China’s public Tsinghua University, as well as with various government organizations in both China and California.
Q. What do you expect the school to accomplish in the next five years and beyond?
A. Our own strategic plan is a component of the overall UVA strategic plan, and thus our planned accomplishments can be defined around discovery, service and community.
Thus far, our discoveries have been based around a limited research agenda. That agenda will expand with new faculty, a Ph.D. program and a focus on leading-edge research. Since data science covers all fields, we can’t attempt everything and we will focus where we think we can have the maximum societal benefit, notably through research in biomedicine with an emphasis on neurodegenerative diseases and clinical translation, the environment, cybersecurity, business analytics, educational analytics and the digital humanities.
Behind the Inforum 2019 GA announcement of the Coleman AI platform lies an intriguing data science debate: will customers embrace self-service data science? Here’s my look into how Infor weighed this out internally, and what they decided.
More than 70% of healthcare data breaches in the U.S. have involved sensitive demographic or financial information that could fuel identity theft, a new study suggests.
When a healthcare company is hacked, criminals gain access not only to health information, but also to demographic and financial data that could compromise patients’ privacy and financial security, researchers from the Michigan State and Johns Hopkins report.
Media reports often focus on the numbers of patients affected by these breaches, but what may be more important is the kind of data that has been stolen, they write in Annals of Internal Medicine.
U-M researchers will partner with colleagues at New York University and the University of Washington over the next two years to deploy new techniques and technologies that enable responsible data science, while establishing an interdisciplinary community focused on the study, design, deployment and assessment of equitable data systems.
Equity is an important facet of data science that NSF aims to strengthen in the coming years, as the federal agency partners with universities such as U-M to enable new modes of data-driven discovery that will transform the frontiers of science and engineering.
The centerpiece of its ongoing effort, called Harnessing the Data Revolution at NSF, is the development of national institutes that address multidisciplinary problems in big data. U-M will help lay the groundwork for developing these institutes, which will eventually serve as a point of convergence for researchers from multiple disciplines to share expertise and address pressing challenges in data science.
“It’s an amazing honor, and very unexpected. There are a very small number of cognitive scientists who have ever received it, so it’s an incredible honor to be in their company,” says Tenenbaum, a professor of computational cognitive science and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Center for Brains, Minds and Machines (CBMM).
Using computer modeling and behavioral experiments, Tenenbaum seeks to understand a key aspect of human intelligence: how people are able to rapidly learn new concepts and tasks based on very little information. This phenomenon is particularly noticeable in babies and young children, who can quickly learn meanings of new words, or how objects behave in the physical world, after minimal exposure to them.
How will Canadian universities change over the next 20 years? What challenges will they face and what opportunities lie ahead? In honour of University Affairs’ 60th anniversary, we put questions like these to seven people representing different regions and facets of the university enterprise from coast to coast. They spoke about their dreams for universities that better represent the world scholars strive to understand, about their concerns around finances, how the students they serve inspire and teach them, and about the opportunities – and risks – posed by the onslaught of rapid technological change. Most of all, they affirmed that universities have a vital role to play in helping society navigate through the deepest challenges of our time, from climate change to the dangers of misinformation and rising intolerance.
Florida Atlantic University’s College of Engineering and Computer Science is launching the state’s first Master of Science with Major in AI (MSAI), administered by its Department of Computer and Electrical Engineering and Computer Science. This degree will prepare students for careers in various education, government and industry positions that require AI skills.
“As we are experiencing the dawn of the fourth industrial revolution that is defined by AI and autonomy, our state and nation strive to lead the world in AI-and-autonomy-driven innovation. And, as there is hardly any industry that is not affected by AI and autonomy, industry investments on AI and autonomy are reaching very high levels,” said Stella Batalama, Ph.D., dean of FAU’s College of Engineering and Computer Science.
Anne Hunter, the undergraduate academic administrator for the electrical engineering and computer science (EECS) department, is retiring after 37 years in the role and more than 46 years at MIT.
Earlier this week, The Tech interviewed Hunter to talk about her experiences as academic administrator and her contributions to student success within the department.
The Berejiklian Government says it is on a mission to change the culture on NSW roads by permanently setting up cameras to detect motorists using mobile phones.
It is spending $88 million on fixed and portable cameras, which will be placed at 45 spots across the state.
Everyone was in uniform; there were scheduled briefings, last-minute discussions, final rehearsals. “They wanted to look me in the eye and say, ‘Are you sure this is going to work?’ ” an operator named Neil said. “Every time, I had to say yes, no matter what I thought.” He was nervous, but confident. U.S. Cyber Command and the National Security Agency had never worked together on something this big before.
Four teams sat at workstations set up like high school carrels. Sergeants sat before keyboards; intelligence analysts on one side, linguists and support staff on another. Each station was armed with four flat-screen computer monitors on adjustable arms and a pile of target lists and IP addresses and online aliases. They were cyberwarriors, and they all sat in the kind of oversize office chairs Internet gamers settle into before a long night. [audio, 49:23]
ike Capps, the chief executive of AI startup Diveplane, and former president of Epic Games, the producer of blockbusters Fortnite and Gears of War, sees how it can also support traditional shipping and logistics.
Here are 10 ways Capps thinks AI should be applied to the trucking industry.
Using Synthetic data sets will help logistics providers analyze their vast quantities of customer-based data without fear of the repercussions to their reputation or financial loss due to data loss. Implementing Synthetic data “twins” allows for broader internal and external analysis of data to better understand customer demand and patterns.
Purdue University, The Exponent student newspaper, Nick Lundin
from
With around 2,000 students, computer science is the largest major at Purdue, and it is in high demand.
There are thousands of applications with a limited number of slots available for new students. Some students, who are not directly admitted into the program may look to CODOing as their opportunity into computer science, however, the process is not easy.
By controlling the properties of the feedback loop—in this case, the distance between the speaker and the microphone—you can control the system’s output. It takes very little energy: the feedback loop doesn’t power the amplifier. There’s no obvious point of control. The feedback loop commandeers the sound system and the engineers, with all their knobs and dials, have to fight to bring the system back under control. Until they succeed, you just have to sit back and listen to the noise.
Network propaganda works in much the same way as microphones and music. Propaganda isn’t a new phenomenon. It has existed for ages, probably going back to the dawn of consciousness—certainly to the dawn of political competition.
Only now the mechanics, the mechanisms used to spread disinformation, have changed.
“Pairing our deep knowledge of human biology and medicine with Microsoft’s leading expertise in AI could transform the way we discover and develop medicines for the world,” Narasimhan added.
The partnership will start with three specific projects: implementing AI-based approaches to help personalize treatments for macular degeneration and irreversible blindness, including through image segmentation and analysis; increasing the efficiency of cell and gene therapy manufacturing, starting with treatments for acute lymphoblastic leukemia such as Kymriah; and expediting Novartis’ processes for designing and generating new therapeutic molecules.
College of Coastal Georgia announced Tuesday that a new degree in data science will be offered next semester.
The college will launch a Bachelor of Science in Data Science beginning in Spring 2020, to help meet the needs of one of the most in-demand career paths available.
Although many companies talk about artificial intelligence, it’s likely that the majority of their employees aren’t actually using machine-learning technologies in the workplace.
One big reason for that is while executives may be excited about A.I., employees may feel threatened or even insulted that managers would force them to use tools that that they fear will one day replace them.
As FedEx senior data scientist Clayton Clouse said during an A.I. conference in San Francisco last week, “We shouldn’t expect that people will jump up and down and be excited when we say, ‘Hey, we’re going to be augmenting your job with A.I.’”
Wendy Martinez has been serving as the Director of the Mathematical Statistics Research Center at the Bureau of Labor Statistics (BLS) for six years. [audio, 25:25]
The worst times are at the start of term, when students are adjusting to being away from home, or over the holidays, when the small number who remain on campus may feel lonely and isolated. Increasingly, Vass’s security team are called out to mental health emergencies, sometimes accompanying suicidal students to A&E and staying with them. “We spend as much time as it takes,” says Vass. On occasion, he has spent six hours with a student in distress.
British universities are experiencing a surge in student anxiety, mental breakdowns and depression. There has been a sharp rise in students dropping out – of the 2015 intake, 26,000 left in their first year, an increase for the third year running – and an alarming number of suicides. In the 12 months ending July 2017, the rate of suicide for university students in England and Wales was 4.7 deaths per 100,000 students, which equates to 95 suicides or about one death every four days.
… The CCPA provides some novel protections and powerful mechanisms for consumers to fight back against the wanton sharing of personal data. Importantly, the law broadens the definition of “sale” to include any sharing of personal data from which the company would gain valuable consideration. Companies are required to respect requests from individuals to opt-out of any sale of their data, and it prohibits businesses from discriminating against the people who exercise these rights. This legislation is an important step toward a future in which you have more agency and control over your digital identities, but it doesn’t prevent companies from collecting information about you. As individuals, we continue to be vulnerable to large-scale database breaches, which result from the centralization and warehousing of our personal information.
A Penn program gives students the chance to work directly with election polling data ahead of the 2020 presidential election.
The Program on Opinion Research and Election Studies, run through Penn’s Political Science department, chooses student fellows each semester to work with faculty on projects related to political outcomes research. Known as PORES, the program was founded by Political Science professor John Lapinski, who is also director of the Elections Unit at NBC News.
The Columbia team behind the revolutionary 3D SCAPE microscope announces today a new version of this high-speed imaging technology. In collaboration with scientists from around the world, they used SCAPE 2.0 to reveal previously unseen details of living creatures — from neurons firing inside a wriggling worm to the 3D dynamics of the beating heart of a fish embryo, with far superior resolution and at speeds up to 30 times faster than their original demonstration.
For 6G wireless to become a reality, it must overcome a few technical hurdles, such as connecting terahertz spectrum to hard, optical transmission lines. Researchers at the Karlsruhe Institute of Technology say they have solved the problem.
A new prosthetic leg integrates with a wearer’s nervous system to give real-time feedback about their environment. Users can report they can “feel” where their artificial leg is in space, giving them the ability to complete a range of tasks previously out of reach.
Researchers described tests with the new prosthetic in Science Translational Medicine this week in three patients with above-the-knee-amputations. They say it could lead to devices that mesh with our nervous systems to expand amputees’ abilities and restore feeling to missing limbs.
“Provenance is the record of data lineage and software processes operating on these data that enable the interpretation, validation, and reproduction of results,” explained Line Pouchard, a senior researcher at the Center for Data-Driven Discovery (C3D), part of the Computational Science Initiative (CSI) at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory.
Currently, Pouchard is leading an effort focused on enhancing scientific experimentation through provenance via a framework called the Dynamic Provenance System (DPS).
For scientific experiments, provenance encompasses descriptions of samples, experimental procedures and conditions, and data analysis methods. The ability to record these metadata and scientific workflows is especially critical in today’s era of big data, where researchers are faced with large, diverse data from complex, dynamic, and streaming heterogeneous sources. In order for scientists to derive insights that lead to discoveries, they need to know how data were generated and transformed from their original state to produce the final results.
The Federal Communications Commission has mostly defeated net neutrality supporters in court even though judges expressed skepticism about Chairman Ajit Pai’s justification for repealing net neutrality rules.
One of the three judges who decided the case wrote that the FCC’s justification for reclassifying broadband “is unhinged from the realities of modern broadband service.” But all three judges who ruled on the case agreed that they had to leave the net neutrality repeal in place based on US law and a Supreme Court precedent (see ruling).
Alteryx, a publicly traded analytics company, announced this morning that it has acquired Feature Labs, a machine learning startup that launched out of MIT in 2018. The company did not reveal the terms of the deal.
Co-founder and CEO Max Kanter told TechCrunch at the time of the launch the company had been based on research at MIT that looked at how to automate the creation of machine learning algorithms. “Feature Labs is unique because we automate feature engineering, which is the process of using domain knowledge to extract new variables from raw data that make machine learning algorithms work,” Kanter told TechCrunch in 2018.
Ampere makes chips for data centers based on customizable designs from Intel rival ARM Holdings. The company’s headquarters are in Silicon Valley, near Intel’s base, but Ampere has a substantial engineering office in Northwest Portland and James splits her time between Oregon and California.
PayPal has decided to withdraw from the Libra Association, the 28-member nonprofit organization formed in June 2019 to oversee the cryptocurrency’s creation and eventual consumer rollout.
Brown University researchers, surgeons from Rhode Island Hospital and private partners will develop and test a device aimed at bridging the gap in neural circuitry created by spinal cord injury, in the hope of restoring muscle control and sensation.
Reports emerged this week Amazon is in talks to bring its cashierless Amazon Go technology to airports, movie theaters and baseball stadiums—a move that could help the ecommerce giant really hit the gas in terms of brick-and-mortar expansion, which has been slower than initially anticipated.
In recent months, we’ve been partnering with cities across ten different countries to learn how they currently collect data, plan for reduction projects, take action, and track results. We’ve been working with these cities, and our city-network partners, to validate EIE’s data and approach against existing data sources, and testing our modeled data against actual road sensor counts.
A major component of the renovation involved re-evaluating and rebuilding the Bass Library’s collection, which has been consolidated in stacks on the library’s lower level. As part of the process, library staff analyzed content and usage of the Bass collection. As a result of this work, more than 35% of the 61,000 volumes in the post-renovation collection are new to the Bass Library. Disciplines that were under-represented before the renovation, such as the arts, sciences, and law, have a proportionally larger presence in the new collection. Going forward, the collection will be dynamic, with up to 3,000 new titles added per year, [Susan] Gibbons explained.
The program centers on developing leading-edge software and hardware technology that combines human and machine elements to exploit their respective strengths and mitigate their respective weaknesses. It aligns with the University’s strategic vision for research that impacts Northwest Florida’s economic development and technology enterprise. The first of its kind in Florida and one of only a few in the nation, the program will serve the manufacturing, health care, defense and other high-tech industries, providing critical support to high-demand career fields.
“UWF welcomes an esteemed group of eager doctoral students, each with a uniquely impressive background,” said UWF President Martha D. Saunders. “They are ready, and we are confident that UWF and IHMC will guide them to their individual success.”
As they start to understand the profound transformations that AI entails, many countries are developing national strategies on artificial intelligence. But these approaches are far from similar. In fact, one could and should place these attempts to master AI within the broader framework of (great) power competition. To paraphrase, AI is no more than the continuation of international politics by other means.
A quick analysis of some of these strategies reveals takes on AI that are subsumed to the overarching objective of advancing national interests. Therefore, what are these national plans on AI telling us about the return of great power competition?
SparkCognition, an artificial intelligence technology company, makes applications for industries such as oil and gas, defense, utilities, aviation, and financial services. Its customers include The Boeing Company, Hitachi High-Technologies, Aker BP and many others.
SparkCognition’s products include the Darwin for automated model building, DeepArmor for AI-built cybersecurity, SparkPredict, an analytics solution, and DeepLNP, a natural language processing solution.
In their efforts to work out what’s going wrong, researchers have discovered a lot about why DNNs fail. “There are no fixes for the fundamental brittleness of deep neural networks,” argues François Chollet, an AI engineer at Google in Mountain View, California. To move beyond the flaws, he and others say, researchers need to augment pattern-matching DNNs with extra abilities: for instance, making AIs that can explore the world for themselves, write their own code and retain memories. These kinds of system will, some experts think, form the story of the coming decade in AI research.
Across the arc of the past 150 years, we can see both science and scientism shaping human identity in many ways. Developmental psychology zeroed in on the intellect, leading to the transformation of IQ (intelligence quotient) from an educational tool into a weapon of social control. Immunology redefined the ‘self’ in terms of ‘non-self’. Information theory provided fresh metaphors that recast identity as residing in a text or a wiring diagram. More recently, cell and molecular studies have relaxed the borders of the self. Reproductive technology, genetic engineering and synthetic biology have made human nature more malleable, epigenetics and microbiology complicate notions of individuality and autonomy, and biotechnology and information technology suggest a world where the self is distributed, dispersed, atomized.
Individual identities, rooted in biology, have perhaps never played a larger part in social life, even as their bounds and parameters grow ever fuzzier.
Texas Advanced Computing Center, Faith Singer-Villalobos
from
Kuleana is a uniquely Hawaiian value and practice which embodies responsibility to self, community, and the ‘aina’ (land). At Chaminade University, a federally designated Native Hawaiian serving university in Hawai‘i with a two million-square-mile Pacific island catchment area, kuleana is part of the institution’s DNA.
It’s with this spirit that 21 undergraduate students at Chaminade University on the island of Oahu, 92 percent of whom were Native Hawaiian, undertook a month-long summer immersion experience in the field of data science.
Helen Turner, Chaminade University’s Vice President for Strategy and Innovation, has a 20-year history of working with the Native Hawaiian and Pacific Islander communities through research, education, and outreach programs.
Helen Turner, Chaminade’s Vice President for Strategy and Innovation, has a 20-year history of working with the Native Hawaiian and Pacific Islander communities through research, education, and outreach programs. The university’s recent push into the field of data science (starting Hawai‘i’s first Bachelor of Science program in this area as well as associated professional development qualifications) is the latest STEM (science, technology, engineering, and mathematics) initiative led by Turner.
The UW System Board of Regents approved a new data science major Friday, opening the door for University of Wisconsin–Madison undergraduates to study a field tied to one of the country’s fastest-growing professions.
Students may immediately begin taking courses that will count toward the new degree. Beginning in fall 2020, students will be able to declare the major within the School of Computer, Data & Information Sciences (CDIS), home to the departments of Statistics and Computer Sciences and the Information School. The newly created school – along with the American Family Insurance Data Science Institute established earlier in 2019 – are part of UW–Madison’s commitment to leading research and education in information technology and big data.
the Bureau of Industry and Security of the Department of Commerce announced that it will add 28 Chinese governmental and commercial organizations to the Entity List for engaging in or enabling activities contrary to the foreign policy interests of the United States. This action constricts the export of items subject to the Export Administration Regulations (EAR) to entities that have been implicated in human rights violations and abuses in China’s campaign targeting Uighurs and other predominantly Muslim ethnic minorities in the Xinjiang Uighur Autonomous Region (XUAR).
“The U.S. Government and Department of Commerce cannot and will not tolerate the brutal suppression of ethnic minorities within China,” said Secretary of Commerce Wilbur Ross. “This action will ensure that our technologies, fostered in an environment of individual liberty and free enterprise, are not used to repress defenseless minority populations.”
If Medtronic is going to move beyond selling insulin pumps and glucose monitors, for example, it needs to help people with diabetes monitor their nutrition. The result is that Medtronic in November 2018 announced it was acquiring Tel Aviv, Israel–based Nutrino Health and its nutrition-related data services and artificial-intelligence-based analytics.
Partnerships with health payers and providers are important, too. Dodd mentioned Medtronic’s five-year value-based healthcare partnership with the Lehigh Valley Health Network. The company is using its technological know-how and data-crunching skills to tackle up to 70 major medical conditions, with the goal of helping the Northeastern Pennsylvania health system improve the lives of as many as 500,000 people, create efficiencies, and reduce healthcare costs to patients, payers, and the health system by $100 million over five years.
Los Angeles Times, Kaiser Health News, Barbara Feder Ostrov and Harriet Blair Rowan
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Drugmakers fought hard against California’s groundbreaking drug price transparency law, passed in 2017. Now, state health officials have released their first report on the price hikes those drug companies sought to shield.
Pharmaceutical companies raised the “wholesale acquisition cost” of their drugs — the list price for wholesalers without discounts or rebates — by a median of 25.8% from 2017 through the first quarter of 2019, according to the Office of Statewide Health Planning and Development. (The median is the point at which half the prices are higher and half are lower.)
Four years after the first issue of Nature was published, the US National Academy of Sciences (NAS) faced an existential crisis. In October 1873, one of its original members demanded the expulsion of another member for swindling. Josiah Whitney, California’s state geologist, accused Benjamin Silliman Jr, professor of applied chemistry at Yale University in New Haven, Connecticut, of accepting large sums from California oil companies in return for favourable, possibly fraudulent, science. Silliman responded forcefully that company funding for science was evidence of responsibility, not misconduct: companies needed objective “technical opinions”. Without science, swindling would be more common, he argued.
NAS president Joseph Henry, secretary of the Smithsonian Institution and a former consultant to Samuel F. B. Morse, inventor of the telegraph, had to agree. If the NAS expelled every member who had ever consulted for a private company, it would not survive. Henry rejected the efforts to remove Silliman. More importantly, he resolved to expand the NAS membership; new members were to be judged on the basis of their research, not on the source of their income1. By the 1870s, it was already clear that industry relied on science.
The Silliman–Whitney controversy marked a watershed in the relationship between science and industry.
On October 2nd, the AI Now Institute at NYU hosted its fourth annual AI Now Symposium to another packed house at NYU’s Skirball Theatre. The Symposium focused on the growing pushback to harmful forms of AI, inviting organizers, scholars, and lawyers onstage to discuss their work. The first panel examined AI’s use in policing and border control; the second spoke with tenant organizers from Brooklyn who are opposing their landlord’s use of facial recognition in their building; the third centered on the civil rights attorney suing the state of Michigan over its use of broken and biased algorithms, and the final panel focused on blue-collar tech workers, from Amazon warehouses to gig-economy drivers, to speak to their organizing and significant wins over the past year.
The DOE partnered with the University of Chicago and its affiliated laboratories, Argonne National Laboratory and Fermi National Accelerator Laboratory on a recent event to teach and inspire middle and high school students to consider a future in developing AI technology.
“Whether you are in government, business or a scientist, there’s a big revolution coming, and it’s called artificial intelligence,” said Chris Fall, director of the DOE’s Office of Science, who spoke at the Oct. 1 event at the Gary Comer Youth Center. If young people are interested in understanding how Alexa works and becoming someone who builds AI tools, “we’re interested in talking to you,” he said. “Maybe I can talk you guys into becoming scientists and engineers.”
The key thing about Luminar 4, however, is the use of AI – artificial intelligence – to take the grunt work out of image editing. For Skylum, photo editing has not changed much in 20 years – with most programs offering a tool-based approach. Instead, Luminar offers a content-aware software that allows you to “spend less time editing and photos, and more time behind the camera’.
AI Structure, AI Sky Replacement, and AI Skin Enhancer are the key ingredients in Luminar 4 – and the three features has been teasing us with for months. The goal, according to Skylum CTO Dima Sytnik, is to “take away all the boring stuff like layers and masks.” He explains that they have learned from pros as to how they edit their pictures, so that they can know where to boost detail with AI Structure for instance. And with AI Skin Enhancer they have aimed to replicate the results of a professional retoucher – but in a fraction of the time.
The first official message dispatched by telegraph — the Bible verse “What hath God wrought” — was relayed by Morse code 175 years ago, across 40 miles.
What have humans wrought since? Fifty years ago, at 10:30 p.m. on Oct. 29, 1969, Leonard Kleinrock, a professor in the new-ish field of computer science, along with his colleagues in their UCLA lab, laboriously fashioned the first computer message. It went the 350 or so miles to a Stanford computer set up through a Defense Department program. The intended pioneering message, “login,” only got as far as “l-o” before the system crashed, so the effect, if not the intent, was likewise biblical.
Next week, UCLA marks the 50th anniversary with a daylong symposium tracking the evolution of the world-altering phenomenon. Among the panelists at the event will be Eric Schmidt, former CEO of Google and former executive chairman of Google’s parent company Alphabet. The engineer and technology pioneer said he could not speak to current Google-related topics but reflects here on the state of tech and its place in the world, a half-century after that breakthrough.
Using a new technique to monitor vital signs remotely, engineers from the University of South Australia and Middle Technical University in Baghdad have designed a computer vision system which can distinguish survivors from deceased bodies from 4-8 metres away.
As long as the upper torso of a human body is visible, the cameras can pick up the tiny movements in the chest cavity, that indicate a heartbeat and breathing rate. Unlike previous studies, the system doesn’t rely on skin colour changes or body temperature.
The breakthrough is a more accurate means of detecting signs of life, the researchers say.
The United States military is falling behind in the race to use artificial intelligence to box adversaries into warfighting corners, the former head of U.S. Naval Special Warfare Command said on Tuesday.
A.I. has the potential to quickly sort through what can be a myriad of possible outcomes and offer the best possible action to take, he said during a panel discussion at The Promise and The Risk Of the A.I. Revolution conference, hosted by the U.S. Naval Institute.
It was always highly unlikely that Wisconsin’s taxpayer-subsidized deal with Taiwan-based smart phone manufacturer Foxconn was going to fulfill the promises made by Foxconn and the state government. Now, it’s worth wondering if the deal will live up to any of them.
Eighteen months after Foxconn bought a building in downtown Milwaukee that was supposed to be the first of several “innovation centers” to be built around the state, the building sits abandoned and empty, Wisconsin Public Radio reports. Other “innovation centers”—partnerships with local colleges and universities, each one supposed to create 100 to 200 high-tech jobs—planned for Green Bay, Madison, Eau Claire, and elsewhere also appear to be on hold.
When Sepiedeh Keshavarzi was getting her medical degree in Tehran, she often read research papers by prominent scientists in the U.S.
“It was my dream at some point when I was much younger to do research in the States,” she says.
Not anymore.
The U.S. denied Keshavarzi’s request for a visa to attend this year’s Society for Neuroscience meeting, which drew more than 25,000 brain scientists from around the world to Chicago this week. She was also denied a visa for last year’s meeting in San Diego.
How do we combine others’ probability forecasts? Prior research has shown that when advisors provide numeric probability forecasts, people typically average them (i.e., they move closer to the average advisor’s forecast). However, what if the advisors say that an event is “likely” or “probable?” In 7 studies (N = 6,732), we find that people “count” verbal probabilities (i.e., they move closer to certainty than any individual advisor’s forecast). For example, when the advisors both say an event is “likely,” participants will say that it is “very likely.” This effect occurs for both probabilities above and below 50%, for hypothetical scenarios and real events, and when presenting the others’ forecasts simultaneously or sequentially. We also show that this combination strategy carries over to subsequent consumer decisions that rely on advisors’ likelihood judgments. We find inconsistent evidence on whether people are using a counting strategy because they believe that a verbal forecast from an additional advisor provides more new information than a numerical forecast from an additional advisor. We also discuss and rule out several other candidate mechanisms for our effect.
If you work in a hospital and you’re not a security professional, IT professional, or executive, you probably never even think about cybersecurity. And that’s exactly the problem.
For people who actually work in the business of electing politicians (especially Democratic politicians), the media circus surrounding these poll numbers is nothing short of infuriating. The next election, after all, is hardly a foregone conclusion. Even more worrisome, several sources told me, is the possibility that our ongoing infatuation with polls could be providing a distorted image of a political environment in which voter enthusiasm—pro- and anti-Trump—is off the charts. Could a false sense of security costs Democrats the White House in 2020?
It’s not just cable news, of course. Almost daily there’s a story in national newspapers about this poll or that, swinging away from Trump and toward the Democrats, even though a clear front-runner has yet to emerge. (There are still a half-dozen people vying for that spot.) “Analysis: Trump’s one good 2020 poll just turned against him,” the Washington Post recently declared, citing a September Washington Post–ABC News poll that questioned 877 registered voters asking if they would vote for Trump, or former vice president Biden, or four other Democrats, which all showed Trump losing. (Trump was down double digits with Biden, and between four and nine points with other potential rivals, the poll found, also noting that the results had a margin of error of about four points.)
A common approach to disease outbreak has been one that is reactionary in nature — take action after the person is infected and after there is evidence of an outbreak. However, a new tool being developed at Kansas State University will instead provide a risk assessment of individuals becoming infected before it happens and will guide implementing preventive measures.
Funded by a U.S. Department of Defense, three-year, $868,000 grant, Caterina Scoglio, the LeRoy and Aileen Paslay professor in the Mike Wiegers Department of Electrical and Computer Engineering in the Carl R. Ice College of Engineering, is leading the team effort, PICTUREE: Predicting Insect Contact and Transmission Using histoRical Entomological and Environmental Data.
The AI challenges organizations are wrestling with span everything from the integrity of the data being employed to drive AI models to a lack of skills.
IBM this week confronted all the hurdles inhibiting adopting of artificial intelligence at a Data and AI Forum event. Industry analysts such as Gartner estimate that despite all the promise of AI, only 14% of organizations have deployed AI in a production environment. That’s up from only 4% a year ago. The AI challenges organizations are wrestling with span everything from the integrity of the data being employed to drive AI models to a lack of skills.
Rob Thomas, general manager for data and AI at IBM, told conference attendees data, skills and lack of trust in AI models are the three biggest inhibitors of AI adoption today.
Georgia State University News, Andrew Young School of Policy Studies
from
A new research partnership is connecting Georgia State University social scientists with Georgia Tech computer scientists in a unique collaboration to address historic social inequities.
The partnership will be in the form of a two-semester fellowship program for 16 faculty members, eight from each university, split into pairs. Each pair will match a Georgia Tech computer scientist with a Georgia State social scientist, working together to develop interdisciplinary projects addressing historic and continuing inequity challenges in the southeastern United States.
Yale University, Yale School of Engineering & Applied Science
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[Ayah] Bdeir, the founder of LittleBits, maker of educational kits of snap-together electronics, was the opening speaker for last week’s 4th International Symposium on Academic Makerspaces (ISAM) at Yale University. The three-day event was co-hosted by Olin College and attended by 350 maker educators, equipment manufacturers, and other enthusiasts from 156 universities from 14 countries. There, they talked shop, traded notes, and heard from leaders in the growing multi-disciplinary field. The annual event is the result of the partnership between Yale and six other universities – Case Western Reserve University, Georgia Tech, MIT, Olin College, Stanford University, University of California-Berkeley. This partnership, known as the Higher Education Makerspaces Initiatives (HEMI), is also the organizing body for the soon-to-be published International Journal for Academic Makerspaces and Making.
Bdeir was among many there who talked about the impact that makerspaces have had on their lives. “In my journey, there were many challenges I encountered and at every point, I focused on that problem as the most important one and learned the skills it required,” she said. “Having been part of the makerspace movement early on in my life really equipped me to deal with those challenges.”
After years of anticipation, autonomous vehicles are now being tested on public roads around the world. As ambitious innovators race to develop what they see as the next high-tech pot of gold, some experts warn there are still daunting challenges ahead, including how to train artificial intelligence to be better than humans at making life-and-death decisions. How do self-driving cars work? How close are we to large-scale deployment of them? And will we ever be able to trust AI with our lives? [video, 53:29]
The idea for the office grew out of an April 2018 working group that Yee convened with more than 200 representatives from the tech sector, the Teamsters union, advocacy groups like Walk San Francisco and other nonprofits to explore ways to foster innovation without undermining public safety, equity and labor protections.
“I appreciate the supervisor’s willingness to engage with the industry,” said Jennifer Stojkovic, executive director of sf.citi, a trade group that advocates on behalf of tech companies and who participated in the brainstorm meeting. “Oftentimes, there is legislation that comes out without industry being at the table, and I appreciate [Yee] involving us in the beginning.”
madison.com, Wisconsin State Journal, Shelley K. Mesch
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Madison’s Google office, where employees develop hardware and software for Google’s data centers, spans about 30,000 square feet over the top two floors of the building. Sweeping views of the city are a significant feature of the new space, said principal scientist and site leader Jeff Naughton.
With windows enclosing the office, most employees need just turn around for a bird’s-eye view of the Isthmus. From an outdoor lounge space, employees can look out toward the state Capitol as well as lakes Mendota and Monona.
University of North Carolina, University Libraries
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The University Libraries and SAGE Publishing will enter into a pilot agreement enabling researchers at the University of North Carolina at Chapel Hill to publish open access articles in SAGE journals at no cost to the researcher.
Under the agreement, part of the subscription fees that the Library will pay for SAGE content beginning in 2020 will cover the costs of open access publishing for a number of UNC-Chapel Hill authors in SAGE publications. This comes at no additional cost to the Library and will preserve access to all content that the Library currently licenses from SAGE.
“We want to make it as easy as possible for Carolina researchers to publish open access,” said Elaine L. Westbrooks, vice provost for University Libraries and University librarian. “This is also part of our strategy to forge new channels that will make published research as open and accessible as possible.”
By applying BERT models to both ranking and featured snippets in Search, we’re able to do a much better job helping you find useful information. In fact, when it comes to ranking results, BERT will help Search better understand one in 10 searches in the U.S. in English, and we’ll bring this to more languages and locales over time.
Particularly for longer, more conversational queries, or searches where prepositions like “for” and “to” matter a lot to the meaning, Search will be able to understand the context of the words in your query. You can search in a way that feels natural for you.
Using a supercomputing system, MIT researchers have developed a model that captures what web traffic looks like around the world on a given day, which can be used as a measurement tool for internet research and many other applications.
Understanding web traffic patterns at such a large scale, the researchers say, is useful for informing internet policy, identifying and preventing outages, defending against cyberattacks, and designing more efficient computing infrastructure. A paper describing the approach was presented at the recent IEEE High Performance Extreme Computing Conference.
In a landmark report that reinforces legal standards to combat online hate, the UN’s monitor for freedom of expression calls on governments and companies to move away from standardless policies and inconsistent enforcement, and to align their laws and practices against ‘hate speech’ with international human rights law.
“The prevalence of online hate poses challenges to everyone, first and foremost the marginalised individuals who are its principal targets,” said David Kaye, the UN Special Rapporteur on freedom of opinion and expression, in the report to be presented to the UN General Assembly today. “Unfortunately, States and companies are failing to prevent ‘hate speech’ from becoming the next ‘fake news’, an ambiguous and politicised term subject to governmental abuse and company discretion.
This article addresses how “data fabrics” enable improved analytics by solving the problems faced in accessing data stored in different locations and overlapping software programs in the multi-vendor, multi-user, and multi-shareholder information technology (IT) environments prevalent in leading hospital systems, and the legal issues that result.
A “data fabric” is a technology for providing connectivity between data dispersed in different locations and in incompatible formats, and the multiple computer programs running in different IT systems at different sites. This characterizes hospital IT systems where one department operates dozens of different software programs and multiple databases hosted both in the cloud and on computers at hospital facilities.
The advanced functionality provided by data fabrics is the ability to not only connect data, but to connect both data and software, all while leaving the data and programs in place.
Data fabrics are connected to “machine learning,” which is a branch of “artificial intelligence,” where an algorithm (essentially software) is improved by “learning” from the data presented to it. In hospital operations, data fabrics improve revenue cycle management and supply chains efficiency and uncover unauthorized access to controlled substances.
Here’s something you don’t hear every day: two theories of consciousness are about to face off in the scientific fight of the century.
Backed by top neuroscientist theorists of today, including Christof Koch, head of the formidable Allen Institute for Brain Research in Seattle, Washington, the fight hopes to put two rival ideas of consciousness to the test in a $20 million project. Briefly, volunteers will have their brain activity scanned while performing a series of cleverly-designed tasks targeted to suss out the brain’s physical origin of conscious thought. The first phase was launched this week at the Society for Neuroscience annual conference in Chicago, a brainy extravaganza that draws over 20,000 neuroscientists each year.
Both sides agree to make the fight as fair as possible: they’ll collaborate on the task design, pre-register their predictions on public ledgers, and if the data supports only one idea, the other acknowledges defeat.
Google’s Android OS for smartwatches, Wear OS, isn’t nearly as successful as Android for smartphones, tablets, or televisions, and there’s a lot of blame to go around for that. We can blame Google for not having enough confidence to launch its own smartwatch hardware or for barely giving Wear OS the time of day at its big developer conference, or we can blame Qualcomm for failing to design a competitive smartwatch SoC. Smartwatches from Samsung, Huawei, and Apple, with their custom operating systems and SoCs, tend to have much better battery life than smartwatches with Wear OS and Qualcomm’s Snapdragon Wear 2100 or 3100. Qualcomm’s current wearable platforms are manufactured on a 28nm fabrication process; in comparison, Samsung’s Exynos 9110, found in the Galaxy Watch series, is manufactured on a 10nm fabrication process. Qualcomm may be bridging the gap with its next SoC for wearables, however, and it could come in the form of the Snapdragon Wear 3300.
The 82-year-old automotive giant has announced that it is creating a new startup dedicated to developing self-driving technology. It remains to be seen whether that will let it compete against the myriad new players in the autonomous vehicle market.
When the editor-in-chief of a highly reputable American medical journal decided to publish a potential bombshell study from Canada hinting that pregnant women who drink fluoridated water risk subtly damaging their child’s brain, he braced for the blowback.
He imagined anti-fluoridationists would sink their teeth into it and wave it as more proof of the harms of “mass medication,” while proponents of fluoride would “trash it, because they just don’t want to believe the findings,” Dr. Dimitri Christakis, editor of JAMA Pediatrics said in an interview with the Post.
Scientific American Blog Network, Observations, Brian Cantwell Smith
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The representations in second-wave AI are often called “distributed,” because information about many commonsense features of the world is spread out across these systems’ internal networks. Second-wave systems are also capable of retaining staggering amounts of detail rather than reducing their inputs to simple propositional statements such as “this is an apple” or “that is Lyme disease.” Beyond classifying an x-ray as showing lung cancer, for example, a second-wave AI system could capture the tumor’s density, contrast, shape and other features, all potentially relevant to drug choice or predicted outcome.
Why does this approach work better? Why does second-wave AI excel where GOFAI stumbled? The answer is ontological. How we humans parse the world into objects, properties, relations, and so on—how, as I will say, we register the world—is partially determined by our interests, our culture, our communities, our projects. The uninterpreted world is supremely messy. The objects and properties in terms of which we conceptualize our experience cannot be taken as axioms or directly “read off” this profusion, as is simplistically assumed in first-wave AI.
… One of the potential negatives for consumers, says [Jitesh] Ubrani, is that even if Google vows not to sell ads against your health data, it could find other creative ways to monetize whatever you’re sharing through your wrist.
“They have the data, so they can tie software and services together to try to sell more of their other services,” he says. That’s both the upside and downside of interoperability, of your software working across your phone, your laptop, your smartwatch, or potentially even your smart glasses—when it works, it works, but it’s another access point into your life for one of the tech giants.
Consumers may also be rightfully concerned about privacy and security. Facebook’s privacy missteps have been a “watershed moment” for these issues in the tech sector, Ubrani says, and privacy policies are being scrutinized more.
The Daily Californian student newspaper, Angelina Wang
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“No one treatment works for everyone and no one has objective data on how to differentiate the enormous variability of depression symptoms and subtypes,” said Stephan Lammel, researcher and campus professor of neurobiology, in an email.
The researchers developed a multidisciplinary platform where they analyzed genes, synapses, cells and circuits to identify biological markers associated with specific symptoms related to depression. In order to develop the platform, the researchers used mice as models — when under constant stress, they produce three or more common symptoms of human depression, including anxiety, lack of motivation and loss of pleasure.
Artificial intelligence (AI) is one phrase we’re going to hear a lot more of in the restaurant industry from now on. McDonald’s and KFC are already experimenting with it, and this week, Starbucks said the technology is a key piece of the company’s overall digital strategy moving forward.
On an investor call, Starbucks CEO Kevin Johnson highlighted the company’s Deep Brew initiative, which will be a major area of focus in 2020. And as Johnson explained in a LinkedIn post recently, Deep Brew involves machine learning technologies that will improve back-of-house elements like inventory management and employee scheduling. Johnson said the technology will also power better recommendations and upsell offers to customers via the Starbucks mobile app. “Deep Brew solutions will support our partners in many ways such as sequencing orders, anticipating equipment maintenance, streamlining supply chain logistics, and more,” he wrote in the post.
In July 2018, DOD leadership tasked the Defense Innovation Board to propose a set of ethics principles for consideration. Since then, the DIB has conducted an extensive study that included numerous discussions with experts in industry, academia and the private sector. The board also led multiple public listening sessions, interviewed more than 100 stakeholders and held monthly meetings of an informal DOD working group in which representatives of partner nations also participated. The board also conducted two practical exercises with leaders and subject matter experts from DOD, the intelligence community and academia.
Board members met yesterday in a public meeting at Georgetown University in Washington to discuss and vote on their recommended AI ethics principles.
Newark, New Jersey-based Duality Technologies, a provider of privacy-enhancing data science solutions, today announced that it’s raised $16 million in a series A round led by Intel Capital, with participation from Hearst Ventures and existing investor Team8. Duality previously raised $4 million in a November 2018 round, which together with this latest tranche brings its total raised to about $20 million.
Cofounder and CEO Alon Kaufman said that Duality will leverage the fresh funding to continue developing its secure computing platform and to expand into new segments. To this end, it recently collaborated with Intel to explore the challenges of AI workloads using encryption, which informed efforts like the open source HE-Transformer backend for Intel’s nGraph neural network compiler.
Today’s best digital computers still struggle to solve, in a practical time frame, a certain class of problem: combinatorial optimization problems, or those that involve combing through large sets of possibilities to find the best solution. Quantum computers hold potential to take on these problems, but scaling up the number of quantum bits in these systems remains a hurdle.
Now, MIT Lincoln Laboratory researchers have demonstrated an alternative, analog-based way to accelerate the computing of these problems. “Our computer works by ‘computing with physics’ and uses nature itself to help solve these tough optimization problems,” says Jeffrey Chou, co-lead author of a paper about this work published in Nature’s Scientific Reports. “It’s made of standard electronic components, allowing us to scale our computer quickly and cheaply by leveraging the existing microchip industry.”
Is it time for new rules for donations to colleges and universities?
Brown University apparently thought so. On Sunday, Brown published an updated gift-acceptance policy that states, among other things, that it won’t take money that “compromises the academic freedom of the university community” or “could inflict damage to the university’s reputation, standing, or integrity, or be contrary to university values.”
The update was issued after student groups protested donations from an alumnus, Warren Kanders, whose company sold tear gas used on migrants at the United States-Mexico border, The Brown Daily Herald reported.
Neural machine translation (NMT) is a machine translation approach that utilizes an artificial neural network to predict the likelihood of a sequence of words. With the development of deep learning, NMT is playing a major role in machine translation and has been adopted by Google, Microsoft, IBM and other tech giants. A Google AI research team recently published the paper Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges, proposing a universal neural machine translation (NMT) system trained on over 25 billion examples that can handle 103 languages.
Take Nasdaq, which recently debuted a new system that uses A.I. to monitor for a kind of stock fraud known as spoofing. With spoofing, criminals covertly manipulate a company’s share price by submitting buy or sell orders and then quickly cancelling them before they are executed.
It took nearly a year for Nasdaq to build and test the monitoring system, which is based on the powerful deep-learning technique that’s created breakthroughs in computer vision and text analysis. Earlier this month, the stock exchange debuted the system more broadly.
Despite the fancy technology, one key element in making it useful was basic:
… Fitbit would be filling more than a hardware gap. It’s a window to a $3 trillion health-care sector.
Fitbit has struggled to expand its Health Solutions, but Google “provides the resources to expand and compete at the highest level,” according to a Friday note by Wedbush analysts.
Even if Fitbit continues to languish behind the Apple Watch, it has sold 100 million devices, and 28 million of them are currently in use. All of those devices are collecting data, and that’s a potential gold mine for the health industry, including medical researchers and health insurers. Google, which specializes in creating data tools and making a profit from them, could use Fitbit’s brand and customers to help get a piece of that pie.
Should your wearable data be protected as health data? Can it be? The more the information gets integrated into your care plan, the more potential there is to improve your health, says Mona Sobhani, Director of Research and Operations at USC’s Center for Body Computing. But also the more potential for your privacy to be exposed. It doesn’t have to be that way. [video, 23:36]
The effective range of Wi-Fi, and other wireless communications used in Internet of Things networks could be increased significantly by adding wireless noise, say scientists.
This counter-intuitive solution could extend the range of an off-the-shelf Wi-Fi radio by 73 yards, a group led by Brigham Young University says. Wireless noise, a disturbance in the signal, is usually unwanted.
The remarkably simple concept sends wireless noise-energy over-the-top of Wi-Fi data traffic in an additional, unrelated channel. That second channel, or carrier, which is albeit at a much lower data rate than the native Wi-Fi, travels further, and when encoded can be used to ping a sensor, say, to find out if the device is alive when the Wi-Fi link itself may have lost association through distance-caused, poor handshaking.
“We now are in a position where you can address some really important questions in Puget Sound,” said Joel Baker, director of the University of Washington’s Puget Sound Institute.
One of the more surprising and hopeful results comes from a recently published study on climate change. It predicts that the Sound could in many ways fare a bit better than the Pacific Ocean when considering the damaging effects of a warmer world.
Cameras have allegedly fallen off; data have been deleted or mislabeled. A 2018 report found that most body-camera footage from fatal shootings never sees the light of day. As of June, the NYPD had a backlog of nearly 800 footage requests.
And now some police-reform advocates argue that recent technological advances mean these cameras are increasingly used not to scrutinize police, but to surveil the public. Recorded footage uploads to the cloud, allowing police to hold more images and videos, and to hold them longer. Object recognition lets officers quickly search through hours of footage to find items of interest (a red backpack, for example). With live-streaming, officers can send everything they see back to department headquarters nearly instantaneously.
Sending breeders into fields to manually measure the characteristics of plants is slow, laborious and expensive. Remote sensing technologies, coupled with advanced analytics, offer the promise of faster, more accurate data collection to improve the speed at which plant breeders can bring better cultivars to the market. … “Manual phenotyping is slow and costly. To do all of this measurement by hand takes a lot of people, and you don’t get a lot of data,” said Mitch Tuinstra, a Purdue professor of plant breeding and genetics, Wickersham Chair of Excellence in Agricultural Research, and principal investigator for the project. “Next-generation phenotyping technologies enable plant scientists and plant breeders to collect data automatically by remote sensing and process it using computational algorithms.”
At an A.I. conference last week at Stanford University, Stanford law professor David Engstrom discussed the challenges facing the federal government’s foray into machine learning. In many ways, the challenges mirror those facing corporations, like having employees how know how to operate sophisticated machine-learning software.
Engstrom shared some preliminary findings from the Stanford Policy Lab, which has analyzed technology use by the federal government. The team will eventually present the analysis to the Administrative Conference of the United States, a federal agency intended to improve government processes, to create guidelines for agencies using machine learning.
Holy Name Medical Center announced on Wednesday that Reg Grant joined its leadership team as director of human performance to develop and launch a new medical fitness program.
The program aims to prevent or reduce the incidence and severity of chronic illnesses and diseases, using an integrative approach focused on a person’s unique lifestyle.
Global Association of Risk Professionals, Katherine Heires
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Paul Ford brings an engineering mindset to solving a longstanding problem in operational risk management. His strategy: Aggregate risk and control data for the entire banking sector in a large-scale data network.
His goal is to have that network managed by Acin, a London- and New York-based company that Ford, a former Barclays and Credit Suisse executive, founded in 2018 and serves as CEO.
“We aim to bring the same kind of engineering and quantitative discipline we see in the markets and credit risk areas of banks to the operational risk area,” Ford says.
Space communications start-up Swarm Technologies will begin delivering commercial, bi-directional Internet of Things (IoT) data early next year, according to the company, which has just received its regulatory go-ahead to launch its satellites and transmit.
“Swarm will begin rolling out its commercial, two-way data offerings in early 2020,” Sara Spangelo, co-founder and CEO told me in a recent e-mail. The company aims to deploy 150 satellites before the end of 2020, she says. The FCC, in October, granted Part 25 approval for the startup to deploy and operate 150 non-geostationary, Low Earth Orbit (LEO) satellites, for non-voice purposes.
Swarm intends to target logistics, energy and the maritime verticals with what it promises to be a cheap service. Data over satellite, while allowing connections remotely across the entire globe unlike cellular, has historically been expensive: Satellite-communications incumbent Iridium’s Short Burst Data rates can be a dollar per kilobyte, for example. Swarm doesn’t say how much its service will cost. However, in January, the company obtained $25 million in Series A funding to build what Spangelo then described as “the world’s lowest cost satellite network.”
Morgan Stanley, National Geographic Society and the University of Georgia College of Engineering today announced a partnership to scale and enhance the citizen science movement to help prevent and reduce plastic waste in coastlines and waterways through support for the Marine Debris Tracker (Debris Tracker). The Debris Tracker is a mobile app that allows individuals to log plastic waste pollution as well as a suite of educational materials about the sources of, and solutions to, plastic waste. It is the only litter-tracking tool that enables users to learn by exploring and contributing to an open-data platform with over two million items tracked to date. Together, this partnership will improve understanding of the sources of plastic debris and pollution, generate scientific findings, inform solutions and inspire upstream design.
This partnership is a significant step in Morgan Stanley’s Plastic Waste Resolution aimed at tackling the growing global challenge of plastic waste in our environment.
CU Boulder researchers are working to apply machine learning to psychiatry, with a speech-based mobile app that can categorize a patient’s mental health status as well as or better than a human can.
“We are not in any way trying to replace clinicians,” says Peter Foltz, a research professor at the Institute of Cognitive Science and co-author of a new paper in Schizophrenia Bulletin that lays out the promise and potential pitfalls of AI in psychiatry. “But we do believe we can create tools that will allow them to better monitor their patients.”
University of California-Berkeley, Berkeley Division of Data Science and Information
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In recent decades, data systems have transformed from enabling basic transactions to facilitating complex interactions—from supporting “back office” record-keeping for banks and hospitals to enabling, capturing, and analyzing interchanges that power the likes of Amazon, Netflix, Facebook, and Lyft.
As the complexity and social implications of data-centric computing continue to intensify, Berkeley has redoubled its commitment and historic leadership in the field with a series of recent hires of leading faculty from across the country. This new cohort focuses on diverse facets of data systems, from protecting data security, to developing systems for massively-scalable machine learning, to working with data distributed across the globe. Combined with existing faculty, this infusion of experts places UC Berkeley at the center of academic research in systems to analyze and manage data.
The past decade has seen the emergence of the use of reinforcement learning models to study developmental change in value-based learning. It is unclear, however, whether these computational modeling studies, which have employed a wide variety of tasks and model variants, have reached convergent conclusions. In this review, we examine whether the tuning of model parameters that govern different aspects of learning and decision-making processes vary consistently as a function of age, and what neurocognitive developmental changes may account for differences in these parameter estimates across development. We explore whether patterns of developmental change in these estimates are better described by differences in the extent to which individuals adapt their learning processes to the statistics of different environments, or by more static learning biases that emerge across varied contexts. We focus specifically on learning rates and inverse temperature parameter estimates, and find evidence that from childhood to adulthood, individuals become better at optimally weighting recent outcomes during learning across diverse contexts and less exploratory in their value-based decision-making. We provide recommendations for how these two possibilities — and potential alternative accounts — can be tested more directly to build a cohesive body of research that yields greater insight into the development of core learning processes. [full text]
Any young writer who (isn’t) fully dominated by the algorithm is to me, godlike, because it’s so hard to resist. If you are under 30, and you are able to think for yourself right now, God bless you. If I was (that age), it would have defeated me entirely. All I wanted was people’s approval, and I would have been right in there tweeting it up.
It’s hard to resist that now.
The key with the unfreedom of the algorithm is that it knows everything and it feeds back everything. So, you can no longer have this bit of humanity which is absolutely necessary — privacy: the sacred space in which you do not know what the other thinks of you. You (come home) and close the door and go “Ah, I’ll put my sweats on.” I’ll be myself with the people I’m most intimate with who, in reality, are four people at most. That is what it is to be human. When that no longer exists it’s hard to be human. The recovery time to be human is gone.
As part of a statewide tech talent initiative, William & Mary committed to producing 930 more graduates with degrees in computer science over the next 20 years. On Nov. 7, Governor Ralph Northam allocated more than $1.3 million a year, beginning next year, to the college to help it reach its goal.
With the help of the Tech Talent Investment Program, Virginia plans to produce at least 25,000 to 31,000 more graduates with degrees in computer science and related fields in the next 20 years. Ten other schools including Virginia Tech, George Mason and the University of Virginia, were also awarded funding.
Research from Penn’s Socio-Spatial Climate Collaborative (SC)2 and McHarg Center, in partnership with Data for Progress (DFP), offered the data-driven foundation on which the legislation stands.
Led by (SC)2 Director Daniel Aldana Cohen, an assistant professor in the Department of Sociology, and Julian Brave NoiseCat, DFP’s vice president of policy and strategy, the team’s analysis found that beyond making conditions better for those who live in public housing, greening these spaces would equate to removing 1.2 million cars from the road each year—an important step in decarbonizing the U.S. economy—and would create about a quarter-million jobs annually across the country.
The University of Illinois is spending $500,000 to develop a business plan and economic impact study for its vaunted Discovery Partners Institute in Chicago.
Boston Consulting Group was hired in June to develop a two-year, five-year and 10-year business plan for the institute, according to documents provided to The News-Gazette.
Meanwhile, the institute’s budget grew to $4.2 million this year, according to the UI.
The Chicago-based research and education center is designed to bring together students and faculty from the UI and other universities to tackle big challenges and promote innovation and entrepreneurship, working with partners in industry, government and other sectors.
After leaving Oculus, Palmer Luckey started Anduril with a mission to build cutting-edge defense technology for the U.S. government.
Traditional defense contractors “do not have the world’s best talent when it comes to artificial intelligence, computer vision, and machine learning,” Luckey said.
Eigen Technologies, the legal and financial services AI doc review company, has completed a major $37m (£29m) Series B funding round co-led by Lakestar and Dawn Capital, with participation from Singapore’s sovereign wealth fund, Temasek, and Goldman Sachs Growth Equity.
The move is further proof that the money flowing into legal tech is not slowing, and that some startups are quite rapidly reaching later funding stages, as in this case, (see related market funding analysis).
The pioneering London-based company said that the fresh funding would help support its strategy of becoming a truly Transatlantic business, with the US seen as equally important to the AI company as the UK and other major markets where it operates.
WBUR, Here and Now, Jeremy Hobson and Allison Hagan
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Amtrak is on track to break even on its passenger railroad service next year for the first time in the company’s nearly 50-year history.
Founded in 1970, the national rail operator receives federal and state subsidies but the company is better known for losing money than turning a profit. Last week, the company reported an operating revenue of $3.3 billion for fiscal year 2019 — a 3.6% increase over the last year.
Richard Anderson, president and chief executive, says this marks Amtrak’s best operating performance ever. The company reported $29.8 million in losses — an 83% improvement over last year, he says — and has reduced operating losses by close to $400 million over the past year. [audio, 9:43]
The Hong Kong edition of EMNLP — called EMNLP-IJCNLP 2019 (IJC standing for International Joint Conference) — was held on November 5–7, 2019 and featured 465 long papers, 218 short papers, and 44 demo papers. There were just shy of 3,000 submissions, 37% more than in 2018.
At the closing ceremony held on November 9, 2019, EMNLP announced the winners of the four awards up for grabs: Best Paper, Best Paper Runner-Up, Best Demo Paper, and Best Resource Paper.
The Best Paper Award went to Xiang Lisa Li and Jason Eisner from John Hopkins University for their paper on Specializing Word Embeddings (for Parsing) by Information Bottleneck. The Runners-Up for Best Paper Award were John Hewitt and Percy Liang from Stanford University for Designing and Interpreting Probes with Control Tasks.
I’ve wondered about the improvements limitless intelligent connectivity will actually provide to the average person – and whether people are prepared to pay the price for it. Sasa Crnojevic believes we are moving into an era when you no longer need to carry ID, keys or money, but technology allows seamless and safe identification and access. An AI system can remotely monitor your health and automatically warn of potential problems, even alerting emergency services if necessary. The only question is whether people will be prepared to give up that much control over their data – and some of their privacy – for the sake of this level of connectivity and improved services. Will the trade-off be worthwhile?
The scale of supercomputing has grown almost too large to comprehend, with millions of compute units performing calculations at rates requiring, for first time, the exa prefix — denoting quadrillions per second. How was this accomplished? With careful planning… and a lot of wires, say two people close to the project.
Having noted the news that Intel and Argonne National Lab were planning to take the wrapper off a new exascale computer called Aurora (one of several being built in the U.S.) earlier this year, I recently got a chance to talk with Trish Damkroger, head of Intel’s Extreme Computing Organization, and Rick Stevens, Argonne’s associate lab director for computing, environment and life sciences.
The two discussed the technical details of the system at the Supercomputing conference in Denver, where, probably, most of the people who can truly say they understand this type of work already were.
Te U.S. Department of Energy’s Fermi National Accelerator Laboratory announced the launch of the Fermilab Quantum Institute, which will bring all of the lab’s quantum science projects under one umbrella. This new enterprise signals Fermilab’s commitment to this burgeoning field, working alongside scientific institutions and industry partners from around the world.
At IBM we’re committed to an exploratory science agenda, working with companies to advance innovation research and learning within their ecosystem. Today, IBM is embarking on a multi-year, collaborative effort with Wells Fargo focused on research and learning that is intended to enhance the company’s artificial intelligence and quantum computing capabilities. Together with IBM, Wells Fargo plans to accelerate its learnings to inform innovation initiatives that reimagine the future of financial services in a way that is designed to deliver customer experiences that are simple, fast, safe and convenient.
As part of the agreement, Wells Fargo will join the IBM Q Network, a community of Fortune 500 companies, startups, academic institutions and research labs working to advance quantum computing and explore practical applications. IBM will provide Wells Fargo access to the world’s largest fleet of quantum computing systems for commercial use case exploration and fundamental research at the IBM Quantum Computation Center.
Indiana University is developing a laboratory to help first responders and emergency management agencies before they get on the scene of a disaster, such as floods, hurricanes, and wildfires.
The Crisis Technologies Innovation Lab was created to deliver practical resources and solutions when facing a current severe weather crisis. It’s also intended to help emergency responders to plan for potential disasters.
“We might be entering a new phase where crises are a new normal, particularly on the coasts,” said David Wild, co-director of the CTIL. “Our life is a sandbox between an explosion of technology and the world of crisis and disaster and emergency response.”
The University of Louisville is teaming up with business leaders to launch Artificial Intelligence Innovation Consortium, a first-of-its kind alliance for the city.
The consortium, known as the AIIC, will bring together thought leaders to explore a holistic perspective on AI and where it can take the region. Participants in the new organization include Amazon Web Services, GE Appliances, Amgen, V-Soft Consulting and other Fortune 1000 companies, according to a news release.
AIIC will operate as a Louisville-based think tank of IT and advanced technology with thought leaders focusing on how AI can propel organizations and the community forward, the release said. Specifically, AIIC will build standards and best practices that help drive AI adoption, evolve privacy, data governance and bias, guiding principles and alignment of the AI evolution.
The European Economic and Social Committee (EESC) is adopting a firm stance on artificial intelligence and has insisted, at a high-level conference held in Helsinki on 21 November 2019, that the digital revolution must have a human face, be inclusive and bring benefits for all Europeans.
The New York Times will no longer use tracking pixels from Facebook and Twitter to track its users’ browser history, executives tell Axios.
What’s new: The company has created a marketing tool that will allow it to target potential subscribers on platforms like Facebook and Twitter without having to leverage its users’ general browsing history.
MIT researchers have invented a way to efficiently optimize the control and design of soft robots for target tasks, which has traditionally been a monumental undertaking in computation.
Soft robots have springy, flexible, stretchy bodies that can essentially move an infinite number of ways at any given moment. Computationally, this represents a highly complex “state representation,” which describes how each part of the robot is moving. State representations for soft robots can have potentially millions of dimensions, making it difficult to calculate the optimal way to make a robot complete complex tasks.
At the Conference on Neural Information Processing Systems next month, the MIT researchers will present a model that learns a compact, or “low-dimensional,” yet detailed state representation, based on the underlying physics of the robot and its environment, among other factors. This helps the model iteratively co-optimize movement control and material design parameters catered to specific tasks.
Ask medieval historian Michael McCormick what year was the worst to be alive, and he’s got an answer: “536.” Not 1349, when the Black Death wiped out half of Europe. Not 1918, when the flu killed 50 million to 100 million people, mostly young adults. But 536. In Europe, “It was the beginning of one of the worst periods to be alive, if not the worst year,” says McCormick, a historian and archaeologist who chairs the Harvard University Initiative for the Science of the Human Past.
A mysterious fog plunged Europe, the Middle East, and parts of Asia into darkness, day and night—for 18 months.
Over the past 10 years, much has changed. Technological advances are transforming not only how research – and peer review – is conducted, but the article formats and channels used to communicate those findings.
10 years on from the influential 2009 Peer Review Survey we have partnered with Elsevier to find out how far we have come. 3000 researchers were surveyed to understand how researcher attitudes have changed. Read the full report, Quality, trust & peer review: researchers’ perspectives 10 years on.
Researchers responded from a wide array of disciplines, career stages and locations. We repeated some of the questions asked in 2009, but importantly expanded our scope to capture feedback on trustworthiness, what constitutes peer review, and which metrics best signal quality and aid evaluation. We also wanted to understand how researchers view public confidence in research. In addition to the survey, we interviewed a number of researchers to explore the issues raised.
The building will also be the tallest on BU’s campus, with a four-story podium above a basement and then 13 floors on top of that, with a top floor for mechanical, electrical, and plumbing apparatuses.
What’s more, the building will be environmentally sustainable, according to BU—in fact, it’s supposed to be the most sustainable building in all of Boston. To that end, it will be built 5 feet above the city’s suggested level for sea rise, and will include features such as geothermal wells, shading systems, and triple-glazed windows. It is also being designed and built to not use fossil fuels at all.
Issues in Science and Technology magazine, Jeffrey Funk
from
The percentage of start-up companies in the United States that are profitable at the time of their initial public stock offering has dropped to levels not seen since the 1990s dotcom stock market bubble. Uber, Lyft, and WeWork have incurred higher annual and cumulative losses than any other start-ups in history. All the major ride-sharing companies, including those in China, Singapore, and India, are losing money, with total losses exceeding $7 billion in 2018 alone. Most start-ups involved in bicycle and scooter sharing, office sharing, food delivery, peer-to peer lending, health care insurance and analysis, and other consumer services are also losing vast amounts of money, not only in the United States but in China and India. These huge losses are occurring even though start-ups are remaining private companies twice as long as they did during the dotcom bubble. The size of these losses endangers the American venture capital system itself.
The large losses are easily explained: extreme levels of hype about new technologies, and too many investors willing to believe it. The result is what then-Federal Reserve Board chair Alan Greenspan, commenting on the dotcom bubble in 1996, called “irrational exuberance.” Nobel Laureate Robert Shiller, in his 2000 book of that title, describes the drivers of booms and busts in stock and housing markets, cycles that occurred for stocks during the twentieth century every 10 to 20 years. During a boom, price increases lead to more price increases as each increase seems to provide more evidence that the market will continue to rise. The media, with help from the financial sector, supports the hype, offering logical reasons for the price increases and creating a narrative that encourages still more increases. Rising prices for internet companies in the late 1990s, for instance, led many people to believe that rises would continue indefinitely as the media described a New Age Economy of internet companies that would reorganize product value chains and create enormous new profitability for online businesses. During a bust, the same thing happens in reverse, with a new narrative driving price declines that feed off themselves. Negative hype.
For the past 3 years Research to the People (Formerly SVAI) has done a variety of patient focused research hackathons: 3 day get togethers of researchers who analyze the genetic disease of a single patient. Read more about them here:
https://www.researchtothepeople.org/about (3/7)
The variety of machine learning applications is only going to increase, introducing radically different demands on storage performance, network bandwidth and compute, more akin to something seen in the world of supercomputers.
The idea that AI can replicate or amplify human prejudice, once argued mostly at the field’s fringes, has been thoroughly absorbed into its mainstream: Every major tech company now makes the necessary noise about “AI ethics.”
Yes, but: A critical split divides AI reformers. On one side are the bias-fixers, who believe the systems can be purged of prejudice with a bit more math. (Big Tech is largely in this camp.) On the other side are the bias-blockers, who argue that AI has no place at all in some high-stakes decisions.
In an email interview with The Verge, Chollet explained his thoughts on this subject, talking through why he believes current achievements in AI have been “misrepresented,” how we might measure intelligence in the future, and why scary stories about super intelligent AI (as told by Elon Musk and others) have an unwarranted hold on the public’s imagination.
Mortality due to substance abuse has increased in Appalachia by more than 1,000 percent since 1980. Deaths from diabetes, blood and endocrine diseases also increased in most counties in the United States during that time.
That’s according to a new study, published Tuesday in the Journal of the American Medical Association, examining the mortality rates for 21 leading causes of death. The study also found that the death rate from cardiovascular disease, the leading cause of mortality in the U.S., is down in most parts of the country. And the research highlights numerous disparities between counties. For example, a newborn is nearly 10 times more likely to die from a neonatal disorder if she is born in Humphreys County, Mississippi, which has the highest neonatal mortality rate in the country, than if she is born in Marin County, a wealthy area north of San Francisco, which has the lowest rate.
The computer scientist whom President Donald Trump picked this month as the next director of the National Science Foundation (NSF) has followed the path taken by an untold number of foreign-born researchers by seeking greater opportunities in the United States. If the Senate confirms him, as seems likely, 58-year-old, India-born Sethuraman Panchanathan will become not only the second NSF director of Asian American descent, but a living embodiment of how the international flow of talent has helped fuel U.S. leadership in global science.
A new study by UCLA computer scientists, statisticians and psychologists shows potential for robots powered by artificial intelligence to earn the trust of humans.
Published in Science Robotics, the study shows a robot not only knows how to open pill bottles with safety locks after a few rounds of human demonstration, it can also explain its behaviors in multiple ways in real time. The study was supported by the Defense Advanced Research Projects Agency, also known as DARPA.
“In the past, machines were designed to do exactly what they are supposed to do, and in restricted workspace under human control,” said Song-Chun Zhu, a UCLA professor of computer science and statistics. “As we enter a new age of AI, and rely on data-driven machines to make decisions and recommendations, they cannot yet explain those decisions and actions to human users. This has impeded the general acceptance of AI and robotics in critical tasks.”
Responsible Operations is intended to help chart library community engagement with data science, machine learning, and artificial intelligence (AI) and was developed in partnership with an advisory group and a landscape group comprised of more than 70 librarians and professionals from universities, libraries, museums, archives, and other organizations.
This research agenda presents an interdependent set of technical, organizational, and social challenges to be addressed en route to library operationalization of data science, machine learning, and AI.
The potential for digital healthcare to deliver time savings for medical practitioners is well documented. Dr. Eric Topol’s Topol Review, on preparing the health workforce to deliver this digital future, published earlier this year, highlights the “gift of time” as a major opportunity arising from digital health services. The report details the skills clinicians need to acquire to take advantage of these new digital technologies. Furthermore, it calls for the adoption of such technologies to, wherever possible, enable clinicians to gain more time to care and interact directly with patients, to enhance the patient-clinician relationship and improve the patient experience and patient safety.
China should introduce a regulatory framework for artificial intelligence in the finance industry, and enhance technology used by regulators to strengthen industry-wide supervision, policy advisers at a leading think tank said on Sunday.
“We should not deify artificial intelligence as it could go wrong just like any other technology,” said the former chief of China’s securities regulator, Xiao Gang, who is now a senior researcher at the China Finance 40 Forum.
Artificially-generated faces of people who don’t exist are being used to front fake Facebook (FB) accounts in an attempt to trick users and game the company’s systems, the social media network said Friday. Experts who reviewed the accounts say it is the first time they have seen fake images like this being used at scale as part of a single social media campaign.
With news that the United States may be considering a shift in their national open access policy, the Open Research Funders Group (ORFG) reaffirms its support for the sharing of research outputs as widely and quickly as possible. The ORFG, a partnership of 16 philanthropies with assets in excess of $100 billion, believes that open access (along with open data and broader open science activities) benefits society by potentially accelerating the pace of discovery, reducing information-sharing gaps, encouraging innovation, and promoting reproducibility.
From a practical standpoint, open access demonstrates a tangible return on taxpayer investment. Federal funds that support research have their highest impact when the results of this labor are shared, discussed, tested, and built upon with as few restrictions as possible.
Miss Virginia Camille Schrier earned the title of Miss America 2020 on Thursday night, beating out 50 other contestants for the prestigious crown after performing the show’s first-ever science demonstration in the talent portion.
This new API offers fully tagged and searchable access to faces across age ranges, ethnicities, and physical attributes. We are constantly improving our output results and have developed a brand new AI system to make sure faces that seem too ‘off’ never make it to production. This new process delivers class-leading consistency for AI developed imagery.
Conferences are undoubtedly an important part of academic life, but little is known about the extent to which conference presentations can advance researchers in their attempts to publish in scholarly journals. This column analyses more than 4,000 papers presented at three leading economics conferences over the 2006-2012 period, and finds that conference presentation is positively related to the likelihood of publication in high-quality journals. It also suggests that participating in major conferences helps improve research impact and visibility.
Cold Spring Harbor Laboratory, CHSL Stories and Media
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In this age of “big data,” artificial intelligence (AI) has become a valuable ally for scientists. Machine learning algorithms, for instance, are helping biologists make sense of the dizzying number of molecular signals that control how genes function. But as new algorithms are developed to analyze even more data, they also become more complex and more difficult to interpret. Quantitative biologists Justin B. Kinney and Ammar Tareen have a strategy to design advanced machine learning algorithms that are easier for biologists to understand.
The algorithms are a type of artificial neural network (ANN). Inspired by the way neurons connect and branch in the brain, ANNs are the computational foundations for advanced machine learning. And despite their name, ANNs are not exclusively used to study brains.
Biologists, like Tareen and Kinney, use ANNs to analyze data from an experimental method called a “massively parallel reporter assay” (MPRA) which investigates DNA. Using this data, quantitative biologists can make ANNs that predict which molecules control specific genes in a process called gene regulation.
Imagine being able to spray or paint bridges, houses and skyscrapers with the material, which would then capture light, turn it into energy and feed it into the electrical grid. That’s where this technology is going thanks to UCF.
The global hacker community continues to grow and evolve, constantly finding new targets and methods of attack. University of Arizona-led teams will be more proactive in the battle against cyberthreats thanks to nearly $1.5 million in grants from the National Science Foundation.
The first grant, for nearly $1 million, will support research contributing to an NSF program designed to protect high-tech scientific instruments from cyberattacks. Hsinchun Chen, Regents Professor of management information systems at the Eller College of Management, says the NSF’s Cybersecurity Innovation for Cyberinfrastructure program is all about protecting intellectual property, which hackers can hold for ransom or sell on the darknet.
“I care about the epistemological questions,” [Stephanie] Dick says. “I want to know how we know with the machine, what we know with it, what it knows—if anything, and how our knowledge is different for working within the confines of what computers can and cannot do. To do that, there’s no way around getting into the code. That’s what I think is the most important, to see how computer scientists have translated and transformed different problems and questions and ideas into code and what is gained and lost in the process.”
Learning Rate is a hyperparameter in deep learning which you tune to control how fast or slow the training of the algorithm happens. This learning rate is used to update the parameters (weights and biases) which we are trying to optimize.
In this article I will be talking about how you can slowly reduce the learning rate of your training algorithm over time. This is known as Learning Rate decay.
Now why this might help. Say you are training your neural network with a Gradient Descent algorithm (in back-propagation). If you have a constant learning rate, then even when you are close to the “global minima” you will take longer steps to learn and in the process deviate further from the minima. However if you keep slowly reducing the learning rate (alpha) then when you are close to the minima, you only move around in a tight spot and eventually converge at the minima. This is the intuition behind Learning Rate Decay.
GlaxoSmithKline is ramping up its use of artificial intelligence and recruiting 80 AI specialists by the end of 2020 as it turns to cutting-edge computing to develop medicines of the future.
However, the UK’s largest drugmaker by revenue is struggling to hire enough AI researchers and engineers from areas such as Silicon Valley and is looking to former employees in academia, the US Navy and the music industry to fill positions in the new team. They will be spread across London, Heidelberg, San Francisco, Philadelphia and Boston.
The AI unit will be headquartered in San Francisco, with one GSK executive admitting competition for AI professionals is fierce. “In AI, we are scouring the planet for the best people. These folks are very rare to find. Competition is high and there aren’t a large number of them,” said Tony Wood, GSK’s senior vice-president of medicinal science and technology.
G. Sayeed Choudhury is always looking for ways to do things more efficiently. It comes from his training as a civil engineer, which he learned is about focusing on people, processes, products and the workflows that connect them.
Choudhury, Associate Dean for Research Data Management and the Hodson Director of the Digital Research and Curation Center at Johns Hopkins University, applied his engineering expertise to transform the campus library system’s infrastructure and technology capabilities. Most recently, he led a team that built the “Public Access Submission System” (PASS), a platform to help researchers comply with the access policies of their funders and institutions. After the 2013 White House policy requiring public access was passed, SPARC encouraged developers to create a “unified deposit portal” for manuscript deposit.
Consumer Reports; Rachel Rabkin, Peachman. Andy Bergmann
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Infant heads are large and heavy in proportion to their body size and neck strength, and the sleeper’s 30-degree incline allowed Asher’s head to slump forward, blocking his trachea.
[Jan] Hinson, who is both a practicing lawyer and a former respiratory therapist, called Fisher-Price to alert the company to the problem. But company representatives said they stood by the safety of their product and had no plans to investigate, she says. So the Goodriches sued. “We could not stand the thought of another baby suffocating in the Rock ’n Play Sleeper,” says Hinson, who did not represent the family in the lawsuit.
Asher’s life-threatening episode wasn’t the only serious incident reported to Fisher-Price.
ProPublica; T. Christian Miller, Megan Rose, Robert Faturechi and Agnes Chang
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When the USS John S. McCain crashed in the Pacific, the Navy blamed the destroyer’s crew for the loss of 10 sailors. The truth is the Navy’s flawed technology set the McCain up for disaster.
The Interior Department is moving to formally define “habitat” in the Endangered Species Act, part of an anticipated second wave of changes to the bedrock conservation law under the Trump administration.
According to a notice published Monday by the White House Office of Information and Regulatory Affairs, the addition to the ESA is undergoing interagency review.
Interior’s Fish and Wildlife Service and the Commerce Department’s NOAA Fisheries are overseeing the proposed revisions.
The issue became a point of contention during a legal battle over FWS plans to protect the dusky gopher frog in Louisiana and the rights of private landowners, including timber giant Weyerhaeuser Co.
The Christmas season can have a major impact on human health. Especially increased contact with in-laws during the holiday season is an important environmental factor known to affect both physical and mental health (Mirza et al., 2004). However, the mechanism through which in-laws influence host health is not yet understood. Emerging evidence has identified the intestinal microbiota as an important mediator for both physical and mental health. Here, we performed a prospective observational study to examine the impact of contact with in-laws on the gut microbiome during the Christmas season. We conducted 16S ribosomal DNA sequencing of fecal samples collected at two separate time points (December 23rd and December 27th 2016) from a group of 28 healthy volunteers celebrating Christmas. To discriminate between participants who visited their own family versus their in-laws, we built a multivariate statistical model that identified microbial biomarker species. We observed two distinct microbial-biomarker signatures discriminating the participants that visited their in-laws versus their own family over the Christmas season. We identified seven bacterial species whose relative-change profile differed significantly among these two groups. In participants visiting in-laws, there was a significant decrease in all Ruminococcus species, known to be associated with psychological stress and depression. A larger randomized controlled study is needed to reproduce these findings before we can recognize in-laws as a potential risk factor for the gut microbiota composition and subsequently host health. [full text]
Two major research projects released this fall show steep declines in bird populations and a grim outlook as temperatures continue to warm. A USA TODAY Network analysis of the data shows the loss of birds touches every U.S. state in North America.
As Wes Biggs tells it, a Baltimore oriole flew onto his family’s front porch and landed on his bassinet when he was only 6 months old. Captivated, he became a lifelong bird-watcher.
Over the 71 years since then, like thousands of other longtime birders across the continent, Biggs has seen and helped document dramatic change.
Bald eagles surged back from the brink of extinction. Many duck species rebounded. But a host of other species — including sparrows, meadowlark and quail — declined at an alarming rate.
“You’re just not seeing thousands and thousands of birds anymore, and certainly not as often as you used to,” said Biggs of Sebring, owner of Florida Nature Tours.
As college enrollment rates drop across the nation, several Connecticut schools say they are bucking the trend.
Recently released statistics from the National Student Clearinghouse show that college and university enrollment in the U.S. dropped 1.3% from fall 2018 to fall 2019. In Connecticut, enrollment decreased by 1.6%, to about 184,000 students. Post-secondary enrollment has trended downward in the state since fall 2015 and nationally since fall 2012.
“A decreasing high school graduate population, coupled with stark increases in tuition at rates that far exceed inflation, could spell crisis,” said Angel Perez, vice president of enrollment and student success at Trinity College in Hartford.
Iowa’s ability to economically thrive in the future hangs on its residents’ digital skills, some say, and state leaders recognizing that have crafted laws and standards urging computer science education — with the Board of Regents now getting behind the push.
The board recently voted to add a computer science category to a list of high school subjects in-state students can take to qualify for assured admission to one of Iowa’s public universities — the University of Iowa, Iowa State University or the University of Northern Iowa.
Other subjects already on the list — according to the Regent Admission Index — are English, math, science, social studies and world language. The vote adds computer science to the list.
When hackers began slipping into computer systems at the Office of Personnel Management in the spring of 2014, no one inside that federal agency could have predicted the potential scale and magnitude of the damage. Over the next six months, those hackers — later identified as working for the Chinese government — stole data on nearly 22 million former and current American civil servants, including intelligence officials.
The data breach, which included fingerprints, personnel records and security clearance background information, shook the intelligence community to its core. Among the hacked information’s other uses, Beijing had acquired a potential way to identify large numbers of undercover spies working for the U.S. government. The fallout from the hack was intense, with the CIA reportedly pulling its officers out of China. (The director of national intelligence later denied this withdrawal.)
Personal data was being weaponized like never before. In one previously unreported incident, around the time of the OPM hack, senior intelligence officials realized that the Kremlin was quickly able to identify new CIA officers in the U.S. Embassy in Moscow — likely based on the differences in pay between diplomats, details on past service in “hardship” posts, speedy promotions and other digital clues, say four former intelligence officials. Those clues, they surmised, could have come from access to the OPM data, possibly shared by the Chinese, or some other way, say former officials.
“New technologies in the field allow us to collect more data than we ever dreamed of,” said BP HPC Computational Scientist Vladimir Bashkardin, referencing the properties of subsurface fluid and rocks obtained via energy responses to the company’s probing. “We need to scale our ability to access large seismic datasets, which can measure half a petabyte at times.”
To assist them in this monumental effort Bashkardin and his colleagues turned to the Department of Energy’s Oak Ridge National Laboratory, home to Summit, the world’s most powerful and “smartest” computer, and a wealth of expertise on how to manage and process today’s large and complex scientific datasets.
It’s no secret that I hate predictions — not least because the security field changes rapidly, making it difficult to know what’s next. But given what we know about the past year, we can make some best-guesses at what’s to come.
Ransomware will get worse, and local governments will feel the heat
File-encrypting malware that demands money for the decryption key, known as ransomware, has plagued local and state governments in the past year. There have been a near-constant stream of attacks in the past year — Pensacola, Florida and Jackson County, Georgia to name a few. Governments and local authorities are particularly vulnerable as they’re often underfunded, unresourced and unable to protect their systems from many major threats. Worse, many are without cybersecurity insurance, which often doesn’t pay out anyway.
When Abigail Thompson, chair of the math department at the University of California (UC), Davis, penned an essay in the December 2019 issue of the Notices of the American Mathematical Society criticizing mandatory “diversity statements” in university hiring, simmering frictions in math boiled over. Researchers rushed to author op-eds and joint public letters both supporting and opposing Thompson. The reactions reflect a tension between mathematicians who see efforts to promote diversity as an intrusion of politics into research, and those who see opening their field to historically marginalized communities as the surest way to advance research. As befits the field, each side claims numerical data support their view.
Academic math skews overwhelmingly white and male. According to American Mathematical Society data, women made up 30% of new tenure-track hires in 2018. Data for ethnicity are harder to come by, but black and Hispanic faculty are rare. According to a 2017 National Science Foundation diversity report, black people are earning fewer degrees in math today than 20 years ago.
University of Arizona researchers have been awarded $7.5 million to create an artificial intelligence agent that can understand social cues and human interactions, and use that information to help teams achieve their goals.
The grant comes from the Defense Advanced Research Projects Agency and is part of DARPA’s Artificial Social Intelligence for Successful Teams program.
“The goal of the ASIST program is to develop artificial intelligence with a ‘theory of mind,’ and create AI that is a good teammate to humans,” said Adarsh Pyarelal, a research scientist in the Machine Learning for Artificial Intelligence Lab in the University of Arizona School of Information. Pyarelal is the principal investigator for the DARPA-funded project.
eLife; William Hedley Thompson, Jessey Wright, Patrick G Bissett
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Arguments in support of open science tend to focus on confirmatory research practices. Here we argue that exploratory research should also be encouraged within the framework of open science. We lay out the benefits of ‘open exploration’ and propose two complementary ways to implement this with little infrastructural change. [full text]
The ocean is home to more biodiversity than anywhere else on the planet—making it a largely untapped source of opportunity for researchers studying marine organisms as a source of novel drug leads.
“The unique adaptations of marine organisms have made them valuable models for biomedical research, enhancing our understanding of fundamental biological processes, such as nerve function, immune system function, and cell division,” Andrea Bodnar, science director at the Gloucester Marine Genomics Institute, tells Xconomy.
Dubbed the “mouse model of the sea,” the sea urchin is among the organisms providing researchers with new insights.
The company’s web browser Chrome dominates the market, and that’s why Google got a lot of attention last week when it announced it intended to change the way ads are targeted online.
Google’s goal of making third-party cookies “obsolete” by 2022 will be a significant shift for the online advertising industry, which relies on the technology to serve personalised content.
“Users are demanding greater privacy…and it’s clear the web ecosystem needs to evolve to meet these increasing demands,” Justin Schuh, Google’s director of Chrome Engineering, wrote in a blog post.
The Karsh Family Foundation, established by Oaktree Capital Management co-founder Bruce Karsh and his wife Martha Karsh, has donated $10 million to Howard University to endow its STEM program.
Howard’s Science, Technology, Engineering and Math program, established in 2017, was designed to increase the number of underrepresented minorities earning post-graduate degrees in STEM fields. It will be renamed the Karsh STEM Scholars Program.
The US offers a limited number of H1-B visas annually, these are temporary 3-6 year visas that allow firms to hire high-skill workers. In many years, the demand exceeds the supply which is capped at 85,000 and in these years USCIS randomly selects which visas to approve. The random selection is key to a new NBER paper by Dimmock, Huang and Weisbenner. What’s the effect on a firm of getting lucky and wining the lottery?
Four experts in diverse aspects of artificial intelligence have joined Rensselaer Polytechnic Institute as part of the Artificial Intelligence Research Collaboration (AIRC), a recently formed joint initiative of Rensselaer and IBM Research.
“The addition of these faculty is expanding our interdisciplinary cohort of AI researchers across the entire campus. We expect these four outstanding faculty members are the first wave of hires who will increase our capabilities for AI and machine learning research across all five of Rensselaer’s schools,” said James Hendler, director of the AIRC, and a Rensselaer Tetherless World Professor of Computer, Web, and Cognitive Science.
World Economic Forum, Alois Zwinggi and Adrien Ogée
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The platform economy is changing how companies interact with customers. Enterprises need to connect with their customers efficiently to successfully and rapidly match the latter’s wants and needs with services and products. Being able to authenticate users to enable efficient and effective interaction with organizations is vital to business strategies of the future.
Password-based consumer authentication was initially designed for employees, not customers or clients. User experience was not a concern. Today, in the age of fingerprint readers and facial recognition, people expect a seamless customer experience, and passwords are becoming a key factor in poor customer retention rates. Furthermore, from setup to reset and decommission, password management is costing companies millions of dollars per year.
… SEMI: Mojo Vision has conducted its own research on human interaction with mobile devices. Why is this important?
Wiemer: Our mobile devices have given us access to the information we need and want, improving many aspects of our lives. But our devices have also influenced our relationships and attention to our environment in negative ways. We believe that the next mobile computing platform must improve this situation. Instead of pulling us away from the moment, our devices need to embrace more human-centric engagement while still letting us access information that improves our quality of life. Mojo Vision has worked to understand this problem through our own studies and research so we can better develop an approach to address it.
SEMI: How are key technical trends driving size, efficiency and capability advancements in mobile devices?
Wiemer: Tiny low-power sensors are enabling ever-smaller feature-rich mobile devices that run longer on a battery charge. Smartwatches are a good example. Just a few years ago, smartwatches were not that much more than small screens on our wrists. Today, we have GPS, EKG/health monitoring, and cellular wireless interfaces all inside the same form factor.
The days of wearable tech being a novelty are over. The Apple Watch is on its fifth version. Google in November doled out $2.1 billion to acquire FitBit. And reporting from the Consumer Electronics Show reinforced the notion that wearables will be a fixture in a consumer-driven healthcare economy.
To better understand the organization of the brain and the perceptual tendencies in humans, a team of four scientists are recording video from four head-mounted cameras – with eyetracking and head movement – and assembling a massive video database with more than 240 hours of first-person video that can be used by researchers everywhere.
“The brain is adapted to the world around us, but we don’t have good data on what the world actually looks like to human observers,” Mark Lescroart, an assistant professor and neuroscientist in the psychology department at the University of Nevada, Reno said. “There are no collections of videos that sample the world the way that humans do – Hollywood cinematographers don’t zip the cameras around as fast as human eyes move, so movies don’t really reflect the way we take in the world.”
National Oceanic and Atmospheric Administration, News and Features
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NOAA’s polar-orbiting and geostationary satellites are part of the global Search and Rescue Satellite Aided Tracking System, or COSPAS-SARSAToffsite link, which uses a network of U.S. and international spacecraft to detect and locate distress signals from emergency beacons aboard aircraft, boats and from handheld Personal Locator Beacons (PLBs) anywhere in the world.
Of the 421 U.S. rescues last year, 306 were water rescues, 38 were from aviation incidents and 77 were from events on land, where PLBs were used. Florida had the most SARSAT rescues with more than 100, followed by Alaska with more than 50. The previous rescue record of 353 (total) was set in 2007.
Creating detailed maps is an expensive, time-consuming process done mostly by big companies, such as Google, which sends vehicles around with cameras strapped to their hoods to capture video and images of an area’s roads. Combining that with other data can create accurate, up-to-date maps. Because this process is expensive, however, some parts of the world are ignored.
A solution is to unleash machine-learning models on satellite images — which are easier to obtain and updated fairly regularly — to automatically tag road features. But roads can be occluded by, say, trees and buildings, making it a challenging task. In a paper being presented at the Association for the Advancement of Artificial Intelligence conference, the MIT and QCRI researchers describe “RoadTagger,” which uses a combination of neural network architectures to automatically predict the number of lanes and road types (residential or highway) behind obstructions.
University of California-San Diego, UC San Diego UC San Diego News Center
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In a new University of California San Diego study, researchers examine data from Twitter during the 2014 conflict between Russia and Ukraine. The Russian television narrative, which is that a fascist coup had taken place, did not “catch on” in Ukrainian Russian-speaking communities. The only exception was Crimea. This could explain why Russia’s forces did not advance further than Crimea’s borders, as Russian analysts may have observed overt signals, including some from social media, that they would have faced strong and violent resistance.
“If you’re a conservative Russian military planner, you only send special forces to places where you are fairly certain they will be perceived as liberators, not occupiers,” said they study’s first author Jesse Driscoll, associate professor of political science at the UC San Diego School of Global Policy and Strategy. “A violent occupation of Russian-speaking communities that didn’t want the Russian soldiers to be there would have been a public relations disaster for Putin, so estimating occupation costs prospectively would have been a priority.”
To find out more, Observer talked with Ira Cohen, co-founder and chief data scientist of Anodot, a company dedicated to finding anomalies and glitches, like the gremlins that bedeviled warplanes 80 years ago. He must like cartoons, too, because he began our conversation by discussing a South Park episode—the one where Eric Cartman programs his Alexa to do all kinds of bizarre things. In fact, other Alexa devices started doing the same strange things that Cartman’s did. “Good monitoring would show lots of Alexas doing the same thing at the same time. We would catch these kinds of glitches,” he assured me.
How do they do it? “There are two ways our methods are better,” Cohen explained. “First is scale. There’s lots to look at… the sheer quantity of it all. Even small businesses have 100,000 things to check. The other is speed. You need to be able to look at things quickly and be able to find problems faster.”
Believe it or not, smaller companies are just as likely to take it on the chin when they get hit with gremlins. That’s because few of them currently use AI to check their products.
Cases of scientific misconduct are on the rise. For every 10,000 papers on PubMed, 2.5 are retracted, with more than half of these retractions attributed to scientific misconduct, which includes mismanagement of data and plagiarism.
“Papers from twenty or thirty years ago were fairly simple – they [had] maybe one or two photos,” says Elisabeth Bik, a microbiologist who now works as a scientific integrity consultant. “That’s around the time that I did my PhD. If we wanted to submit papers with photos, we had to make an actual appointment with a photographer! It was very hard to fake anything.”
Companies involved in software development, either for external customers or for their own internal needs, face a variety of challenges. A shortage of skilled developers is impeding efforts to create quality software. Development projects often go awry. Many are late, go over budget, or are simply cancelled before they come to fruition. And despite the best efforts of programmers and other pros, finished applications can be hampered by bugs. One factor that can alleviate some of these obstacles is artificial intelligence (AI) , according to a new report from Deloitte.
Proceedings of the National Academy of Sciences, Christopher Barrington-Leigh and Adam Millard-Ball
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The pattern of new urban and residential roads represents an essentially permanent backbone that shapes new urban form and land use in the world’s cities. Thus, today’s choices on the connectivity of streets may restrict future resilience and lock in pathways of energy use and CO2 emissions for a century or more. In contrast to the corrective trend observed in the United States, where streets have become more connected since the late 20th century, we find that most of the world is building ever-more disconnected “street-network sprawl.” A rapid policy response, including regulation and pricing tools, is needed to avoid further costly lock-in during this current, final phase of the urbanization process.
National Affairs, James Piereson & Naomi Schaefer Riley
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In recent years, public universities have faced a troubling question: Can they remain financially solvent while serving their own residents at the low tuition rates that were common several decades ago? In other words, can they have their cake and eat it too? A recent survey of flagship state universities conducted by the Washington Post concludes that the answer is probably no.
Among the 50 state universities surveyed, 44 have experienced a decrease in their percentage of in-state students in the past decade. Just 51% of the students at the University of Michigan in fall 2016 were actually Michigan residents, down 13 percentage points from 10 years before. With the continuing decline in legislative appropriations for higher education, public universities are trying to fill the gap by recruiting higher-paying out-of-state students.
This is part of a frantic effort by public universities around the country to sustain a financial model they inherited from the 1950s and 1960s.
We are standardizing OpenAI’s deep learning framework on PyTorch. In the past, we implemented projects in many frameworks depending on their relative strengths. We’ve now chosen to standardize to make it easier for our team to create and share optimized implementations of our models.
npj Digital Medicine; Alicia L. Nobles, Eric C. Leas, Theodore L. Caputi, Shu-Hong Zhu, Steffanie A. Strathdee & John W. Ayers
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We investigated how intelligent virtual assistants (IVA), including Amazon’s Alexa, Apple’s Siri, Google Assistant, Microsoft’s Cortana, and Samsung’s Bixby, responded to addiction help-seeking queries. We recorded if IVAs provided a singular response and if so, did they link users to treatment or treatment referral services. Only 4 of the 70 help-seeking queries presented to the five IVAs returned singular responses, with the remainder prompting confusion (e.g., “did I say something wrong?”). When asked “help me quit drugs” Alexa responded with a definition for the word drugs. “Help me quit…smoking” or “tobacco” on Google Assistant returned Dr. QuitNow (a cessation app), while on Siri “help me quit pot” promoted a marijuana retailer. IVAs should be revised to promote free, remote, federally sponsored addiction services, such as SAMSHA’s 1-800-662-HELP helpline. This would benefit millions of IVA users now and more to come as IVAs displace existing information-seeking engines.
The Predictive Risk Investigation System for Multilayer Dynamic Interconnection Analysis (PRISM), funded by the National Science Foundation (NSF) and co-led by David S. Matteson, associate professor of statistics and data science, aims to harness data in order to identify risk factors across domains for catastrophic events such as the 1989 blackout – which impacted transportation, food, water, health and finance and racked up costs exceeding $2 billion.
With a team of experts in fields including data science, statistics, computer science, finance, energy, agriculture, ecology, hydrology, climate and space weather, PRISM will integrate data across different areas to improve risk prediction.
Several companies and universities have teamed up to develop mathematical approaches and tools for incorporating data-based machine learning algorithms into cyber physical systems as part of a Defense Advanced Research Projects Agency program aimed at ensuring the safety of autonomous technology.
Participants have demonstrated signs of progress in their 18-month research and development efforts under the first phase of DARPA’s Assured Autonomy program, the agency said Wednesday.
Boeing collaborated with the University of California at Berkeley, Collins Aerospace and SGT Inc. to create an ML-based system design and analysis toolkit, dubbed VerifAI, that seeks to increase safety of aircraft systems during operations on ground.
Berkeley health-tech startup Eko was granted FDA clearance today to take its algorithm for detecting atrial fibrillation to the market.
The algorithm, in tandem with a digital stethoscope, is meant to be used to screen for atrial fibrillation and other types of heart disease caused by heart murmurs — a condition that can result in a stroke or heart failure if left untreated.
Connor Landgraf, CEO and co-founder of Eko, said it is the first in-office screening algorithm used with a stethoscope to be cleared by the FDA.
The Institute for Statistics Education at Statistics.com is excited to announce that it has been acquired by Elder Research, Inc, a Machine Learning, Data Science, and AI consulting firm headquartered in Charlottesville, VA. Peter Bruce, Founder of the Institute said “Elder Research’s quarter century of expertise in data science consulting and training for leading companies and government agencies brings a powerful dose of practical experience to the Institute’s offerings. Joining forces with Elder Research will give Institute students the real-world skills they need to successfully deploy the techniques they learn, and a good view of potential careers.” Statistics.com’s existing courses, certificate programs, and degree programs will continue.
The United States Census Bureau has announced that it will endorse differential privacy as the disclosure avoidance mechanism for the 2020 Census. In a layperson’s terms, this means that census counts will be infused with random noise prior to release. The aim is to reduce (substantially) the chances that sophisticated hackers can recover individual data from the reported aggregate counts. But as always, there is no free lunch. The injection of noise makes the data less useful and, if not analyzed/interpreted properly, misleading. As emphasized in the leading discussion article by Provost Teresa Sullivan, ensuring reliable Census data underpins “our democracy (and republic),” a point echoed and expanded upon by nine scholars and census experts from several countries. (The use of differential privacy in one country can obviously be tried in other countries.) Indeed, conducting reliable decennial censuses is mandated by the US Constitution. Why then is the Census Bureau allowed to add noise to essentially every data point produced?
The answer is not hard to find. The law also requires that the Census Bureau protect data privacy, a requirement that I am sure a vast majority of us would appreciate. Even if there were no such legal requirement, it would still be essential for any census bureau or data collectors to ensure as much privacy as possible, for the very purpose of improving data quality and quantity. How many of us have ignored surveys and opinion polls in the past, even in the absence of privacy concerns? Humans are the ultimate dilemma creators: we like to know more about others, and we dislike others knowing more about us. But others’ others are us. The Census Bureau, therefore, has a mathematically impossible task: to produce accurate and privacy-protected data.
The largest radio conglomerate in the country, iHeartMedia, initiated a round of mass layoffs this week, cutting enough people that one former on-air host described Tuesday as “one of the worst days in on-air radio history.” The layoffs were concentrated in small and medium markets, where staffs had already been reduced, striking another major blow to local radio.
Some employees began to suspect that cuts were coming last week. “There was a very urgent, emergency meeting called in New York City for market presidents and higher-level local management,” says one former iHeartMedia employee who spoke on the condition of anonymity so as not to jeopardize a severance package. (Many declined to comment, citing the same reason.) “We heard a lot of different rumors, including talk about automating certain markets depending on the revenue [they generated].”
For other iHeartMedia employees, the first sign of trouble came early Tuesday morning, when the company sent employees an email announcing a “new organizational structure.” The memo, obtained by Rolling Stone, seemed plucked partly from a corporate-culture parody like Office Space. I
In the coming decade, big projects like the Large Hadron Collider (LHC) and the Square Kilometre Array (SKA) are each expected to produce an exabyte of data yearly, which is about 20 times the digital content of all the written works throughout human history. This information overload requires new thinking about data management, which is why scientists have begun to look to the “cloud.” In such a scenario, data would be stored and analyzed remotely, with the advantage that information would become more accessible to a wider scientific community. Efforts are underway to create “science clouds,” but disagreements remain over their structure and implementation. To discuss these details, around 60 scientists came together for The Science Cloud meeting in Bad Honnef, Germany. The attendees shared lessons from past and ongoing projects in the hope of building the groundwork for a future scientific computing infrastructure.
The three-day meeting, held in a 19th century building of the German Physical Society, brought together physicists, astronomers, and computer scientists for the purpose of identifying “a common set of needs,” says meeting organizer Karl Mannheim, an astrophysicist from the Julius Maximilian University of Würzburg, Germany. He believes these sorts of discussions will help steer scientific data projects at the national and international level. In Europe, for example, in 2018 the European Union launched the European Open Science Cloud, which aims to be a one-stop portal for multidisciplinary research.
Three University of Miami innovators served as judges on a National Football League pitch competition that was designed to boost advancements in athlete health and safety. The event was part of the University’s collaboration with the NFL, which hosted a range of Super Bowl activities in Miami this past week.
The NFL’s 1st and Future competition, held Friday at the Miami Beach Convention Center, reviewed presentations on both innovative product concepts and analytics and data models—which compared factors such as natural versus synthetic turf with the aim to reduce the potential for injury, especially to lower limbs.
Dan Hellie, host of NFL Total Access, emceed the event he described as “a little bit ‘Shark Tank’ and a little bit ‘Oprah’ ” and a “unique and very cool look into the future and the innovation of our great game.”
Intel’s AI ASIC strategy will be based on Habana chips from now on
In a move widely speculated to have been looming, Intel has axed Nervana’s NNP-T and NNP-I training and inference chips for the data center in favor of Gaudi and Goya chips from recent acquisition Habana Labs.
A statement emailed to EETimes said that Intel will cease development on Nervana’s NNP-T AI training chip (Spring Crest) for the data center, while merely honoring existing customer commitments to the NNP-I inference chip (Spring Hill), following “customer feedback”.
Like watching a familiar play, but this time from the balcony and with a new set of binoculars, satellite remote sensing technology is giving Michigan State University researchers a powerful lens to view landscapes that set the stage for earth’s biodiversity.
“Geodiversity, or the variations in abiotic processes and features of the landscape such as landmarks, topography and unique soil types, have yet to be quantified at different scales in the United States,” said Phoebe Zarnetske, assistant professor in the Department of Integrative Biology in the MSU College of Natural Science and principal investigator of the project. “We wanted to know if, thanks to advances in satellite remote sensing, we could measure geodiversity in a new way and align it with already established patterns of biodiversity.”
“We are especially interested in the scales at which geodiversity and biodiversity relate most closely,” Zarnetske continued. “Is geodiversity more closely related with biodiversity at fine resolutions, at a plot scale for example, or does it correlate better if we zoom out to a larger area?”
Partnership for Public Service , Center for Presidential Transition
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The 2020 presidential campaign is well underway as the first primaries and caucuses rapidly approach. Soon, presidential hopefuls will need to assemble a team to plan a transition — either to a new administration or a second term.
One of the most important tasks for any administration is filling more than 4,000 political appointments. Yet, as Amanda Patarino recently wrote in the Kennedy School Review, progress is hampered for transitions teams because official listings and data about these positions is often problematic and unreliable.
One of the primary sources of information about political appointments is the Plum Book, published by Congress and the Government Publishing Office after each presidential election. Unfortunately, as Patarino points out, data in the Plum Book is often “outdated, unreliable and cumbersome.”
Carnegie Learning announced today its commitment to a new National Science Foundation (NSF)-funded project to build a Learner Data Institute that will harness the power of data to better understand how people learn, improve adaptive instructional systems, and make the learning technology ecosystem more effective and cost-efficient. The project, led by Dr. Stephen Fancsali, Director of Advanced Analytics at Carnegie Learning, and Dr. Vasile Rus, Professor of Computer Science at The University of Memphis (Tennessee), will bring together researchers from universities, government agencies, and private companies to collaborate on improving educational outcomes everywhere.
A multidisciplinary University at Buffalo research team has received an $800,000 grant to develop a machine learning system that could eventually help caseworkers and human services agencies determine the best available services for the more than 20,000 youth who annually age out of foster care without rejoining their families.
The National Science Foundation and Amazon, the grant’s joint funders, have partnered on a program called “Fairness in Artificial Intelligence” (FAI) that aims to address bias and build trustworthy computational systems that can contribute to solving the biggest challenges facing modern societies.
The University of Rochester research lab that recently used lasers to create unsinkable metallic structures has now demonstrated how the same technology could be used to create highly efficient solar power generators.
In a paper in Light: Science & Applications, the lab of Chunlei Guo, professor of optics also affiliated with the Department of Physics and Astronomy and the Material Sciences Program, describes using powerful femto-second laser pulses to etch metal surfaces with nanoscale structures that selectively absorb light only at the solar wavelengths, but not elsewhere.
A regular metal surface is shiny and highly reflective. Years ago, the Guo lab developed a black metal technology that turned shiny metals pitch black. “But to make a perfect solar absorber,” Guo says, “We need more than a black metal and the result is this selective absorber.”
Understanding how employment gaps can affect careers is especially relevant given the recent policy discussions around paid family leave and childcare access in the U.S.
I am a sociologist whose research examines what happens to people’s careers after they take time out of work. I find that gaps in employment can negatively affect future career prospects in multiple ways, particularly for those who left work for childcare responsibilities.
“Invisible oil” escaped the view of satellites that were tasked with measuring the extent of the Deepwater Horizon spill in the Gulf of Mexico in 2010, according to a new study. In the Science Advances article, researchers argue that updated techniques need to be deployed alongside satellite measurements to track future oil spills below the water’s surface.
BP’s Deepwater Horizon rig spewed more than 200 million gallons into the Gulf in 2010. At the time, satellite readings were used to determine which areas in the Gulf were off-limits to fishing, but the dangers posed by the spilled oil to fish and the humans who eat them spread beyond those boundaries. In places where oil from the spill was no longer visible from space, it still persisted in concentrations that were enough to be toxic. The extent of the spill could have been as much as 30 percent larger than previous estimates, according to study authors.
New computer models can now more accurately predict how a spill will spread. Used in tandem with satellite remote sensing and measurements taken at the site of the spill, these advancements can make for a faster and more effective cleanup in the event of another disaster.
The online part-time degree will teach students in the computational, mathematical and statistical foundations of Machine Learning. Applications are now open on the College website.
Students will also have the opportunity to work with industry-standard tools like PySpark and PyTorch to develop and apply their Machine Learning and data science skills. Over the coming year a number of specialisation courses will be released which will give students the opportunity to explore these diverse areas.
This Master’s course aims to accelerate learners’ careers in engineering or data science, supporting them to choose a path that’s right for their skill set. This could be as a data scientist, a machine learning engineer, or a computational statistician.
MIT Technology Review, Karen Hao and Jonathan Stray
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Until pretty recently, computers were hopeless at producing sentences that actually made sense. But the field of natural-language processing (NLP) has taken huge strides, and machines can now generate convincing passages with the push of a button.
These advances have been driven by deep-learning techniques, which pick out statistical patterns in word usage and argument structure from vast troves of text. But a new paper from the Allen Institute of Artificial Intelligence calls attention to something still missing: machines don’t really understand what they’re writing (or reading).
Harvard T.H. Chan School of Public Health, Magazine
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Over the past decade, Buckee, who pins a visitor with her direct gaze and gestures frequently with her hands when explaining heady concepts, has been building systems to track and forecast the spread of lethal infections, including malaria, dengue, Ebola, and cholera. Being able to follow the path of a parasite, bacterium, or virus is crucial to getting ahead of it and stopping a localized outbreak from blossoming into an epidemic, and an epidemic from ballooning into a pandemic. Buckee’s work blends tried-and-true epidemiological methods that go back as far as John Snow with bleeding-edge technology. Among her more high-profile pursuits is using location data from mobile phones to study how and where diseases spread. “In terms of epidemic forecasting, being able to know where people are going is hugely important,” she says. “And mobile phone data answers very specific questions about how people travel around.”
Drawing on massive aggregated, anonymized data sets provided by phone companies, Buckee looks for what she calls “coarse-scale mobility flows.” It’s the type of information that can show, for instance, that 40,000 people moved from County A to County B one day, and that 10,000 people moved from County B to County C another day. In numerous peer-reviewed studies, Buckee and colleagues have shown that these large-scale trends can be turned into epidemiologically relevant patterns of movement. These patterns could then be translated into risk maps so that health officials can better allocate resources to prevent and fight outbreaks.
Toast’s new valuation is a leap from $2.7 billion in April when it raised $250 million in April. Toast said it would use the money to invest in its technology and fund research and development.
“We’re at the stage when companies would consider going public, but we’re not in any rush yet,” Toast Chief Executive Officer Chris Comparato said in an interview. “Going public is a milestone and we want to have certain projects under our belt as a private company.”
Another player in the restaurant software space, Olo, is preparing for an initial public offering later this year, Bloomberg News has reported.
Reyes is now the head of analytics at the Ayala Corporation, a business conglomerate in the Philippines with interests in industries such as water, power, infrastructure, healthcare and education (to name a few). Her job allows her to use many of the skills she developed as an astrophysicist: problem solving, statistics and modeling, programming techniques, and the ability to work with large datasets. And most importantly, she says, it allows her to touch people’s lives.
This morning global health nonprofit Medic Mobile launched its new health tech accelerator Medic Labs. The accelerator will be focused on providing equitable healthcare globally and using data science to propel this effort. A $3 million grant from The Rockefeller Foundation will kick off Medic Lab’s initial efforts.
Medic Lab will focus on three areas: human-centered design, data integration and data interoperability (including third-party solution integration).
Using a machine-learning algorithm, MIT researchers have identified a powerful new antibiotic compound. In laboratory tests, the drug killed many of the world’s most problematic disease-causing bacteria, including some strains that are resistant to all known antibiotics. It also cleared infections in two different mouse models.
The computer model, which can screen more than a hundred million chemical compounds in a matter of days, is designed to pick out potential antibiotics that kill bacteria using different mechanisms than those of existing drugs.
“We wanted to develop a platform that would allow us to harness the power of artificial intelligence to usher in a new age of antibiotic drug discovery,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering. “Our approach revealed this amazing molecule which is arguably one of the more powerful antibiotics that has been discovered.”
An analysis of “some of the most heavily funded private companies” found that 60% do not have any women on the board, and only 7% of seats are held by women.
It’s unclear how many of those private companies may look to go public. But a recent high-profile IPO effort shows that when a company with an all-male board tries to go public, an uproar can ensue. When WeWork filed its registration for an IPO last year, the company noted its “culture of inclusivity” — but also listed its board members, all of whom were men. Controversy erupted, and the company added a woman. (This problem was soon overshadowed by numerous other problems plaguing WeWork.)
Goldman’s new rule may stem from the best of intentions. But as founder of a company that works to bring gender equality to one of the most male-dominated industries — the energy sector — I see it as misguided, and potentially damaging.
The technology giant is discussing whether to let users choose third-party web browser and mail applications as their default options on Apple’s mobile devices, replacing the company’s Safari browser and Mail app, according to people familiar with the matter. Since launching the App Store in 2008, Apple hasn’t allowed users to replace pre-installed apps such as these with third-party services. That has made it difficult for some developers to compete, and has raised concerns from lawmakers probing potential antitrust violations in the technology industry.
The web browser and mail are two of the most-used apps on the iPhone and iPad. To date, rival browsers like Google Chrome and Firefox and mail apps like Gmail and Microsoft Outlook have lacked the status of Apple’s products. For instance, if a user clicks a web link sent to them on an iPhone, it will automatically open in Safari. Similarly, if a user taps an email address — say, from a text message or a website — they’ll be sent to the Apple Mail app with no option to switch to another email program.
New Mexico is suing Google for allegedly invading children’s privacy through educational products it provides to the state’s schools, claiming it tracks students’ activities on their personal devices outside the classroom. The suit calls into question what a major for-profit player in the nonprofit educational space — which counts millions of children among its users — is doing with whatever data it collects from them.
I asked more than 20 young Silicon Valley types to talk with me about their personal finances in the hopes that one of them would tell me about their prenup. Not a single one of them would.
But they’re talking to someone about prenups: the lawyers they’re hiring to draft them.
Family law specialists in San Francisco and Silicon Valley say millennials in tech are seeking prenups at much higher rates than their elders did — and that they’re using them to prevent potential post-marital problems that their predecessors never had to consider.
The new Data Science track at Moravian will include an “applications” course in which students will learn how to use data in real-life situations and come to understand the ethical implications of data and data analysis. All Moravian students engaged in this track will be strongly encouraged to complete an internship in a relevant field as part of the program. In 2019 the Moravian Graduate program launched the Master of Science in Predictive Analytics (MSPA), and the undergraduate Data Science track is an ideal precursor to the MPSA program for students interested in pursuing a graduate degree.
In this Let’s Talk Exascale podcast, Ian Foster from Argonne National Lab describes how the CODAR project at ECP is addressing the needs for data reduction, analysis, and management in the exascale era. [audio, 7:12]
Gaby Ecanow loves listening to music, but never considered writing her own until taking 6.S191 (Introduction to Deep Learning). By her second class, the second-year MIT student had composed an original Irish folk song with the help of a recurrent neural network, and was considering how to adapt the model to create her own Louis the Child-inspired dance beats.
“It was cool,” she says. “It didn’t sound at all like a machine had made it.”
This year, 6.S191 kicked off as usual, with students spilling into the aisles of Stata Center’s Kirsch Auditorium during Independent Activities Period (IAP). But the opening lecture featured a twist: a recorded welcome from former President Barack Obama. The video was quickly revealed to be an AI-generated fabrication, one of many twists that Alexander Amini ’17 and Ava Soleimany ’16 introduce throughout their for-credit course to make the equations and code come alive.
What kind of promoted search behavior is acceptable?
Clearly, promoted search results should be useful to searchers. Otherwise everyone loses: searchers waste their time, advertisers don’t obtain useful leads, and search providers lose money and customers.
But usefulness, while necessary, is not sufficient. There are at least three other requirements: transparency, ethical design, and fairness.
EurekAlert! Science News, Association for Computing Machinery
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ACM, the Association for Computing Machinery, today announced the inaugural issue of Digital Government: Research and Practice (DGOV), a new interdisciplinary open access journal on the impact of technology on governance and public institutions. DGOV presents applied and empirical research from academics, practitioners, designers and technologists, using political, policy, social, computer and data science methodologies. … “Digital technologies have reshaped how governments function at every level, as well as how citizens interact with government and each other,” said DGOV Co-Editor-in-Chief Soon Ae Chun of the City University of New York.
Largo Films, an EPFL spin-off, unveiled its data-assisted movie-making software to producers and other movie-industry specialists today at the Berlin Film Festival. Largo’s program uses artificial intelligence to generate recommendations for just about every stage of the filmmaking process – from putting together a script and soundtrack to selecting the actors and emotional register – all in just a few minutes.
In spring 2018, Seleta Reynolds, the general manager of the Los Angeles Department of Transportation, issued a grave warning about the new generation of urban transportation companies such as Uber.
“A lot of these private actors and companies are not mobility companies,” Reynolds told an audience at Harvard’s Graduate School of Design. “They are data companies. And they are building new empires on top of a platform that we are absolutely not ready for.”
The power dynamics must shift, she continued. “We have to bust our ways of thinking inside government in particular.”
Seven years ago, Allstate Corporation told Maryland regulators it was time to update its auto insurance rates. The insurer said its new, sophisticated risk analysis showed it was charging nearly all of its 93,000 Maryland customers outdated premiums. Some of the old rates were off by miles. One 36-year-old man from Prince George’s County, Md., who Allstate said in public records should have been paying $3,750 every six months, was instead being charged twice that, more than $7,500. Other customers were paying hundreds or thousands of dollars less than they should have been, based on Allstate’s new calculation of the risk that they would file a claim.
Rather than apply the new rates all at once, Allstate asked the Maryland Insurance Administration for permission to run each policy through an advanced algorithm containing dozens of variables that would adjust it in the general direction of the new risk model. Allstate said the goal of this new customer “retention model,” which it was rolling out across the country, was to limit policy cancellations from sticker shock.
The Emory Healthcare Innovation Hub (EHIH) announced Monday that it will be powered by Verizon 5G Ultra Wideband service, adding digital speed and connectivity to an ecosystem working to transform the health care industry.
The strategic partnership between Verizon and Emory Healthcare creates the nation’s first 5G health care innovation lab.
EHIH is a health care advancement and commercialization program committed to improving patient care and provider experience. The addition of Verizon 5G gives researchers the ability to explore solutions such as connected ambulances, robotic-assisted surgery, remote physical therapy and next-generation medical imaging.
Amazon made headlines Tuesday with the debut of its newest cashierless grocery store concept in Seattle. The opening drew hundreds of smartphone-equipped shoppers eager to try out the “Just Walk Out” technology that removes the checkout process from the shopping experience.
But does greater automation mean lower prices? GeekWire sought to answer this question with our own test Tuesday evening, shopping for identical products at both Amazon Go Grocery and the Kroger-owned QFC just down the street in Seattle’s Capitol Hill neighborhood. Kroger is one of several incumbents facing new competition from Amazon, which is making moves in the $800 billion U.S. grocery industry since its 2017 acquisition of Whole Foods.
We compared a basket of 17 items, from fresh vegetables to packaged goods. The verdict? We saved more than 5 percent, or $2.92, at Amazon Go Grocery, paying $52.78 for items that cost $55.70 with a club card at the nearby QFC. Without a QFC club card, the difference would have been nearly 25 percent, a savings of about $10.
Six months ago or thereabouts, a group of engineers and developers with backgrounds from the National Security Agency, Google and Amazon Web Services had an idea.
Data is valuable for helping developers and engineers to build new features and better innovate. But that data is often highly sensitive and out of reach, kept under lock and key by red tape and compliance, which can take weeks to get approval. So, the engineers started Gretel, an early-stage startup that aims to help developers safely share and collaborate with sensitive data in real time.
It’s not as niche of a problem as you might think, said Alex Watson, one of the co-founders. Developers can face this problem at any company, he said. Often, developers don’t need full access to a bank of user data — they just need a portion or a sample to work with. In many cases, developers could suffice with data that looks like real user data.
We partnered with Digital Science and figshare on the State of Open Data report 2019, the fourth annual report examining attitudes and experiences of researchers working with open data. Download the infographic below, or click Read More for the full report.
More than 50 organizations – from major tech giants to startups and health care industry leaders – convened by the Consumer Technology Association (CTA)® have developed the first-ever ANSI-accredited standard for the use of artificial intelligence in health care. This standard, part of CTA’s new initiative on AI, is the first in a series that will set a foundation for implementing medical and health care solutions built on AI.
“This standard creates a firm base for the growing use of AI in our health care—technology that will better diagnose diseases, monitor patients’ recoveries and help us all live healthier lives,” said Gary Shapiro, president and CEO, CTA. “This is a major first step – convening some of the biggest players in the digital health world – to help create a more efficient health care system and offer value-based health care to Americans.”
We’re trying to do better going forward. But in general, it is *always* a good idea to ask senior people (especially the women!) in your field what a person is like to work with, before you coauthor with someone new. You might be amazed at the stories they’ll tell you.
1. Full-stack & back-end developers are in highest demand
Of the hiring managers that answered the survey, 38% said that “full-stack developer” is the most important role they need to fill in 2020. Back-end developers, on the other hand, were top priority for 24% of hiring managers. Priorities shifted slightly with company size, but across the board, full-stack developers are the #1 priority.
It should be possible for researchers in the life sciences to draw on powerful technological services throughout Germany when they need to analyse large data sets. This is why the Federal Ministry of Education and Research (BMBF) invested about 80 million euros in a major large-scale project: the German Network for Bioinformatics Infrastructure (de.NBI). Bielefeld University is coordinating the project. On Thursday 13 February, scientists and politicians celebrated the fifth anniversary and the previous successes of the network with a symposium in Berlin. These successes include a distributed cloud infrastructure, eight service centres throughout the nation, and 40 participating bioinformatics groups. The BMBF has now announced continued funding for the de.NBI. Until the end of 2021, Bielefeld University alone will have up to 5.3 million euros at its disposal to continue the project.
University of Oxford, The Oxford Student newspaper, Matthew Kayanja
from
Oxford University has been given a £5.5m grant by the Engineering and Physical Sciences Research Council (EPSRC) to help develop computers usable for the highest levels of scientific research. The project, known as JADE 2 (standing for Joint Academic Data Science Endeavour), aims to develop computers for research into AI, machine learning, and molecular dynamics, a method of simulating the movements of microscopic particles.
JADE 2 is headed by Professor Wes Armour, a member of the Oxford Department of Engineering Science and the Oxford e-Research Centre. It is the successor to JADE, a high performance computing project started in 2016 with the purpose of furthering scientific research through the use of supercomputers.
Statistical Modeling, Causal Inference, and Social Science blog, Andrew Gelman
from
In biological sciences, it might be reasonable to expect real effects to replicate, but carrying out the measurement required to study this replication is difficult for technical reasons.
In social sciences, it might be straightforward to replicate the data collection, but effects of interest could vary so much by context that replication could be difficult.
When New York University closed its NYU Shanghai campus in response to the COVID-19 epidemic in China, little did it realize how much students would appreciate the efforts the university went through to keep their learning on track. The spring 2020 semester kicked off with school officials determined to use digital tools to deliver learning online as an alternative. More than a thousand undergraduate and graduate students and faculty have signed on to participate in virtual lectures, discussions and more physical activities from locations around the world.
For Malinda Smith, political science professor at University of Alberta, it’s critical that universities do work to responsibly collect faculty diversity data. However, she still sees data gap as a crucial obstacle.
Prof. Smith strongly believes that universities need to use an intersectional lens when talking about diversity and inclusion.
“When we say the women are improving, what we’re not saying is that is not true for racialized minority women, not true for Indigenous women,” said Dr. Smith, who is also a past president at Academic Womens’ Association (AWA) and began conducting research alongside Nancy Bray, communication officer at AWA, on diversity in leadership at a group of Canadian research institutes.
arXiv, Computer Science > Social and Information Networks; Valentin Danchev, Mason A. Porter
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An emerging area of research is the study of large-scale migration interactions as a network of nodes that represent places (e.g., countries, cities, and rural areas) and edges that encode migration interactions that connect those places. In this chapter, we review interdisciplinary applications of social and spatial network approaches for the analysis of migration networks. We focus in particular on global migration networks. We describe properties of global migration networks and outline network diagnostics and methods that are relevant to the study of such networks. We then present key findings and propose areas of future research to overcome current challenges. Research on migration networks is multidisciplinary; it connects migration studies to diverse research areas that include sociology, geography, regional science, network science, applied mathematics, computer science, and other areas. Consequently, a major objective of the present chapter is to highlight and foster interdisciplinary conversations.
The Chronicle of Higher Education, Bennett Leckrone
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Academics channeled their inner screenwriter this past weekend after the news broke that Sandra Oh would be starring as a department chair at a major university in a coming series on Netflix.
It wasn’t immediately clear what, if any, university would be depicted in The Chair, which will feature Oh, the star of Killing Eve, as chair of an English department. Deadline described the series — written by the actress Amanda Peet with Annie Julia Wyman, who earned a Ph.D. at Harvard — as a “dramedy.”
Academe quickly took notice, with some wondering why it had taken Hollywood so long to “mine that rich field for comedy.”
Johnny Ryan has spent the last year and a half trying to convince European regulators that the business model that props up the biggest tech companies in the world — behavioral advertising — is illegal. Now, he is gearing up for a new fight. This time, he wants regulators to crack down on how tech giants use data inside their own virtual walls.
The charismatic Irishman is the chief policy officer for the web browser company Brave. Back in 2018, he filed a complaint with Ireland’s Data Protection Commissioner accusing Google and the Interactive Advertising Bureau in Europe of violating European data protection laws through the wanton broadcasting of sensitive personal information in online ad exchanges. Flexing his media savvy, Ryan drummed up tons of press about it, and strategically coordinated with other data rights groups throughout Europe to file similar complaints. It caused a stir.
Scientific Reports; Chantel S. Prat, Tara M. Madhyastha, Malayka J. Mottarella & Chu-Hsuan Kuo
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This experiment employed an individual differences approach to test the hypothesis that learning modern programming languages resembles second “natural” language learning in adulthood. Behavioral and neural (resting-state EEG) indices of language aptitude were used along with numeracy and fluid cognitive measures (e.g., fluid reasoning, working memory, inhibitory control) as predictors. Rate of learning, programming accuracy, and post-test declarative knowledge were used as outcome measures in 36 individuals who participated in ten 45-minute Python training sessions. The resulting models explained 50–72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. Across outcome variables, fluid reasoning and working-memory capacity explained 34% of the variance, followed by language aptitude (17%), resting-state EEG power in beta and low-gamma bands (10%), and numeracy (2%). These results provide a novel framework for understanding programming aptitude, suggesting that the importance of numeracy may be overestimated in modern programming education environments. [full text]
Carnegie Mellon University, Heinz College, Media Relations
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Recurrent, unplanned readmissions to the hospital—which happen when patients return shortly after discharge and are readmitted for the same or a related condition—are a challenge worldwide. Many researchers have examined how to predict them and how to understand the factors that contribute to them. A new study looked at how the risk of readmission progressed over multiple visits to emergency departments (EDs) in Israel by patients with chronic diseases. The study explored a way to identify distinct groups of patients who are more likely to be readmitted so medical professionals can intervene to prevent or reduce the possibility of future readmissions.
2U, an online program management provider, believed it was the strongest partner to enable the digital transformation of universities by allowing them to offer a variety of courses to a new student profile. Harvard Business School professors Karim Lakhani and Marco Iansiti discuss the case, “2U: Higher Education Rewired,” and connections to concepts in their book, “Competing in the Age of AI.” [audio, 31:20, transcript]
The Canadian Space Agency (CSA) has a long-standing tradition of innovation and technological development in space. Who can forget the Shuttle Remote Manipulator System (SRMS), more familiarly known as the “Canadarm“, which was essential to the Space Shuttle program? How about its successor, the Canadarm2, which is a crucial part of the International Space Station and even helped assemble it?
Looking to the future, the CSA intends to play a similar role in humanity’s return to the Moon – which includes the creation of the Lunar Gateway and Project Artemis. To this end, the CSA recently awarded a series of contracts with private businesses and one university to foster the development of technologies that would assist with national and international efforts to explore the Moon.
For a while now, Google has been working on making mobile-first indexing the default behavior of its search engine. With mobile-first indexing, Google Search primarily uses a page’s mobile content for creating its search index and ranking. Google announced this initiative in 2016 and as it announced today, by September 2020, it’ll become the default behavior for all sites.
After a few small tests, the company started going all-in last year, and by December, it used mobile-first indexing for more than half of the web pages it showed in its search results. Today, that number is 70% already.
Juan Reynoso is about to step into largely uncharted territory. When he graduates this spring, he’ll be only the second person to have completed a new joint Master in Public Health (MPH)/Master in Urban Planning (MUP) degree program. Launched in 2016 by Harvard T.H. Chan School of Public Health and Harvard Graduate School of Design (GSD), the program allows students to pursue a transdisciplinary education in urban planning and public health and sharpen their understanding of key areas including policy, sustainability, and social determinants of health.
Over the course of the program, Reynoso has bounced between studios at GSD, where he’s wrestled with urban planning challenges, and classrooms at Harvard Chan School, where he’s learned about population health and has grown especially interested in how environmental exposures, such as air pollution or tainted drinking water, affect health.
There are two approaches that higher education can take in terms of data science. First is to create data scientists. This includes preparing students from undergraduate to Ph.D.
The second is to develop data science skills for students’ current disciplines or for a future career path that is not directly related to data science. For example, a person who is working in the finance sector will want data science skills to stay competitive.
Therefore, we must offer opportunities for both career paths: creating data scientists and preparing professionals with data science skills. At MTSU, we are tackling the first educational objective — creating the data scientist — with a new bachelor’s degree in Data Science. Applications for this program are currently being accepted for the upcoming fall semester. We are also focusing efforts to create a data science track for a Computational Science Ph.D., which will provide students a path to become a data scientist.
For the last decade, Mark Muro has sought to unravel the mystery of America’s tech hubs. Why aren’t they sharing the wealth?
In places like Silicon Valley, Seattle and Austin, the world’s most valuable companies have hired hundreds of thousands of well-paid office workers since 2010. But even though that has fueled side effects of rapid job growth like skyrocketing housing costs, soul-crushing commutes and an increasingly visible tech backlash, employers haven’t stopped hiring in the same cities.
“Nobody feels like they’re winning” in the tech economy, said Muro, a senior fellow and policy director of the Brookings Institution’s Metropolitan Policy Program. “Not even the winners.”
The next generation of research and innovation leaders will be supported through a major £179 million investment.
Business Secretary Alok Sharma and Education Secretary Gavin Williamson announced on Friday that 41 universities will host Doctoral Training Partnerships (DTPs) funded by the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).
Four pilot projects will also explore ways to widen career paths into doctoral training, including attracting more people currently working in business.
The DTP investment was announced alongside the first nine Stephen Hawking Fellows, who will continue Professor Stephen Hawking’s legacy by furthering our understanding of the universe and communicating the wonders of science to the public, and funding to improve and boost uptake of science subjects at school.
Large-scale social experiments are now ubiquitous, and conducted without public scrutiny. Has this new era of experimentation remembered the lessons of the old?
HIMSS (MobiHealthNews’s parent company) posted its own definition that it hopes will provide useful clarity to the industry, along with a white paper that presents HIMSS’ Digital Health Framework. Here’s the definition HIMSS came up with:
Digital health connects and empowers people and populations to manage health and wellness, augmented by accessible and supportive provider teams working within flexible, integrated, interoperable, and digitally-enabled care environments that strategically leverage digital tools, technologies and services to transform care delivery.
The hottest feature of 5G isn’t discussed very much. When people talk about 5G they tend to discuss the gigabit speeds or the lower latencies. But it’s network slicing, the ability to partition off segments of the 5G network with specific latency, bandwidth, and quality-of-service guarantees, that could change the underlying economics of cellular service. Network slicing could lead to new companies that provide connectivity and help offset the capital costs associated with deploying 5G networks.
How? Instead of selling data on a per-gigabyte basis, these companies could sell wireless connectivity with specific parameters.
Forget robot teachers, adaptive intelligent tutors and smart essay marking software — these are not the future of artificial intelligence in education but merely a step along the way.
The real power that AI brings to education is connecting our learning intelligently to make us smarter in the way we understand ourselves, the world and how we teach and learn.
For the first time we will be able to extend, develop and measure the complexity of human intelligence — an intellect that is more sophisticated than any AI. This will revolutionise the way we think about human intelligence.
A majority of the world’s women are still not connected to the internet, largely because they can’t afford it or have no access to the technology they need or the skills to use it. Men remain 21% more likely to be online than women, rising to 52% in the world’s least developed countries. This gap reinforces existing inequalities and prevents millions from using the web to learn, earn, and make their voice heard.
Second, for many who are online, the web is simply not safe enough. New research by the Web Foundation and the World Association of Girl Guides and Girl Scouts found over half of young women surveyed have experienced violence online — including being sexually harassed, sent threatening messages, or having their private images shared without consent. Eighty-four percent think the problem is getting worse.
Animals rely on group behavior to survive, whether it’s fish swimming together to avoid predators or humans sharing knowledge with each other. But despite the importance of such social interactions, scientists do not have a good understanding of the biological processes that guide collective behavior.
In a new study published in iScience, researchers at Harvard University and the Max Planck Institute of Animal Behavior developed a new way to study how genes influence collective behavior. Using zebrafish as a model, they set out to establish the connection between genetic mutations and behavior.
“We are interested in answering a fundamental biological question: why do animals live in groups?” said Mark Fishman, Harvard professor of stem cell and regenerative biology. “To search for genes that affect collective behavior, we focused on genetic mutations that are associated with psychiatric diseases that have a social behavior component, including autism and schizophrenia.”
Developers can use the startup’s ArtEngine platform to bring real-world materials to their game worlds, adapting the visual patterns to their 3D worlds more quickly than existing toolsets while eliminating seams and irregularities. ArtEngine uses AI to identify visual flaws in replications and saves developers from having to endlessly tweak environments.
Greenland and Antarctica have lost 6.4 trillion tons of ice in the past three decades; unabated, this rate of melting could cause flooding that affects hundreds of millions of people by the end of the century, NASA said in a statement.
Satellite observations showed that the regions are losing ice six times faster than they were in the 1990s, according to a new study.
If the current melting trend continues, the regions will be on track to match the “worst-case” scenario of the Intergovernmental Panel on Climate Change (IPCC) of an extra 6.7 inches of sea level rise by 2100.
Diseases often pile on, coinfecting people, animals and other organisms that are already fighting an infection. In one of the first studies of its kind, bioscientists from Rice University and the University of Michigan have shown that interactions between pathogens in individual hosts can predict the severity of multipathogen epidemics.
Six Daphnia dentifera zooplankton, as seen under a microscope.
In lab experiments, scientists explored how the timing of bacterial and fungal infections in individual zooplankton impacted the severity of bacterial and fungal epidemics in zooplankton populations. The study, published this week in the Proceedings of the Royal Society B, showed that the order of infections in individual hosts can change the course of an epidemic.
“It’s well known that the way parasites and pathogens interact within hosts can alter disease transmission, but the question has been, ‘What information do you need to gather about those interactions to be able to predict the severity of an epidemic?’” said corresponding author Patrick Clay, a University of Michigan postdoctoral associate who conducted the research during his Ph.D. studies at Rice.
Main takeaway: We see a consensus among the experts that the outbreak will continue to escalate in the US in coming weeks, and that only 13% of all COVID-19 infections have been confirmed as cases so far. Experts expect hospitalizations for COVID-19 to peak in May.
According to an ongoing investigation at The Atlantic, the US has tested only about 14,000 people for COVID-19 so far (a stat CDC data seems to confirm). 14,000 out of 330 million people. Olga Khazan writes about the four main reasons why the US is so behind in testing for the virus.
“Weather patterns that cause extreme events such as heatwaves and cold spells in the mid-latitudes (most of North America, Europe, large parts of Asia) are often due to abnormal patterns in the jet streams: unusual configurations of high and low-pressure systems,” said Pedram Hassanzadeh, assistant professor of mechanical engineering and planetary sciences at Rice and co-author of the study. “So given this, and the recent advances in AI-based pattern recognition techniques, we thought to see if we can go back to the idea of analog forecasting, but leveraging AI.”
To create their model, the team revised their approach to the problem; the AI method they had initially been using was convolutional neural networks (CNNs). However, their approach soon changed to one of pattern-recognition, when the team caught wind of a new form of deep learning called capsule neural networks. Unlike CNNs, capsule neural networks don’t have “pooling layers,” which reduce the dimensions of the feature maps and therefore reduce the number of parameters to learn and the amount of computation performed in the network. CapsNets also use “capsules” that are nested sets of neural layers that allow them to identify relative spatial relationships, which is critical in predicting extreme weather occurrences.
Nature, Palgrave Communications; José Balsa-Barreiro, Aymeric Vié, Alfredo J. Morales & Manuel Cebrián
from
In the age of hyperconnectivity, we are undergoing an explosive increase in the interdependence of the political, commercial, financial, and social spheres. The recent rise of deglobalization movements across the world highlights the local negative externalities of poorly designed networked structures at the global scale: high social complexity derived from immigration shocks, elevated risk of contagion in financial downturns, as well as increasing inequality and social polarization. While global interdependencies on networks enable opportunities for cultural and economic growth, they also establish channels for unresolved conflicts and design errors to propagate across social systems. We analyze failure propagation on networks as a function of density and centralization of inter-dependencies. We show that the risk of failure in both overly distributed and centralized systems behave similarly when the number of connections exceeds a system-dependent threshold number. The scale of interdependencies matters and must be considered for the design of policies targeted at increasing or decreasing the connectivity of social systems.
Hi Reddit, I’m Tom Smith, MD for the UK’s Data Science Campus as part of the Office for National Statistics. I have 20 years’ experience using data and analysis to improve public services and am a life-long data addict.
I have a PhD in computational neuroscience and robotics, an MSc in knowledge-based systems and an MA in theoretical physics.
I’m currently Chair of the Advisory Board to the United Nations Global Platform for big data & official statistics, Member of Council for the UK Royal Statistical Society, and previously chair of the Environment Agency Data Advisory Group, vice-chair of the Royal Statistical Society Official Statistics section, and a member of the Open Data User Group ministerial advisory group to Cabinet Office.
A newly-created ‘COVID-19 Task Force’, which includes representation from the Chan Zuckerberg Initiative (CZI), Chan Zuckerberg Biohub, UCSF, and Stanford University, today announced that they aim to quadruple UCSF’s COVID-19 testing and diagnostics capacities by funding the acquisition of two state-of-the-art clinical diagnostic machines. Once approved by the FDA for COVID-19 testing and diagnostics, these machines will allow UCSF to significantly increase its ability to test and diagnose new Bay Area COVID-19 cases. Per public health protocols, testing is being limited to symptomatic patients with tests ordered by doctors and health care professionals.
“As the coronavirus epidemic continues to grow, our ability to rapidly test and diagnose cases is critical,” said Chan Zuckerberg Biohub co-President, Joe DeRisi. “Procuring these new diagnostic machines will have a significant impact on our ability to respond to the outbreak in a more streamlined way.”
The Task Force was also able to help bridge some of the Bay Area’s testing shortages by connecting groups at UCSF and Stanford, so that UCSF test requests can now be handled at Stanford when UCSF’s internal capacity is exceeded and city laboratories are backlogged.
Association of Public Data Users (APDU), Brendan Buff
from
The Census Bureau’s solution to protecting privacy is a new DAS based on a methodology referred to as Differential Privacy (DP). In brief, it functions by leveraging the same database reconstruction techniques that were used to diagnose the problem in the previous system: the 2020 DAS synthesizes a complete set of person- and household-level data records based on an extensive set of tabulations to which statistical noise has been added. Viewed as a continuum between total noise and total disclosure, the core of this method involves a determination regarding the amount of privacy loss or e, that can be accepted without compromising data privacy while ensuring the utility of the data. The key then becomes “where to set the dial”—set e too low and privacy is ensured at the cost of utility, but set e too high and utility is ensured but privacy in compromised. In addition to the overall level of e, its allocation over the content and detail of the census tabulations for 2020 is important. For example, specific block-level tabulations needed for redistricting may require a substantial allocation of the privacy-loss budget to achieve acceptable accuracy for this key use, but the cost is that accuracy of other important data (including for blocks, such as persons per household) will likely be compromised. Finding ways to resolve these difficult tradeoffs represents a serious challenge for the Census Bureau and users of its data.
In the early days of Canada’s COVID-19 outbreak, Elisa Baniassad was able to trace how new cases were spreading and plan her outings accordingly.
“When I plotted how the virus was being transmitted, I saw that it was from close contact. People weren’t getting it out on the street, they were getting it at home from their family members,” said the computer science instructor at the University of British Columbia.
Baniassad is one of a handful of people making use of the reams of data being collected and published daily around the world to help governments and citizens plan and be informed of the latest situation.
A technology company that previously sold software that detects weapons has announced it is deploying “artificially intelligent thermal cameras” that will be able to detect fevers in people, and in turn send an alert that they may be infected with COVID-19.
“Our Fever Detection COVID19 Screening System is now a part of our platform along with our gun detection system which connects directly to your current security camera system to deliver fast, accurate threat detection,” Austin, Texas-based Athena’s website says.
While new surveillance technologies could have some use during a pandemic, experts are warning the emergency must not be used as an excuse to infringe on our freedom and basic civil liberties.
We have teams at YouTube, as well as partner companies, that help us support and protect the YouTube community—from people who respond to user and creator questions, to reviewers who evaluate videos for possible policy violations. These teams and companies are staffed by thousands of people dedicated to helping users and creators. As the coronavirus response evolves, we are taking the steps needed to prioritize the well-being of our employees, our extended workforce, and the communities where they live, including reducing in-office staffing in certain sites.
Our Community Guidelines enforcement today is based on a combination of people and technology: Machine learning helps detect potentially harmful content and then sends it to human reviewers for assessment. As a result of the new measures we’re taking, we will temporarily start relying more on technology to help with some of the work normally done by reviewers. This means automated systems will start removing some content without human review, so we can continue to act quickly to remove violative content and protect our ecosystem, while we have workplace protections in place.
Bloomberg Technology, Gwen Ackerman and Yaacov Benmeleh
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An Israeli technology company, which has gained notoriety for the spyware it sells, has developed a new product it says has the ability to track the spread of the coronavirus.
NSO Group Ltd.’s product analyzes huge volumes of data to map people’s movements to identify who they’ve come in contact with, which can then be used to stop the spread of infection, according to a person familiar with the matter.
Google is limiting how its trove of location data is used in the fight against the novel coronavirus as the company balances government demands with user privacy concerns.
The largest U.S. internet company has been talking with other tech companies and governments about how to respond to the pandemic. Google has detailed information on the movement of billions of people who use its digital Maps and Android devices, and this has been identified as a useful asset.
Georgia Institute of Technology, College of Computing
from
Most of our social interactions, most of our information needs, and most of our daily tasks and decision making is happening online.
With high-stakes decisions being made via the web, the ways in which malicious users engage with us online can have a profoundly negative impact on our lives and on society as a whole.
Is the business world really evolving or is it still stuck in the past? Women enjoy more professional opportunities than ever before, but a recent survey finds the corporate landscape still has a long way to go before men and women employees are treated equally. A survey of 2,000 employed women finds that the average woman gets “mansplained” (talked down to, spoken to like a child by a male co-worker) while on the job six times each week.
Emerson Boggs, 25, a Ph.D. student and virologist at the University of Pittsburgh, signed up on Jan. 23 to moderate what was then a small Reddit community with about 1,000 members dedicated to a relatively obscure topic: a new coronavirus that had been discovered in Wuhan, China.
Less than two months later, the Reddit message board /r/coronavirus has grown to more than 1.2 million members — almost a million of whom signed up in the last two weeks. Boggs is now one of a team of 60 volunteer content moderators, including researchers of infectious diseases, virologists, computer scientists, doctors and nurses, spending hours policing the more than 50,000 daily comments posted by the community for misinformation, trolls and off-topic political discussions.
As the United States races to ramp up testing for the pandemic coronavirus using technology based on the tried-and-true polymerase chain reaction (PCR), alternative approaches are beginning to roll out that could make it easier and quicker for people to learn whether they have been infected. Some methods modify the standard PCR test, which amplifies tiny bits of genetic material to enable detection, while others sequence the virus directly or use the genome editor CRISPR.
Faster and cheaper tests are coming, says Evan Jones, CEO of OpGen, a rapid diagnostics company in Gaithersburg, Maryland. However, he adds, developing new kinds of tests is “going to take time.” Some of the new tests are coming online now, but others will likely take months to validate and ready for widespread distribution.
Roni Rosenfeld makes predictions for a living. Typically, he uses artificial intelligence to forecast the spread of the seasonal flu. But with the coronavirus outbreak claiming lives all over the world, he’s switched to predicting the spread of Covid-19.
It was the Centers for Disease Control and Prevention (CDC) that asked Rosenfeld to take on this task. As a professor of computer science at Carnegie Mellon University, he leads the machine learning department and the Delphi research group, which aims “to make epidemiological forecasting as universally accepted and useful as weather forecasting is today.” The group has repeatedly won the CDC’s annual “Predict the Flu” challenge, where research teams compete to see whose methods generate the most accurate forecasts.
Initially, Rosenfeld balked when the CDC asked him to predict Covid-19’s spread. He didn’t think his AI methods were up to the challenge. Yet he’s taking his best stab at it now — and you can help, even if you know nothing about AI.
It is too early to confidently predict the course of the economic downturn facing us due to the coronavirus. But a recession is inevitable. The global manufacturing industry was already shaky in 2019. Now we are deliberately shutting down the world’s major economies for at least several months. Factories are closing, shops, gyms, bars, schools, colleges, and restaurants shuttering. Early indicators suggest job losses in the United States could top 1 million per month between now and June. That would be a sharper downturn than in 2008-2009. For sectors like the airline industry, the impact will be far worse. In the oil industry, the prospect of market contraction has unleashed a ruthless price war among OPEC, Russia, and shale producers. This will stress the heavily indebted energy sector. If price wars spread, we could face a ruinous cycle of debt-deflation that will jeopardize the world’s huge pile of corporate debt, which is twice as large as it was in 2008. International trade will sharply contract.
In the division of labor among different branches of economic policy, addressing the coronavirus recession is a classic task for targeted fiscal policy: tax cuts and government spending. What we need now is less stimulus than a comprehensive national safety net to prevent bankruptcies and long-term financial damage.
Russian media have deployed a “significant disinformation campaign” against the West to worsen the impact of the coronavirus, generate panic and sow distrust, according to a European Union document seen by Reuters.
A cross-disciplinary team led by James O’Neill at the University of Liverpool recently presented a method to use machine learning to predict ticks’ presence from a pet’s health records.
In order to build the method, O’Neill and his coauthors took advantage of the Small Animal Veterinary Surveillance Network, an initiative that has accumulated over 3 million records from veterinary visits in the UK.
We want our top students to shine, but in the hastily constructed online education world, our bigger concern is helping the average-and-below students.
… With the International Olympic Committee announcing Sunday it is giving itself a month to explore its options, the key question becomes when could Tokyo host the Games? If they are postponed, could it be later this year? Or 2021? Or possibly 2022?
According to public health experts, the answer might be further out than Tokyo and IOC organizers would like. Projecting the spread of COVID-19 and how well it is contained might be the most challenging factor and one that could put the IOC in a similar predicament in the future.
The Annual AI 2000 Most Influential Scholar List (“AI 2000”) named the world’s 2000 top-cited research scholars from the fields of artificial intelligence (AI) over the next ten years (2020–2029). Data provided by Tsinghua Aminer academic data system, which tracks and analyzes research results for 250,669 scholars worldwide over the past ten years (2009-2019), covering 140,377 papers, including 43 top conferences and journals.
Grades have been on the rise across the country at least since 1960, when the average GPA in the United States was a 2.4. The first major uptick began at the onset of the Vietnam War and is largely ascribed to faculty efforts to keep male students eligible for student draft deferments. Throughout the 1990s, grades rose again with the emergence of the “student as consumer” model of higher education that demands a transcript that can justify a $250,000 tuition bill. Today, the mean GPA is around a 3.15, and it is even higher at private colleges and universities.
Harris’ 2013 announcement offered a rare glimpse into the grading machinery at Harvard, as the College does not publicly release data on grades. Yet according to The Harvard Crimson’s annual survey of graduating seniors, the class of 2017’s average GPA was 3.65, half a grade higher than the nationwide average and among the highest in the Ivy League. With a 2019 acceptance rate of 4.5 percent, Harvard carefully selects from a pool of the brightest and most accomplished high school students. Are high GPAs to be expected at a school filled with the world’s top performers, or does Harvard just grade easier?
This is not an easy question to answer. Harvard’s average GPA has been rising since grades were first recorded, but some attribute this climb to factors other than grade inflation.
Riyadh has kept mum on its motivations, but if the suspicions of many in the oil market prove true, this oil war will be a Darwinian survival of the fittest. As the world steps up the fight against climate change, the demand for oil will peak in a few decades. Saudi Arabia and Russia will likely emerge bruised but standing. Many others, including U.S. shale producers, will be in dire straits.
In the kingdom, the current thinking is to let free markets work. If officials are worried about low oil prices, they aren’t showing it. Saudi Arabia is hunkering down for one to two years of cheap oil, adjusting government spending and drafting measures to protect the vulnerable among its citizenry.
Cities throughout the US have emptied out amid the coronavirus outbreak. Millions of people are working from home, children are attending school remotely, and no one’s heading to ballparks, nightclubs or movie theaters. They’ve all turned to their home broadband connections to stay connected.
With California mandating “shelter in place” across the entire state, New York City on total lockdown and other states and cities to follow suit, home broadband networks across the nation will be under tremendous pressure as we enter a second week of school and office closures across the country.
So far networks in the US and across the world have been holding up even as usage spikes. But will it continue?
The Publications Division of the American Chemical Society (ACS) and the Massachusetts Institute of Technology (MIT) Libraries today announced a new and innovative agreement, which will advance key elements of open access.
Through this agreement, all ACS journal articles with MIT-affiliated corresponding authors will be made open access. The associated accepted manuscripts will be automatically deposited into MIT’s open access repository, as called for under MIT’s Framework for Publisher Contracts, and in a manner consistent with ACS publishing policies. In addition, a number of the final published papers (the version of record) will also be made open on the ACS publishing platform at no additional cost to individual authors.
Pro Publica; Annie Waldman, Al Shaw, Ash Ngu, and Sean Campbell,
from
Though the U.S. health care system is projected to be overwhelmed by an influx of patients infected with the novel coronavirus, the pressure on hospitals will vary dramatically across the country. That’s according to new data released by the Harvard Global Health Institute, which for the first time gives a sense of which regions will be particularly stressed and should be preparing most aggressively right now. The maps we’ve created based on the data shows why public health officials are so intent on “flattening the curve,” or slowing the spread of infections over a longer period of time, like 18 months instead of six.
Public Integrity; Zachary Fryer-Biggs, Joe Wertz, Liz Essley Whyte
from
Only 16,600 ventilators.
That’s the total number of breathing machines that sit in the Strategic National Stockpile, the government reserve meant to fortify overwhelmed hospitals in a crisis. It’s a small supplement to the U.S. medical system’s estimated 160,000 or so ventilators — many already in use — and not nearly enough to help patients survive a severe outbreak of coronavirus infections, health experts say.
… Postponing the Olympics a year is a far more difficult task than pausing the NBA season or rescheduling the 2020 European soccer championships. It’s figuring out equitable solutions for 11,000 athletes from 206 different countries. It’s reorganizing 200,000 volunteers. It’s assuring the safety, enjoyment and entertainment of 4.5 million ticket holders watching 46 different sports in 42 different venues.
Few would argue Tuesday’s decision was the wrong one. And sure, there are far greater global concerns right now than the ability of Olympic athletes to compete. But in Olympic circles, as much as Tuesday’s news brought clarity for athletes wrestling with whether to train or stay home, it also brought an encyclopedia’s worth of new questions. The majority of which, at least for now, come with the same answer: TBD.
“It almost feels like a wasted year. Like it didn’t even happen,” said two-time Olympic wrestler and 2012 gold medalist Jordan Burroughs. “There is just so much up in the air, shoved to the back burner.”
Target is one of the stores that has seen a spike in purchases of cleaning products, toilet paper and pantry items, but it’s also seen a drop-off in apparel and accessories sales.
CEO Brian Cornell said the retailer is pulling back on plans for store remodels, delaying openings of many small-format stores and withdrawing guidance for the first quarter and the fiscal year.
Stores are adopting new policies to minimize risk, such as temporarily banning all returns and exchanges, wiping down checkout lanes after each transaction and asking employees not to handle customers’ reusable bags.
Yale psychology professor Laurie Santos’s course “Psychology and the Good Life” is the most popular class in the history of the university. Now it’s available for anyone to take for free remotely through Coursera. The public online version of the class is called the “Science of Well-Being.”
The coronavirus crisis isn’t hitting every American equally—both in terms of factors like who is able and allowed work from home and in terms of urban design, like whether someone under lockdown can easily reach a grocery store or whether the nearest hospital is well-prepared for a surge in patients. As governments and nonprofits figure out where to send help, Urban Footprint, an urban planning tool, is beginning to map out the neighborhoods that are most vulnerable.
We collected ~1.5 million behavioral responses in a triplet odd-one-out task for 1,854 natural objects and developed a computational that identified 49 interpretable dimensions. [thread]
A sneaker designed for runners who want to move slowly, rather than sprint. An app that helps caregivers keep track of their schedules and communicate easily with their older clients. A company that helps retirees who want to reenter the labor force — and encourages employers to give them a chance.
These are just a few of the existing products and services that MBA students analyzed in a new Stanford Graduate School of Business course, “Longevity: Business Implications and Opportunities.” The course — likely the first given on the subject of the longevity economy at a business school — explored why business executives and entrepreneurs should focus on the 50+ demographic.
“Whether you want to launch a start-up or work for a large established company, the longevity market is a huge and still mostly overlooked opportunity,” said Robert Chess, a business school lecturer and serial entrepreneur who co-taught the course this winter with Laura Carstensen, director of the Stanford Longevity Center.
Another nice graph, this one from yours truly. Well, not really, it’s all from the CDC, I just made a version that’s easier to look at, because I think it’s an interesting way to reflect on the devastation of the 1918 flu amid an otherwise rapid decline of death from infectious disease. (Y-axis is deaths per 100,000 Americans.)
As the covid-19 pandemic rages on, governments around the world are turning to teams of scientists for guidance on how to proceed. The UK government finally published the scientific advice it has received on Friday 20 March.
At first, most commentators welcomed the transparency. But closer reading of the documents made available online suggests a few causes for concern. The strongest advice from the World Health Organization (WHO) on controlling outbreaks of the coronavirus – testing – barely gets a mention, for example. And the guidance seems to lean heavily on a single model of the outbreak – which some scientists suggest contains systematic errors.
New York State is ramping up efforts to combat the growing coronavirus pandemic, including appeals to all industries for help in the form of much-needed medical equipment for healthcare workers. It’s also specifically asking for help from the tech community, through an open call for contributions from individuals and organizations to help form its “COVID-19 Technology Swat Team.”
Brain-computer interfaces may soon have the power to decode people’s thoughts and interfere with their mental activity. Even now the interfaces, or BCIs, which link brains directly to digital networks, are helping brain-impaired patients and amputees perform simple motor tasks such as moving a cursor, controlling a motorized wheelchair, or directing a robotic arm. And noninvasive BCI’s that can understand words we want to type and place them onto screens are being developed.
But in the wrong hands, BCIs could be used to decode private thoughts, interfere with free will, and profoundly alter human nature.
To counter that possibility, Columbia University professor of biological sciences and Data Science Institute member Rafael Yuste founded the NeuroRights Initiative, which advocates for the responsible and ethical development of neurotechnology. The initiative puts forth ethical codes and human rights directives that protect people from potentially harmful neurotechnologies by ensuring the benign development of brain-computer interfaces and related neurotechnologies.
As COVID-19 continues to spread, with 209,000 confirmed cases and close to 9,000 deaths globally, technology giants are stepping up to accelerate research and potential treatments.
Among them, Amazon and Microsoft are rolling out separate initiatives to support COVID-19 diagnostics and research.
On Sunday, the White House Office of Science and Technology Policy also announced the development of the COVID-19 High Performance Computing Consortium in partnership with IBM and the Energy Department national laboratories. The initiative will enable researchers to have access to supercomputers to help speed the discovery of vaccines and drugs. Alphabet’s Google Cloud, Amazon Web Services (AWS), Microsoft, and many universities also are participating.
As part of its separate initiative, AWS announced Friday it is setting aside an initial $20 million toward the development of diagnostics, including a more accurate, faster coronavirus test.
In response to calls for flexibility and broadening access to telemedicine services during the COVID-19 public health emergency, certain federal privacy regulations have been relaxed and payment policies expanded as a result of actions taken by the Health and Human Services (HHS) Office for Civil Rights (OCR) and the Centers for Medicare & Medicaid Services (CMS).
The AMA quick guide to telemedicine in practice has been developed to help physicians swiftly ramp up their telemedicine capabilities. In addition to informing physicians on the recent actions taken by the OCR and CMS, the guide gives instruction on getting started; policy, coding and payment; practice implementation; and links to other helpful resources.
A University of California, Berkeley robotics lab is developing AI systems for polyculture gardening as part of AlphaGarden, an AUTOLAB project that wants to find out if humans can train robotic control systems to fully automate a polyculture garden of edible plants and invasive species. The AUTOLAB robotics laboratory is perhaps best known for creating the DexNet system for robotic grasping.
Zoom offers reliability, ease of use, and at least one very important security assurance: As long as you make sure everyone in a Zoom meeting connects using “computer audio” instead of calling in on a phone, the meeting is secured with end-to-end encryption, at least according to Zoom’s website, its security white paper, and the user interface within the app. But despite this misleading marketing, the service actually does not support end-to-end encryption for video and audio content, at least as the term is commonly understood. Instead it offers what is usually called transport encryption, explained further below.
By the early 2020s, emotional artificial intelligence (emotional AI) will become increasingly present in everyday objects and practices such as assistants, cars, games, mobile phones, wearables, toys, marketing, insurance, policing, education and border controls. There is also keen interest in using these technologies to regulate and optimize the emotional experiences of spaces, such as workplaces, hospitals, prisons, classrooms, travel infrastructures, restaurants, retail and chain stores. Developers frequently claim that their applications do not identify people. Taking the claim at face value, this paper asks, what are the privacy implications of emotional AI practices that do not identify individuals? To investigate privacy perspectives on soft non-identifying emotional AI, the paper draws upon the following: over 100 interviews with the emotion detection industry, legal community, policy-makers, regulators and NGOs interested in privacy; a workshop with stakeholders to design ethical codes for using data about emotions; a UK survey of 2068 citizens on feelings about emotion capture technologies. It finds a weak consensus among social stakeholders on the need for privacy, this driven by different interests and motivations. Given this weak consensus, it concludes that there exists a limited window of opportunity to societally agree principles of practice regarding privacy and the use of data about emotions.
San Jose Mercury News, Bay Area News Group, Lisa M. Krieger
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With a diverse and well-traveled population, Santa Clara County is especially vulnerable to contagion.
Yet the arrival of a new virus early this year went completely undetected, giving it time to widely seed our region before we even knew it was here, the county’s top public health official says. By early March, that virus was so widespread that three TSA agents at San Jose International Airport contracted it not from each other but from entirely separate sources.
In an exclusive interview, county health officer Dr. Sara Cody revealed the depth of the coronavirus containment challenge facing the county, Northern California’s hardest-hit location — and why infections exploded so quickly, demanding an aggressive “shelter-in-place” order.
University of Washington, Institute for Health Metrics and Evaluation, Christopher Murray
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The model was most recently updated at 6 a.m. Pacific, March 31, 2020. To view the changes, please visit our estimation updates page. Find more details about curve fitting for this project here.
As the coronavirus outbreak continues to worsen around the world, it’s taking a devastating toll on lives and communities. To help address some of these challenges, today we’re announcing a new $800+ million commitment to support small- and medium-sized businesses (SMBs), health organizations and governments, and health workers on the frontline of this global pandemic.
Dr. Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, revealed on Tuesday that the White House coronavirus task force is seriously considering guidance that Americans wear masks to help thwart the rapid spread of COVID-19.
But the country’s top infectious disease expert also acknowledged that such a directive has been complicated by the nationwide dearth of personal protective equipment.
At the sprawling Kraft Heinz Co. plant in Montreal, the Kraft Dinner production lines are running every minute, every day, pumping out box after box of what has become one of the biggest panic buys of the COVID-19 crisis.
Sales of the Canadian pantry staple last week spiked 35 per cent compared to the previous four weeks, and grocers have struggled to keep it on shelves.
“Kraft Dinner is such a critical line,” said Danielle Nguyen, the plant manager. So critical that Kraft Heinz has a series of backup plans to keep pumping out KD should employees fall ill or need to isolate.
Say ‘collaborative writing’ and most researchers probably think of Google Docs, the ubiquitous word processor that allows multiple authors to co-edit a document online in real time. But Google Docs lacks features that some scientists require, such as reference management, support for code and data and the ability to directly submit articles to journals and preprint servers.
Manubot is one of a small but growing number of tools specifically designed for collaborative writing; others include Overleaf, Authorea, Fidus Writer and Manuscripts.io. These tools not only close some of the key feature gaps, but also provide a glimpse of where scientific communication might move next.
The coronavirus has turned our lives upside down and, although we hope to return to some version of normality in the coming months, it is probable that nothing will quite be the same again. Many have lost their livelihoods and businesses, and there is no diminishing the difficulties – emotional and financial – this has brought in its wake.
But amid the darkness, there are also opportunities.
Opportunities to reimagine the world and one’s place within it. Reversal techniques are typically used by people working in the creative industries to come up with new products or innovations. I wonder if we can all use it to seek out a silver lining or two amid the grey clouds.
In an effort to understand how many people have been infected with the new coronavirus, the World Health Organization (WHO) is planning a coordinated study to test blood samples for the presence of antibodies to the virus. Called Solidarity II, the program, which will involve more than half a dozen countries around the globe, will launch in the coming days, says Maria Van Kerkhove, who is helping coordinate WHO’s COVID-19 response.
Knowing the true number of cases—including mild ones—will help pin down the prevalence and mortality rate of COVID-19 in different age groups. It will also help policymakers decide how long shutdowns and quarantines should last. “These are answers we need, and we need the right answers to drive policy,” WHO’s executive director for health emergencies, Michael Ryan, told a press briefing.
…
The underlying technology required to implement an AI-based health/sickness forecast was first demonstrated to have the accuracy described above in the MIT Media Lab’s Affective Computing Research group in a study using 1,895 days of data collected with sensors and smartphones worn by 69 college students. The approach achieved less than 13% mean absolute error in estimating tomorrow’s health score ranging on a scale from 0=sick to 100=healthy[1].
After further studies and review, the U.S. Government’s BARDA Division of Research, Innovation and Ventures (DRIVe) funded Empatica, an MIT spin-out co-founded by J-Clinic investigator Rosalind Picard, to develop a new tool that will alert wearers about a serious respiratory infection before any symptoms appear.
President Donald Trump’s political operation is launching a multimillion-dollar legal campaign aimed at blocking Democrats from drastically changing voting rules in response to the coronavirus outbreak.
In the past several weeks, the reelection campaign and the Republican National Committee have helped to oversee maneuvering in a handful of battleground states with an eye toward stopping some Democratic efforts to alter voting laws, and to bolster Trump. The mobilization is being closely coordinated with Republicans at the state and local levels.
How many times have you heard such things as “we’re all in the same boat“, “we’ll just have to get through this, one day at a time“, and “just imagine the massive party we’re going to have once this is all over” over the last week? Our guess is a lot – so with that in mind, let’s crack on.
Over the last three weeks, we’ve analysed millions of conversations about Coronavirus for our clients and we know, only too well, about the sheer volume of COVID-19 content that’s out there.
Loneliness hurts. It is psychologically distressing and so physically unhealthy that being lonely increases the likelihood of an earlier death by 26 percent. But the feeling may serve a purpose. Psychologists theorize it hurts so much because, like hunger and thirst, loneliness acts as a biological alarm bell. The ache of it drives us to seek out social connection just as hunger pangs urge us to eat. The idea is intuitively satisfying, yet it has long proved difficult to test in humans.
On March 26, however, just as the COVID-19 pandemic gripped the world, researchers from the Massachusetts Institute of Technology posted a preliminary report on bioRxiv. It is the first study in humans to show that both loneliness and hunger share signals deep in a part of the brain that governs very basic impulses for reward and motivation. The findings point to one telling conclusion: our need to connect is apparently as fundamental as our need to eat.
Machine learning experts working at Google Health have published a new study in tandem with the University of California San Francisco’s (UCSF) computational health sciences department that describes a machine learning model the researchers built that can anticipate normal physician drug prescribing patterns, using a patient’s electronic health records (EHR) as input. That’s useful because around 2% of patients who end up hospitalized are affected by preventable mistakes in medication prescriptions, some instances of which can even lead to death.
Team from NYU Tandon School of Engineering and School of Global Public Health will share information gathered from New York City medical and transit locations with epidemiologists seeking to model the spread of the coronavirus throughout the world
Coronavirus presents an unprecedented predicament: Everyday, leaders must make momentous decisions with life or death consequences for many—but there is a dearth of data. Oded Netzer is a Columbia business professor and Data Science Institute affiliate who builds statistical and econometric models to measure consumer behavior that help business leaders make data-driven decisions. Here, he discusses how leaders from all fields can make sound decisions with scarce data to guide them.
How can leaders, regulators, and businesses make informed decisions with scant data on COVID-19?
For those of us with an expertise in data science, the COVID-19 pandemic has been a humbling experience. In the past few years, we have been promoting the notion of data-driven decisions and encouraging decision makers to use the wealth of data typically available to them to make better and more informed decisions. We have been encouraging leaders to use rich historical or comparable data to estimate a sound model and identify repeated patterns, and then apply these techniques to guide their decision making.
Indiana University is providing free, 24-hour, high-speed Wi-Fi access across the state to IU students, faculty and staff as well as the general public who may not have internet connectivity due to COVID-19-related library and business closures.
IU’s University Information Technology Services networks division has set up “lot hot spots” so users can maintain social distancing while accessing the internet from their cars.
“I am so proud of the creativity and innovation that Indiana University is showing to supply Hoosiers with free and reliable high-speed internet access as we work together to combat the spread of COVID-19,” said Suzanne Crouch, Indiana lieutenant governor. “Their efforts will allow Hoosiers — not just in Bloomington but throughout the entire state — to click, connect and download all while maintaining social distancing.”
The Daily Barometer: Oregon State University Student Newspaper, Jade Minzlaff
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Oregon State University computer science professor Heather Knight is the founder and director of the CHARISMA robotics laboratory, which aims to study how humans and robots interact through collaborative performances.
As part of their research, the CHARISMA lab participates with robots in many live performance spaces around Corvallis. One well-known example is their involvement in the quarterly “Singu-hilarity” robot stand-up comedy nights at the Majestic Theatre. Other common spaces to find robots performing include the local farmers’ market and the Graf Hall office space.
Use of voice signal analysis, an emerging noninvasive biomarker, may identify patients with congestive HF who are at highest risk for 20-month hospitalization or mortality, using voice analysis, according to research published in the Journal of the American Heart Association.
Researchers studied a cohort of 10,583 patients who were registered to a telemedicine call center in Israel and had chronic health conditions including congestive HF. Using voice processing techniques (Vocalis Health), the researchers extracted 223 acoustic features from 20 seconds of audio from each patient. The researchers then developed a vocal biomarker that was based on a training cohort of patients who did not have congestive HF (n = 8,316), and then evaluated use of the vocal biomarker in a cohort of 2,267 patients with congestive HF (mean age 77 years; 63% men) who were categorized into four biomarker quartiles.
David Silver Recognized for Breakthrough Advances in Computer Game-Playing
ACM named David Silver the recipient of the 2019 ACM Prize in Computing for breakthrough advances in computer game-playing. Silver is a Professor at University College London and a Principal Research Scientist at DeepMind, a Google-owned artificial intelligence company based in the United Kingdom. Silver is recognized as a central figure in the growing and impactful area of deep reinforcement learning.
That’s what the State’s Governor, Phil Murphy, apparently meant today, when he said at a press conference that the State needed volunteers who with “Cobalt” computer skills to help fix 40-year-old-plus unemployment insurance systems that are currently overwhelmed as a result of COVID-19-related job losses.
COBOL, for those who are unfamiliar, is a computer language that is over 60 years old, and was once the staple of software development across industry and government. By the late 1980s, however, it had become sufficiently obsolete that many universities did not even include it in their computer science curricula. In fact, while there are certainly are significant COBOL-based systems still in use today, relatively few software developers under the age of 50 have ever seen, never mind written, even one line of COBOL. It is not surprising that even New Jersey’s 62-year old governor, who was an executive at Goldman Sachs for decades, had apparently not heard its name recently enough to remember it correctly.
European Global Navigation Satellite Systems Agency
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We are listing the location-GNSS-Galileo based Applications that, in GSA’s view, may be useful in response to the diffusion of COVID-19.
The applications cover a wide range of uses, from the support to public authorities in understanding the dynamics of the outbreak to the support of citizens in their everyday life, for example by checking and possibly limiting queues at supermarket.
arXiv, Physics > Physics and Society; Gerardo Iñiguez, Federico Battiston, Márton Karsai
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Network science has become a powerful tool to describe the structure and dynamics of real-world complex physical, biological, social, and technological systems. Largely built on empirical observations to tackle heterogeneous, temporal, and adaptive patterns of interactions, its intuitive and flexible nature has contributed to the popularity of the field. With pioneering work on the evolution of random graphs, graph theory is often cited as the mathematical foundation of network science. Despite this narrative, the two research communities are still largely disconnected. In this Commentary we discuss the need for further cross-pollination between fields — bridging the gap between graphs and networks — and how network science can benefit from such influence. A more mathematical network science may clarify the role of randomness in modeling, hint at underlying laws of behavior, and predict yet unobserved complex networked phenomena in nature.
A smart toilet boasting pressure sensors, artificial intelligence and a camera has been unveiled by researchers who say it could provide a valuable way to keep tabs on our health.
The model is the latest version of an idea that has been around for several years: a system that examines our daily movements in an effort to spot the emergence of diseases. Such an approach, experts say, has an advantage over wearable devices, since individuals do not need to remember to use the system.
“We have developed a passive human health monitoring system that can be easily incorporated into a normal daily routine, requiring minimal or even no human intervention,” the team behind the new toilet report.
Traditional social science and policy research is great for understanding what happened in the past, but decision-making requires predicting what is going to happen (if we do X)? 1/n
The disruptions are going to shake up the careers of researchers at all seniority levels, says Lisa Feldman Barrett, a professor at Northeastern University. But they’ll likely have the greatest impact on early-career scientists, she notes. Problems will begin at the undergraduate level, when students begin to build their toolbox of skills at summer internships—many of which are getting canceled this year. “As a consequence of what’s happening, there will be substantially fewer experiences,” Barrett says. And when professors start to review grad school applications later, those who have little research experience will be viewed as less competitive.
Bloomberg Opinion, Arturo Casadevall and Liise-anne Pirofski
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The amount of virus, our genes, the route of infection, the variety of the virus and our immunological history combine to produce outcomes ranging from asymptomatic infection to death. And because these parameters can vary so much from infected person to infected person, it’s impossible to predict who will live and who will die. Therefore, despite accumulating evidence that most who acquire the coronavirus will not develop severe disease, the uncertainty of who is at grave risk enhances the pandemic’s terror.
In this regard, today’s situation is similar to past pandemics in which the matter of who would live and who would die was also mysterious — and led people to attribute outcomes to fortune or supernatural intervention. However, Covid-19 is different than the 1918 flu, in that today a robust scientific establishment can quickly analyze what’s happening and help figure out how best to prevent and treat infections.
CNN announced today that it has acquired the assets and hired the development team of Canopy, a Brooklyn and Boston based private personalization architecture company. The move will accelerate CNN’s development of “NewsCo” – the project name for its forthcoming news and information platform connecting users to trusted sources, storytellers and creators across a wide range of topics. The effort is the first from CNN’s recently formed team of strategists and technologists whose exclusive focus is the creation of new products and platforms to address ever-evolving user needs and drive future growth for the business.
“This acquisition enables us to light up in a single transaction a proven, best-in-class team whose deep knowledge and skill sets would’ve taken many months or even years to assemble,” said CNN EVP & Chief Digital Officer Andrew Morse. “Canopy’s culture of fast-cycle, iterative software and product development will enable us to more rapidly realize our ambitions and deliver against our goals.
Between January and late March, internet traffic increased by around a quarter in many major cities, according to Cloudflare, a US company that provides network infrastructure to businesses around the world. Demand has skyrocketed for certain online services in particular. Video calls have replaced face-to-face interaction with colleagues, family, and friends alike. More people started using the video-conferencing software Zoom in the first two months of 2020 than in all of 2019. Stay-at-home entertainment is also booming. Record numbers of people are using Steam, a popular online PC game store. At one point this weekend more than 24 million players were logged on at the same time, a 25% jump since February. And online grocery stores are unable to handle the surge in business, with customers waiting for hours in virtual lines tens of thousands of people long.
So how is the internet coping with the most sudden burst of usage in its history? There are understandable signs of strain: Wi-Fi that slows to a crawl, websites that won’t load, video calls that cut out. But despite the odd hiccup, the internet is doing just fine. In fact, the covid-19 crisis is driving the biggest expansion in years.
University of Virginia, The Cavalier Daily student newspaper, Zoe Ziff
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Researchers at the Biocomplexity Institute received a $10 million “Expeditions in Computing” grant from the National Science Foundation on March 25 to use computational and engineering methods to answer fundamental questions about epidemics and pandemics in real time. Although the team has been focusing on the COVID-19 pandemic since late December, the five-year grant aims to answer general questions about how these crises arise and model the best steps to take to minimize transmission and allocate resources.
With the data being collected globally, the Biocomplexity Institute has begun modeling the success of various governments’ policies, projecting which health systems will need the most resources in the near future and where the next virus hotspots will be. The Institute also works closely with federal, state and local policy makers, helping decision making related to the pandemic by sharing the projections they have modeled so far.
The grant also supports the group’s extended network of 14 institutions nationally and over a dozen researchers internationally to collect data from the ground.
Chicago Tribune; Chad Yoder, Kori Rumore and Jonathon Berlin
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As the seriousness of the coronavirus pandemic intensifies each day with a flood of data about increasing cases, deaths and soaring jobless claims, virtually every aspect of how people in Illinois work and play has changed. To capture some of these changes, the Tribune looked at data from pollution reports to smartphone app downloads to retail purchases.
During the “COVID-19 and AI” livestream event run by the Stanford Institute of Human-Centered AI (HAI), Stanford professor and HAI codirector Dr. Fei-Fei Li presented a concept for an AI-powered in-home system that could track a resident’s health, including for signs of COVID-19, while ensuring privacy.
It’s designed to keep seniors, many of whom live alone, connected to family or medical caregivers. The difficulty in caring for seniors in the midst of the COVID-19 pandemic is that the best way to protect them is to reduce contact with people — including those who would notice if they’re showing symptoms of the illness. This system seeks to address the problem of tracking seniors’ health without exposing them to risk from contact and would also allow caregivers to remotely monitor the base health of seniors who have existing medical conditions.
A team of data scientists, physicians, and engineers across the Mount Sinai Health System has come together to launch STOP COVID NYC, a web-based app to capture the symptoms and spread of COVID-19 in New York City—currently the epicenter of the nation’s largest outbreak. The group is seeking citywide participation to survey the spread of COVID-19 and enhance medical response to the pandemic.
The web app, now available by texting “COVID” to 64722, allows all Mount Sinai patients and city residents to enroll in the tool to monitor their symptoms. Users complete an initial survey with questions about demographics, exposure, and symptom history, followed by short daily surveys about their symptoms through text messages sent to their phones.
Today, the University of California Health will begin to distribute daily updates via its @UofCAHealth Twitter account about SARS-CoV-2 testing volume, the number of positive tests and age distribution of confirmed cases gathered from its five medical centers across the state.
“Fake news,” broadly defined as false or misleading information masquerading as legitimate news, is frequently asserted to be pervasive online with serious consequences for democracy. Using a unique multimode dataset that comprises a nationally representative sample of mobile, desktop, and television consumption, we refute this conventional wisdom on three levels. First, news consumption of any sort is heavily outweighed by other forms of media consumption, comprising at most 14.2% of Americans’ daily media diets. Second, to the extent that Americans do consume news, it is overwhelmingly from television, which accounts for roughly five times as much as news consumption as online. Third, fake news comprises only 0.15% of Americans’ daily media diet. Our results suggest that the origins of public misinformedness and polarization are more likely to lie in the content of ordinary news or the avoidance of news altogether as they are in overt fakery.
We are facing unprecedented times. Our situation is jarringly different from that of just a few weeks ago. Some of what we need to try today will have never been tried before. Similarly, what has worked in the past may very well not work today.
Humans are not that different from AI in these limitations, which partly explains why our current situation is so daunting. Without previous examples to draw on, we cannot know for sure the best course of action. Our traditional assumptions about cause and effect may no longer hold true.
An unexpected outcome of the current pandemic is that big tech companies, which have spent the past three years on the defensive over their data collection practices, are now promoting them. Over the past four days, Google and Facebook have unveiled new products that aim to improve our understanding of the disease’s spread and help public health organizations and nonprofits that are organizing response efforts. Those products are only made possible by the data we contribute with our smartphones.
The result has been a new kind of competition among the tech giants: who can come up with the most effective use of data to aid in the crisis.
… IUPUI School of Informatics graduate student Nikhil Morar showcased his talents on the biggest stage in early March by winning the sixth annual Hackathon presented by ESPN at the 2020 MIT Sloan Sports Analytics Conference in Boston. … “Our vision when we created a partnership with the School of Informatics to create a sports data analytics degree was to have students participating and competing in events hosted by MIT Sloan,” said David Pierce, director of the IUPUI Sports Innovation Institute. “Nikhil has been a leader since his first day on campus, and it is no surprise that he was able to succeed in a competitive national contest.”
Virologists are alerting doctors to a possibility that could help explain two of the most puzzling aspects of COVID-19—why the severity of the disease varies so widely, and how the infection can be so deadly. In severe cases the virus may enter the brain through the olfactory nerve in the nasal cavity and damage neurons that control breathing.
“Doctors should be aware of this possibility,” warns Pierre Talbot, Professor of Virology at the Institut Armand-Frappier, Université du Québec, Laval, Québec. “It may not be only pneumonia [killing patients]—the virus could be infecting the brain,” he says.
What do we know about Covid-19 and the coronavirus? What don’t we know? What are the implications of both? The team from The New York Times’s Science desk share their latest findings.
Speakers: Celia Dugger, NYT health and science editor; Carl Zimmer, NYT columnist; and Sheri Fink, NYT correspondent. [video, 43:54]
The introduction, and initial success, of the RISC-V processor ISA has reignited interest in the design of custom processors, but the industry is now grappling with how to verify them. The expertise and tools that were once in the market have been consolidated into the hands of the few companies that have been shipping processor chips or IP cores over the past 20 years.
Verification of a processor is different from the verification of other pieces of IP, or even an SoC. A processor is the ultimate piece of general-purpose hardware, and that creates its own unique set of issues.
“It can run any software program,” says Paul Cunningham, corporate vice president and general manager at Cadence Design Systems. “It is one of the most configurable deep-state devices that you can imagine. To truly say I’ve completed verification of the CPU is to say that you have run every possible software program that could run on that CPU, which of course you’ll never do. It is completely intractable. CPU verification is extremely difficult.”
As the coronavirus tears through the country, scientists are asking: Are some people more infectious than others? Are there superspreaders, people who seem to just spew out virus, making them especially likely to infect others?
It seems that the answer is yes. There do seem to be superspreaders, a loosely defined term for people who infect a disproportionate number of others, whether as a consequence of genetics, social habits or simply being in the wrong place at the wrong time.
But those virus carriers at the heart of what are being called superspreading events can drive and have driven epidemics, researchers say, making it crucial to figure out ways to identify spreading events or to prevent situations, like crowded rooms, where superspreading can occur.
Just as important are those at the other end of the spectrum: people who are infected but unlikely to spread the infection.
Census Bureau data shows we live near people with similar occupations, and right now frontline jobs are riskier for both health and economic well-being than working from home.
University of California-San Diego, Jacobs School of Engineering
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Engineers at the University of California San Diego have developed a new method that doesn’t require any special equipment and works in just minutes to create soft, flexible, 3D-printed robots.
The innovation comes from rethinking the way soft robots are built: instead of figuring out how to add soft materials to a rigid robot body, the UC San Diego researchers started with a soft body and added rigid features to key components. The structures were inspired by insect exoskeletons, which have both soft and rigid parts–the researchers called their creations “flexoskeletons.”
The new method allows for the construction of soft components for robots in a small fraction of the time previously needed and for a small fraction of the cost.
… In recent weeks a consensus has started to build among various groups of experts on what this new normal might look like. Some parts of the strategy will reflect the practices of contact tracing and disease monitoring adopted in the countries that have dealt best with the virus so far, such as South Korea and Singapore. Other parts are starting to emerge, such as regularly testing massive numbers of people and relaxing movement restrictions only on those who have recently tested negative or have already recovered from the virus— if indeed those people are immune, which is assumed but still not certain.
This will entail a considerable degree of surveillance and social control, though there are ways to make it less intrusive than it has been in some countries. It will also create or exacerbate divisions between haves and have-nots: those who have work that can be done from home and those who don’t; those who are allowed to move about freely and those who aren’t; and, especially in the US and other countries without universal health coverage, those who have medical care and those who lack it. (Though Americans can now get coronavirus tests for free by law, they may still wind up with hefty bills for related tests and treatment.)
Mathematical predictions may have missed how rapidly the novel coronavirus would develop from threat to world-wide pandemic, but researchers are working hard to find new models that will.
When it comes to something spreading through a population, be it a virus, social media meme or fake news, there are mathematical models that can be used to predict its trajectory. These models rely heavily on data taken at the outset but most assume that whatever is spreading is going to stay the same throughout its lifetime.
In reality, though, things can change rapidly and dramatically. For example, different viruses mutate at varying rates. In an effort to combat this shortcoming, a team of researchers from Carnegie Mellon University and Princeton University have developed a new mathematical model that incorporates this ‘evolution’ of an infectious entity.
International Business Times, The New York Times, Manthan Chheda
from
Even if a supervised learning system reads all the books in the world, it would still not be able to achieve human-level intelligence because a large chunk of our knowledge and expertise is not penned down.
Limitations of human supervision
Supervised learning comprises of feeding data, including images, audio, or text that is fed into computer algorithms, which teams machines to do what they do. However, this learning method has its restrictions.
“There is a limit to what you can apply supervised learning to today due to the fact that you need a lot of labeled data,” said Yann LeCun, an expert in the field of machine learning and artificial intelligence, and a recipient of the Turing Award, the equivalent of a Nobel Prize in computer science, in 2018. He is also the vice president and chief A.I. scientist at Facebook.
The algorithm that will decide who gets access to life saving care in the Commonwealth of Massachusetts was laid out on Apri 7th in this document: “Crisis Standards of Care Planning Guidance for the COVID-19 Pandemic”
At first, it sounds good, because the authors claim that “the Commonwealth’s approach to crisis standards of care is that such tragically difficult decisions must be based on criteria that ensure that every patient has equitable access to any care from which they might benefit.” [thread]
Getting more bright, low-income students into top schools is a laudable goal toward helping more people rise out of poverty. Dozens of elite college prep programs, from Leadership Enterprise for a Diverse America to the University of Chicago’s Collegiate Scholars Program, have been established across the United States in the last 20 years, each with heartwarming stories of college success.
But a newly published French study of one of that country’s most elite college prep programs for disadvantaged youth concluded that it harmed half the high school students who participated and left them worse off. It’s a cautionary tale about efforts to do good.
“The French and American contexts are so different but the finding that this work potentially did damage to students causes some pause and should be explored,” said Jason Klugman, director of the Princeton University’s Preparation Program.
arXiv, Computer Science > Computers and Society; Alessandro Vespignani et al.
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The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively, voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allow the user to share spatio-temporal aggregates – if and when they want, for specific aims – with health authorities, for instance. Second, we favour a longer-term pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.
As silicon photonics make their way closer to compute, the first wave of high-bandwidth devices has been centered around long-distance data-center-to-data-center connectivity. Over the last few years, technology grew in popularity within the data center. Bringing optics close to the compute here meant bringing optics to network switches. But switches only gets us so far. More recently, we’ve seen some of the first steps in the industry to bring silicon photonics directly to the processing chips themselves. One such company that’s been working on this technology is Ranovus, an Ontario, Canada based company. Founded in 2012, they have been working on various silicon photonics technologies. Today, they are ready to talk about their impressive technology.
Purdue University’s College of Science has named new academic leaders for its departments of Mathematics and Statistics.
Irena Swanson, Professor of Mathematics at Reed College in Portland, Oregon and a Purdue alumna, will become department head of mathematics.
Dennis K.J. Lin, University Distinguished Professor of Supply Chain and Statistics at Pennsylvania State University, will become department head of statistics.
A University of Massachusetts Amherst researcher is co-leading a multi-disciplinary team from around the United States to use big data to identify risk factors across systems for catastrophic events such as major power outages and natural disasters.
Mila Getmansky Sherman, a finance professor in the Isenberg School of Management, and a team she is co-leading recently received a $2.42 million National Science Foundation (NSF) grant under the auspices of the NSF’s Harnessing the Data Revolution Big Idea program.
The Predictive Risk Investigation System for Multilayer Dynamic Interconnection Analysis (PRISM) is a three-year study that aims to harness data in order to look at worst-case scenarios in a catastrophe, the risks associated with them and measure their likelihood.
8. What would you recommend for people from academia who are moving to industry?
I am very happy that I work in industry now; I love seeing impact from my work on a short timescale and having flexibility in finding an employer that is a good fit for my values and preferences. The skills and signals of competence in industry are somewhat different than in academia, but it’s important for folks in academia to know that their skills are valuable. The important step is to build out a professional persona that communicates competence clearly, through signals like building a data science portfolio, networking and giving talks, or open source contributions (instead of signals like publishing papers). It looks like the hiring market may be especially tough in upcoming months due to global financial conditions, so resilience and commitment will be even more necessary during what can be a challenging transition.
An IBBME researcher is developing a wearable technology that reminds frontline health-care workers to consistently wash their hands. This technology could significantly reduce the spread of Hospital-Acquired Infections (HAIs), including COVID-19.
Dubbed the Buddy Badge, the wearable device acts as a transponder, using a system of sensors connected to hand-washing stations, doorways, and critical routes to patient rooms. If the badge wearer has not washed their hands before entering a patient’s room, for example, it will discreetly vibrate to remind them to do so.
Another thing that’s in short supply is the realization of how little we know. Even a quick glance at social or traditional media will reveal many people who express themselves with way more confidence than they should. Legal scholar Richard A. Epstein of the Hoover Institution incorrectly claims to have expertise in epidemiology. His predictions were proven false within a week. The president’s son-in-law Jared Kushner, who’s reportedly directing the White House response, has no domain-relevant expertise or training—but does not let that fact stop him from contradicting and overruling U.S. health officials. Peter Navarro, White House trade advisor, believes his training in social science gave him all the tools required to assess medical science.
We see a slow return to work with US cases peaking in ~50days. We expect social distancing reductions in June asdiagnostic/serology testing are widely available and hospitalcapacity is extended. Variable levels of social distancing willremain until a vaccine is widely available in Spring 2021.
US likely to experience two peaks – one for the coastal regions and one for theinterior: We have built individual state models to look at the time to peak acrossthe US. While we expect an initial peak in ~14 days for the cities with the firstoutbreaks, we see a second peak from interior regions of the country pushing theultimate US peak to mid-May (Exhibit 1). While we would expect someresumption in activity in the coastal regions prior to a full US peak, we believeresumptions will be limited until a full US peak. Governors will be hesitant tobroadly relax their social distancing until the immediate threat of imported casesis diminished. We believe our view of a peak in mid-May could beunderappreciated by the market. [pdf]
Objective To provide focused evaluation of predictive modeling of electronic medical record (EMR) data to predict 30 day hospital readmission.
Design Systematic review.
Data source Ovid Medline, Ovid Embase, CINAHL, Web of Science, and Scopus from January 2015 to January 2019.
Eligibility criteria for selecting studies All studies of predictive models for 28 day or 30 day hospital readmission that used EMR data.
Outcome measures Characteristics of included studies, methods of prediction, predictive features, and performance of predictive models.
Results Of 4442 citations reviewed, 41 studies met the inclusion criteria. Seventeen models predicted risk of readmission for all patients and 24 developed predictions for patient specific populations, with 13 of those being developed for patients with heart conditions. Except for two studies from the UK and Israel, all were from the US. The total sample size for each model ranged between 349 and 1 195 640. Twenty five models used a split sample validation technique. Seventeen of 41 studies reported C statistics of 0.75 or greater. Fifteen models used calibration techniques to further refine the model. Using EMR data enabled final predictive models to use a wide variety of clinical measures such as laboratory results and vital signs; however, use of socioeconomic features or functional status was rare. Using natural language processing, three models were able to extract relevant psychosocial features, which substantially improved their predictions. Twenty six studies used logistic or Cox regression models, and the rest used machine learning methods. No statistically significant difference (difference 0.03, 95% confidence interval −0.0 to 0.07) was found between average C statistics of models developed using regression methods (0.71, 0.68 to 0.73) and machine learning (0.74, 0.71 to 0.77).
Conclusions On average, prediction models using EMR data have better predictive performance than those using administrative data. However, this improvement remains modest. Most of the studies examined lacked inclusion of socioeconomic features, failed to calibrate the models, neglected to conduct rigorous diagnostic testing, and did not discuss clinical impact.
In the latest piece to come out of the FTC’s new focus on emerging technologies, the FTC Bureau of Consumer Protection issued new guidance on the use of artificial intelligence (“AI”) and algorithms. The guidance follows up on a 2018 hearing where the FTC explored AI, algorithms, and predicative analysis. As the FTC recognizes, these technologies already pervade the modern economy. They influence consumer decision making – from what video to watch next, to what ad to click on, or what product to purchase. They make investment decisions, credit decisions, and, increasingly, health decisions, which has also sparked the interest of State Attorneys General and the Department of Health & Human Services. But the promise of new technologies also comes with risk. Specifically, the FTC cites an instance in which an algorithm designed to allocate medical interventions ended up funneling resources to healthier, white populations.
In this stop-motion animation, Symmetry writer Sarah Charley, stuck at home in France during the global pandemic, depicts a short story in which a physicist (played by her partner, Maxime) is unable to cook what he wants with the ingredients he has. It’s not easy to get the grocery while sheltering in place, so he decides to use the physics at work in the Large Hadron Collider to get what he needs.
The LHC accelerates tiny particles called protons and smashes them together. The energy from those collisions converts into more massive particles such as Higgs bosons, which then quickly decay, releasing their energy in the form of less massive particles. Maxime quickly scribbles down some Feynman diagrams and an equation representing the Standard Model of particle physics and decides to test whether the same principles can be applied to dinner.
In a new move to stop the spread of dangerous and false information about the coronavirus, Facebook will start telling people when they’ve interacted with posts about bogus cures, hoaxes and other false claims.
In the coming weeks, Facebook users who liked, reacted to or commented on potentially harmful debunked content will see a message in their news feeds directing them to the World Health Organization’s Myth busters page. There, the WHO dispels some of the most common falsehoods about the pandemic.
“We want to connect people who may have interacted with harmful misinformation about the virus with the truth from authoritative sources in case they see or hear these claims again off of Facebook,” wrote Guy Rosen, Facebook’s vice president for integrity, in a blog post.
Look at a thousand of the millions of Facebook ads Donald Trump has run, and it’s hard to believe that they represent a winning strategy. They recycle the same imagery and themes, over and over: Trump, photoshopped in front of a flag, points a finger. Trump claps before an audience. Trump gives a thumbs-up, or smiles at a microphone. Each image is washed in patriotic red or blue. The text almost always issues a call to action: Buy this hat, sign this petition, RSVP to this rally.
They are notable only in their banality, and in their sheer volume. During the 2016 election cycle, Trump’s team ran 5.9 million ads on Facebook, spending $44 million from June to November alone. Hillary Clinton’s campaign ran only 66,000. In 2020, Democrats are still buying fewer ads: According to the Facebook ad archive, only Michael Bloomberg approached the ad volume of the Trump campaign, running more than 50,000 ads in February of this year, his last month in the race. During that time, Bernie Sanders bought only 8,400, Elizabeth Warren and Joe Biden even fewer. Everyone is using Facebook, but Trump is doing something different and, by most accounts, better.
Looking at data at the county level rather than the state level allowed them to find trends “hidden” in the larger view, the researchers say. The results, compiled in an interactive visualization, are a way to more efficiently track coronavirus clusters and direct urgently needed resources.
“County-level visualizations show a dramatically more detailed pandemic landscape, where aggregate data alone can miss local hot spots of surging COVID cases,” says Marynia Kolak, assistant director of health informatics at the Center for Spatial Data Science at the University of Chicago. “If you only look at state-level data, a county cluster would have to be extreme to show up, and by then you’re already too late for many of these prevention measures.”
County College of Morris (CCM) has received a $235,000 grant from the National Science Foundation (NSF) to support the launch of a Data Science Certificate program. … The CCM Data Analytics Certificate will consist of five courses for a total of 15 credits that could be completed over the course of two semesters. Students in the program will learn R, Tableau, Python and SQL. The first course Introduction to Data Science will be offered this fall. One of the chief goals of the new program is to increase the number of women and other underrepresented students studying data analytics.
We realized that most visualizations in the public sphere don’t incorporate or overlay intervention information, so it’s hard to see the curve “flattening”, if at all.
I am delighted to announce the appointment of Barbara Rockenbach as the next Stephen F. Gates ’68 University Librarian, effective July 1, 2020, pending the approval of the board of trustees at their next meeting. She is currently the associate university librarian for research and learning at Columbia University. Ms. Rockenbach has spent her career developing innovative library services in support of education and scholarship. She brings to Yale deep expertise and a commitment to ensuring that our libraries will continue to evolve to meet the changing needs of faculty and students.
Ms. Rockenbach believes strongly that university libraries must balance a dedication to supporting emerging areas of research and scholarship with a commitment to maintaining and increasing collections in all formats. For nearly nine years at Columbia University, she has demonstrated an ability to strike that balance. For example, she built a digital humanities program in close collaboration with faculty members and library staff — this effort was funded by grants from the National Endowment for the Humanities, the Mellon Foundation, and the Arcadia Foundation. At the same time, she enhanced existing collections.
The University of Manchester and Finland’s Aalto University have entered into a strategic cooperation agreement to further health-AI research.
Aalto University’s excellence in artificial intelligence (AI), combined with The University of Manchester’s strengths in data science and AI combined with health systems, will accelerate vital research and development in data-driven healthcare and related areas.
The new collaboration will apply joint expertise to the innovative use of AI and machine learning in the medical sector. In Manchester the work will be focused around the existing Christabel Pankhurst Institute for Health Technology.
As understanding of the novel coronavirus and its impact builds, there have already been countless efforts to visualize new data. While many COVID-19 data visualizations exist, in my opinion few are as evocative and memorable as those produced by the Reuters Graphics team. The team has been at the forefront of visualizing COVID-19 since January 2020 and has produced numerous works capturing how the pandemic has dramatically changed lives globally. Simon Scarr (Reuters Graphics) kindly took time to share some insight on the team’s data visualization process.
Even as America continues to see the death toll of COVID-19 rise, the unfortunate reality is that this pandemic will follow us for many months even after cases decline. Experts suggest we’ll weather 18 months of outbreaks across the globe before we have a vaccine, which means we might not shelter in place just once to get the virus under control. Rather, our behavior will need to be rapidly tweaked, city-by-city, as new cases crop up, to thwart new exponential spread.
Which is why Andy Slavitt, the former Acting Administrator of the Centers for Medicare and Medicaid Services appointed by President Obama, has a suggestion: “We’re going to need to find a way to communicate [threats and appropriate behaviors] as they come and go, and we need a national standard,” says Slavitt, who’s also the founder of healthcare nonprofit United States of Care. His solution, which he says he’s proposed to the White House, is to build a nationwide, color-coded alert system much like the Department of Homeland Security implemented to warn of terrorist attacks following 9/11—or much like New Zealand has implemented to warn about COVID-19 right now.
University of California-San Diego, UC San Diego UC San Diego News Center
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Researchers at the University of California San Diego have been applying their high-performance computing expertise by porting the popular UniFrac microbiome tool to graphic processing units (GPUs) in a bid to increase the acceleration and accuracy of scientific discovery, including urgently needed COVID-19 research.
“Our initial results exceeded our most optimistic expectations,” said Igor Sfiligoi, lead scientific software developer for high-throughput computing at the San Diego Supercomputer Center (SDSC) at UC San Diego. “As a test we selected a computational challenge that we previously measured as requiring some 900 hours of time using server class CPUs, or about 13,000 CPU core hours. We found that it could be finished in just 8 hours on a single NVIDIA Tesla V100 GPU, or about 30 minutes if using 16 GPUs, which could reduce analysis runtimes by several orders of magnitude. A workstation-class NVIDIA RTX 2080TI would finish it in about 12 hours.”
North Carolina’s first school of data science is scheduled to open this fall at UNC Charlotte, expanding the current Data Science Initiative into a standalone institution.
The new School of Data Science will expand on the master’s program run under the existing initiative. Doug Hague, who served as the interim director of the Data Science Initiative, will become the executive director.
LIGO’s mirrors are imperfect, however, because of a strange form of noise that is baked into glass, a mysterious substance in general. Glass consists of atoms or molecules that are haphazardly arranged like those in a liquid yet somehow stuck, unable to flow. Physicists believe that the noise inherent in glass comes from small clusters of atoms switching back and forth between two different configurations. These “two-level systems” ever so slightly change the distance laser light travels between LIGO’s mirrors, since the surface of each glassy layer shifts by as much as an atom’s width.
“LIGO at this point is literally limited by that,” said Frances Hellman, a glass specialist at the University of California, Berkeley and a member of the 1,000-person LIGO scientific team. Despite the detectors’ “astonishing vibration isolation, damping, all kinds of stuff that has led to the extraordinary sensitivity,” Hellman said, “the one thing they haven’t been able to get rid of are these funny little atomic motions in the mirror coatings.” Given the thousandth-of-an-atom amplitude of the gravitational waves LIGO is looking for, the atomic motions are a big problem.
There’s hope, though. Fueled by recent theoretical insights about the nature of glass, Hellman’s group and others are racing to find more perfect glass to use in LIGO’s mirrors.
LabCorp’s at-home COVID-19 test, which is called ‘Pixel,’ has received the first Emergency Use Authorization (EUA) for such a test issued by the U.S. Food and Drug Administration (FDA). The test is an at-home collection kit, which provides sample collection materials including a nasal swab to the user, who then uses the included shipping package to return the sample to a lab for testing.
Until now, the FDA has not authorized any at-home testing or sample collection kits for use, and in fact clarified its guidelines to specifically note that their use was not authorized under its guidelines when a number of startup companies debuted similar products for at-home collection and round-trip testing with labs already certified to run molecular RT-PCR tests to detect the presence of COVID-19.
At East Elementary School in Littleton, the focus is all about getting to the heart of each individual child. But a new program, Operation Dragon Heart, is taking it a step further, by allowing kids to monitor their heart rates with fitness trackers. But rather than tracking their fitness, the goal is to help students monitor their emotional state.
Third-grade student Charlotte Sherwood explained how the watches’ colors work.
“Blue means you’re calm and relaxed, yellow means you’re elevated, so you have to calm down a bit, and red means you are really high,” she said.
The trackers, purchased from IHT, alert the kids that their heart rate is rising with changing colors. Around 30 kids use them every day as part of the pilot program. When they notice their heart rate rising, they use tactics like belly breathing or meditation to calm back down.
A team of statistics and data science researchers have devised a predictive framework for assessing trail running performance. Riccardo Fogliato, Natalia L. Oliveira and Ronald Yurko, PhD candidates in statistics and data science at Carnegie Mellon University in Pittsburgh, propose a framework called Trail Running Assessment of Performance (TRAP), which assesses runners’ performance both before and during a race.
The framework takes into account three factors: the runner’s ability to reach the next checkpoint (or put another way, their probability of dropping out); the runner’s expected passage time at the next checkpoint; and predicted intervals for the passage time.
As the coronavirus pandemic forces all sports leagues to evaluate how to once again host thousands of fans at stadiums across the country, at least one prominent data scientist at the Massachusetts Institute of Technology says there are steps teams can take that will make arenas “as safe as public parks.”
Professor Alex Pentland, the head of the human dynamic lab at MIT, released a white paper this week suggesting companies can use digital tools to help create safer environments — and told ESPN there are applications to sports as well.
“The big things are distancing practices,” such as asking fans to wear masks, Pentland said.
Drones are an emerging solution which makes particular sense in a disaster setting. Unmanned autonomous vehicles (UAVs), commonly known as drones, have the potential to enable faster, safer delivery of critical medicines and vaccines and bypass impacted infrastructure on the ground. Organizations are working together across a variety of collaborative projects to experiment and advance drone technology.
My company has also been participating in this work and our latest test flight achieved an important milestone: last year, together with several partners, and following previous tests to Puerto Rico post Hurricane Maria, we successfully flew a drone to the Bahamas over open water beyond the operator’s line of sight. Today, it is fairly typical to maintain a temperature range of between 2-8 degrees Celsius within the payload of a drone. However, on this flight, the cold-chain delivery technology onboard allowed for precise temperature control at minus 70 degrees Celsius, the temperature required for storing and transporting some life-saving vaccines. This success proves the feasibility of using drones in the future to deliver vaccines and temperature-dependent medicines to remote locations – a practical advance that has major implications.
“Pandemic Research Exceptionalism” is the idea that the urgency of a crisis warrants lowering #research standards. We argue against this view. [thread]
According to @COVID19Tracking
, the US is managing roughly 150k tests per day at this point. These 150k tests are finding about ~30k confirmed cases each day. However, I believe based on modeling results and serology that these have a 10-20X underreporting rate. 2/9
In recent days, attention has focussed on the differential impacts on populations within cities. In particular, African Americans are dying at disproportionate rates in Chicago, Detroit, and Philadelphia. To address this situation, it is important to disentangle the impacts of exposures to the virus from the availability of appropriate care. Location data allow a first step in measuring neighborhood-level variation in quarantining and exposures to congested spaces.
They believe that if you just let the wave pass through the population that you’ll have 70 or 80 percent of the population infected and you won’t have a subsequent wave,” [Samuel] Scarpino told an audience of over 200 researchers, students, and others on Thursday in an online seminar as part of a series presented by the University of Maryland’s network biology program, in partnership with the University of Vermont’s Complex Systems Center.
But those estimates are way too high, Scarpino said. “It’s going to be somewhere like 5 to 20 percent, and you’re going to have multiple waves of infections because you’re still going to have a large fraction of the population susceptible.”
TheHill, Opinion, Marlone Henderson and Art Markman
from
Rather than pushing for speedy, unproven solutions, scientists should set up standing review panels for studies being done in response to the pandemic so that research findings can be reviewed quickly but accurately. They should coordinate efforts among researchers to try to provide multiple independent attempts to obtain the same finding. And when in doubt, rely on older evidence that has not just been peer-reviewed but has stood the test of time. Finally, on those occasions when a new finding is discussed in public forums before being vetted, scientists should treat the data with caution and skepticism.
But Thorp wasn’t really fired up until he heard President Trump tell pharmaceutical executives that they should speed up work on a vaccine. That led to the hugely popular editorial “Do Us a Favor.” Addressing the president, Thorp wrote: “If you want something, start treating science and its principles with respect.”
Not only is it dangerous to skip important steps in the drug development process, but Trump “implies that science wouldn’t want to go fast, that we’ve been holding back for some reason,” he says to C&EN. “To say, ‘Do me a favor, speed up’ with no idea as to why things have to be done the way they have to be done is just so disrespectful.”
In this time when all eyes are on science, Thorp thinks it is vital that scientists be honest about what they can and can’t do. “We have to be very careful that we don’t let this moment cause us to exaggerate how quickly we’re going to be able to respond,” he says.
Researchers from Duke University have devised a method for estimating the air quality over a small patch of land using nothing but satellite imagery and weather conditions. Such information could help researchers identify hidden hotspots of dangerous pollution, greatly improve studies of pollution on human health, or potentially tease out the effects of unpredictable events on air quality, such as the breakout of an airborne global pandemic.
The results appear online in the journal Atmospheric Environment.
“We’ve used a new generation of micro-satellite images to estimate ground-level air pollution at the smallest spatial scale to date,” said Mike Bergin, professor of civil and environmental engineering at Duke. “We’ve been able to do it by developing a totally new approach that uses AI/machine learning to interpret data from surface images and existing ground stations.”
As the spread of the coronavirus eases and people gradually return to work pondering the impact it might have on their jobs, Europe’s second-biggest port is getting ready to test a device aimed at helping thousands of people employed there to respect social distancing.
At Antwerp in Belgium, where some 900 companies operate in an area the size of a small town, two teams of port workers will be wearing next month a bracelet originally designed to find tugboat crew members that have fallen overboard but now modified to help stop the spread of the disease.
CSAIL director and MIT Schwarzman College of Computing deputy dean of research will serve on the President’s Council of Advisors on Science and Technology.
So, how worried should you be that any time you go outside, you’ll contract coronavirus from a fellow pedestrian, runner, or cyclist who happens to exhale as they pass by?
The answer is, you probably don’t need to freak out about it. As long as you’re maintaining at least 6 feet of distance from other people and you’re not in a high-risk group, you’re engaged in a very low-risk activity, particularly if you and others are wearing masks.
By sampling sewage across greater Paris for more than 1 month, researchers have detected a rise and fall in novel coronavirus concentrations that correspond to the shape of the COVID-19 outbreak in the region, where a lockdown is now suppressing spread of the disease. Although several research groups have reported detecting coronavirus in wastewater, the researchers say the new study is the first to show that the technique can pick up a sharp rise in viral concentrations in sewage before cases explode in the clinic. That points to its potential as a cheap, noninvasive tool to warn against outbreaks, they say.
“This visibility is also going to help us predict a second wave of outbreaks,” says Sébastien Wurtzer, a virologist at Eau de Paris, the city’s public water utility. Wurtzer and his colleagues posted the study, which has not been peer-reviewed, on the preprint repository medRxiv on 17 April.
JAMIA Journal American Medical Informatics Association; Robert W Turer et al.
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Emergent policy changes related to telemedicine and the Emergency Medical Treatment and Labor Act (EMTALA) during the novel coronavirus pandemic (COVID-19) have created opportunities for technology-based clinical evaluation, which serves to conserve personal protective equipment (PPE) and protect emergency providers. We define electronic personal protective equipment (ePPE) as an approach using telemedicine tools to perform electronic medical screening exams while satisfying EMTALA. We discuss the safety, legal, and technical factors necessary for implementing such a pathway. This approach has the potential to conserve PPE and protect providers while maintaining safe standards for medical screening exams in the ED for low risk patients in whom COVID-19 is suspected. [full text]
Oxford Academic, Journal American Medical Informatics Association
from
“a Gold Open Access journal which provides a global forum for the publication of novel research and insights in the major areas of informatics for biomedicine and health (e.g., translational bioinformatics, clinical research informatics, clinical informatics, public health informatics, and consumer health informatics), as well as related areas such as data science, qualitative research, and implementation science.”
To truly understand whether a place has reached the peak of its infection curve, you need to be a savvy reader of the charts and the underlying data. And, ideally, you need to look at more than one chart.
So what should you keep in mind when you’re trying to interpret all these data visualizations?
Los Alamos scientists estimated how fast the curve is flattened in 51 countries. They determined that arbitrarily re-opening societies can allow COVID-19 to undo that progress much faster than it took to achieve it. Widespread testing would help to manage the difference.
MGH Institute for Technology Assessment, Harvard Medical School
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The Coronavirus Disease 2019 Simulator (COVID-19 Simulator) is a tool to help policy makers decide how to respond to the novel coronavirus pandemic. The tool evaluates the impact of different social-distancing interventions (by varying their intensity and timing) on reduction in the spread of coronavirus in 50 states and District of Columbia. The information presented can help policymakers understand consequences such as the rate of new cases, potential strain on the healthcare system, and projected deaths. The COVID-19 Simulator combines infectious disease modeling and statistical modeling to simulate the trajectory of COVID-19 at the state level from March 15, 2020 to August 31, 2020 in the United States. Utilizing the most recent reported data for each state, the COVID-19 Simulator considers state-specific disease spread dynamics.
More than 50,000 academic articles have been written about COVID-19 since the virus appeared in November.
The volume of new information isn’t necessarily a good thing.
Not all of the recent coronavirus literature has been peer reviewed, while the sheer number of articles makes it challenging for accurate and promising research to stand out or be further studied.
Computer science and linguistics professor James Pustejovsky is leading a Brandeis team in creating an artificial intelligence platform called Semantic Visualization of Scientific Data — or SemViz — that can sort through the growing mass of published work on coronavirus and help biologists who study the disease gain insights and notice patterns and trends across research that could lead to a treatment or cure.
Peer review was never meant to be a perfect process, nor could it be. And most peer review is productive, polite, and necessary. But sometimes one of the reviewers is just a teensy bit … how to say this … horrible.
It’s such a common complaint among scientists, in fact, that kvetching about rotten peer reviews has spawned Twitter accounts and even academic studies about the harm these unprofessional criticisms cause to both science and scientists.
If any of the following sound familiar, you may have been the victim of a bad peer review yourself:
IEEE Fellow Satyandra K. Gupta is leading a research team at the University of Southern California’s Viterbi Center for Advanced Manufacturing in Los Angeles that is building a robotic arm that uses a UV light sanitizer to clean contaminated areas.
When it comes to her research, Eva Lee sweats the details. The Georgia Institute of Technology engineering professor “is extraordinarily talented” at sifting through massive amounts of health care data and finding “novel insights” into how to save lives, improve care, and reduce costs, says physician scientist Brent Egan of the American Medical Association (AMA), who has collaborated with Lee on treating patients with cardiovascular disease.
Lee’s skills are now in high demand. Public health officials from around the world responding to the COVID-19 pandemic are clamoring to use software that she began to develop nearly 2 decades ago. And Lee’s participation in a group of U.S. scientists who raised an early alarm about the pandemic have garnered her national media attention, including on the front page of The New York Times.
In contrast, she’s paid much less attention to the reporting requirements on the grants that have supported her research for more than 2 decades at Georgia Tech. And the 55-year-old applied mathematician is now paying a steep price for that neglect.
Thrilled to be announcing a big next step: I will be joining the faculty of the University of Massachusetts at Amherst this coming year, and launching a new research center. My friends at UMass have created a unique position for me. I will be an associate professor of public policy, communication and information, with my tenure home in public policy, but teaching in all three departments. My first class at UMass will be in the spring of 2021, the Fixing Social Media class I’ve been teaching this semester at MIT.
Can you tell us a little about the generative design technology at Autodesk?
Vikram Dutt: At Autodesk, we view generative design technology as a tool to help our customers adopt more automated ways of performing design exploration. Initially, our generative design-based initiatives were focused to the manufacturing industry, but now, with the introduction of Autodesk Revit 2021, we’ve expanded this powerful technology to the industries of architecture, engineering and construction. We believe the introduction of Generative Design in Revit will allow AEC professionals to explore, evaluate and identify solutions tailored to project goals and constraints – considering a wide range of factors like density, aesthetics, efficiency and sustainability along the way. Through generative design technology, we’re striving to help these professionals spend less time on tedious tasks and, instead, focus their expertise on more complex design challenges.
As the threat of COVID-19, the disease caused by the novel coronavirus, became apparent in early March, US universities and colleges rushed to implement contingency plans that protected their students and staff but also ensured that learning continued. In addition to extending spring break and moving courses to an online-only format, schools such as the University of California, Berkeley, and the University of North Carolina at Chapel Hill gave students the option of switching from letter grades to pass-fail in their major courses. This move took pressure off both students and professors during a difficult time. “When we think about what our students really need—how do we get through this, how do we focus on the essentials—for some institutions, grades took a big back seat,” says Karen Cangialosi, a professor of biology at Keene State College.
Cangialosi thinks that prioritization says something about the importance of grades in general. Are they really necessary, during a pandemic or otherwise, to ensure students have learned the required material?
Carl Bergstrom is uniquely suited to understanding the current moment. A professor of biology at the University of Washington, he has spent his career studying two seemingly disparate topics: emerging infectious diseases and networked misinformation. They merged into one the moment reports of a mysterious respiratory illness emerged from China in January.
The coronavirus touched off both a pandemic and an “infodemic” of hoaxes, conspiracy theories, honest misunderstandings and politicized scientific debates. Bergstrom has jumped into the fray, helping the public and the press navigate the world of epidemiological models, statistical uncertainty and the topic of his forthcoming book: bullshit.
The following interview has been edited for length and clarity.
Our goal is to empower communities and help drive progress towards a more equitable criminal justice system in the United States. Learn more about the Microsoft Criminal Justice Reform Initiative as several of our employees join together with criminal justice leaders Rebecca Neusteter and Seattle Police Chief Carmen Best to share their thoughts on the role of technology and data to create change. [video, 3:40]
It was a huge step forward when the Congress provided $11 billion to the states to jumpstart spending on tests and another $14 billion to develop better tests.
But $25 billion is not enough. To make everyone feel safe going back to work, we must commit to spending $100 billion per year to purchase about 9 billion tests per year. The quid pro quo for committing to buying this many tests must be that the price per test come down to $10.
Projects that harness the power of data, machine learning, or artificial intelligence to understand the world and empower change. Read about the winner: an online tool helps you make sure your retirement investments reflect your values.
Use this map to see if people in your area could be infected with COVID-19. And don’t forget to update us every day with your symptoms so we can continue to track hot spots.
It’s important to know how the process of data visualization can shape our perception of the crisis. In this video, we deconstruct one particularly popular chart of covid-19 cases around the world which uses a logarithmic scale, and explain how to avoid being misled by it. [video, 4:57]
The Partnership on AI; Riccardo Fogliato, Alice Xiang , Alex Chouldechova
from
In an effort to protect the health and safety of inmates and the Federal Bureau of Prisons (BOP) personnel in the wake of the COVID-19 pandemic, Attorney General William Barr issued a memo on March 26, 2020, listing a set of discretionary factors for determining which inmates should be transferred from prison to home confinement.
Among the key factors established in the memo is the use of an algorithmic risk assessment tool called “PATTERN”—a tool developed to measure recidivism risk, but that has been documented to exhibit racial biases. In using this tool, inmates scoring anything above “minimum,” the lowest level of risk, are not to be prioritized for home confinement. Since the release of the memo, BOP has placed a mere 1,576 inmates in home confinement—just over 1% of the over 140,000 who are at risk of contracting COVID-19.
This use of PATTERN may lead to significant racial disparities among the inmates placed in home confinement, making federal prisons yet another place where we see higher infection rates and death rates among Blacks.
The metric being tracked here (Rt) represents the effective reproduction rate of the virus calculated for each locale. It lets us estimate how many secondary infections are likely to occur from a single infection in a specific area. Values over 1.0 mean we should expect more cases in that area, values under 1.0 mean we should expect fewer. [data viz]
Lets start here: Meet Lincoln. Right now, he’s struggling to breathe in an ICU in Denver -unless he died in the last few hours. His family, the Zimmermans, did everything right. But he still contracted COVID-19…/1
…other parents are mourning their dead children, taken away by COVID, children whose infection could not confirmed until after their lifeless, cold bodies were wheeled from their homes, or from their hospital rooms to the morgue…/2
While the health industry and Democrats still want to bolster Obamacare, an unusual bloc is pressuring Congress to fully subsidize workplace premiums for the uninsured. Corporations would benefit because the employer-based system supplies a big tax break for benefits they can use as a recruiting tool. Unions would keep the generous coverage they have negotiated with corporations. And hospitals and doctors could maintain the big payouts from private insurance, which are far higher than the Medicare and Medicaid rates paid by government.
Carnegie Mellon University, School of Computer Science
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Intelligent tutoring systems have been shown to be effective in helping to teach certain subjects, such as algebra or grammar, but creating these computerized systems is difficult and laborious. Now, researchers at Carnegie Mellon University have shown they can rapidly build them by, in effect, teaching the computer to teach.
Using a new method that employs artificial intelligence, a teacher can teach the computer by demonstrating several ways to solve problems in a topic, such as multicolumn addition, and correcting the computer if it responds incorrectly.
Notably, the computer system learns to not only solve the problems in the ways it was taught, but also to generalize to solve all other problems in the topic, and do so in ways that might differ from those of the teacher, said Daniel Weitekamp III, a Ph.D. student in CMU’s Human-Computer Interaction Institute (HCII).
The Texas A&M University System National Laboratories Office (NLO) and Los Alamos National Laboratory have formed a collaborative research effort to make extremely large data sets indexable and more easily searchable.
“We are excited to be partnering with our colleagues at Texas A&M on this important and potentially game changing research. This collaboration leverages extreme strengths in data management research from both our organizations,” said Gary Grider, division leader for High Performance Computing at Los Alamos
The unexpected transition to online classes due to the COVID-19 pandemic has prompted many changes for undergraduate students and their instructors. To understand the magnitude of these impacts and potentially improve digital learning, researchers in the Penn State School of Engineering Design, Technology, and Professional Programs (SEDTAPP) have received $196,136 from the National Science Foundation (NSF).
With a particular focus on women and traditionally underrepresented groups, the one-year project will gather data from students enrolled in a first-year design course offered in the College of Engineering.
“When we suddenly changed our undergraduates’ fundamental experience by transitioning to a digital environment, we were motivated to understand how this shift might affect the formation of engineering identities,” said Jessica Menold, assistant professor of engineering design and mechanical engineering and the principal investigator of the project.
There’s a chance your Fitbit, Apple Watch, WHOOP or another smartwatch device could mean more to your health than just counting your steps, recommending you go to sleep earlier or reminding you to get off your couch.
Known as fitness wearables, fitness trackers or simply a smartwatch, the devices are a more elaborate version of the everyday wristwatch, and millions are using them in a pairing with their smartphones to track various body metrics — from heart rate and temperature to blood oxygen levels.
Dr. Michael Mina, an assistant professor of epidemiology at Harvard University, told ESPN that smartwatches are “incredible devices” — so incredible that they have the potential to track COVID-19 and other viral diseases if “networked appropriately.”
Apple Inc and Alphabet Inc’s Google on Monday said they would ban the use of location tracking in apps that use a new contact tracing system the two are building to help slow the spread of the novel coronavirus.
The City-led Object Recognition for Blind Image Training (ORBIT) research project is recruiting blind and low vision users to record videos of objects that are important to them. The object will be used in the training and testing of artificial intelligence (AI) models for personalising object recognition.
That some scientists are venal, fallible and selfish may come to be as important as their virtue, diligence and humanism. The systems they work within matter, too. Mechanisms for the peer review of their work, the success, or not, of their funding applications, and the pursuit of promotions, are all open to gaming and interference. These are all framed by what some sociologists call ‘cultural scripts’.
After all, who decides what questions should be pursued in all this, what matters most and what ought to be prioritised. How any ensuing data (limited as it is in both scope and specificity) is to be interpreted is another key issue. Inevitably, decision-makers (and scientists) have other agendas, too – as we all do. Science, then, is not an exact science, but a deeply cultural activity.
Business Closures and Rapid Consumer Reaction to the Public-Health Threat Added up to Several Hurricanes Worth of Local Economic Upheaval Across the U.S.
The economic changes from the first quarter of 2020 were unlike anything we’ve ever seen. In a period of about 15 days as the nation reacted to the threat of the coronavirus pandemic, the economy transformed as much as it had in Yelp’s prior 15 years of operation, combined.
So rather than share one indicator of economic strength for the whole quarter, as we normally report in our Yelp Economic Average, we are sharing several indicators that track what happened throughout the quarter, from its typical first 10 weeks to its final three weeks of upheaval.
Crisis situations like COVID-19 bring up several issues affecting the research enterprise, including changes in the practice of science and ways in which we are training the biomedical workforce to address societal problems with larger overarching implications beyond the university. Overall, in this climate, scientists should inform policymakers of the scientific evidence needed to advance policies that serve the academic community, as well as arm the general public with knowledge to participate in fighting against this pandemic. We must carefully consider the broader effects of this pandemic on society as a whole, and the role of each stakeholder in combating it as part of a larger community.
Advocating for improved policies and funding required to sustain efforts needed to fight this pandemic is equally, if not more important, now than ever before. The challenge is that advocacy largely entails in-person interactions and support garnered through letters and other documents signed by a range of policy decision-makers. While virtual environments hinder meaningful human interactions, technology can allow stakeholders to engage in advocacy in ways that may not traditionally be part of the field.
Since 2014, the Make Data Count (MDC) initiative has focused on building the social and technical infrastructure for the development of research data metrics. With funding from the National Science Foundation, Gordon and Betty Moore Foundation, and Alfred P. Sloan Foundation, the initiative has transformed from a research project with an aim to understand what researchers value about their data, to an infrastructure development project, and now into a full-fledged adoption initiative. The team is proud to announce additional funding from the Sloan Foundation to focus on widespread adoption of standardized data usage and data citation practices, the building blocks for open research data metrics.
Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS)
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Led by principal investigators Joseph Verbalis, MD, from Georgetown University and Thomas Mellman, MD, from Howard University, the mission of GHUCCTS is to advance research and training with excellence, innovation, collaboration, and efficiency while realizing the potential of the unique capacities of its constituent institutions for developing new technologies, promoting ethical clinical and translational research, and engaging the diverse populations of our communities that have been historically underrepresented in clinical research, including people from diverse racial, ethnic, and cultural backgrounds, people with disabilities, and older adults.
“One of the major missions of GHUCCTS has been to stimulate and support the growth of team science,” says Verbalis, a professor of medicine at Georgetown. “Advances in solving the complex and challenging health problems we face today can be achieved more quickly and efficiently by collaborations among investigators from different scientific disciplines working together on common problems.”
University of Michigan, Institute for Health Policy & Innovation
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As heart disease and stroke remain the leading causes of death worldwide, a new University of Michigan research initiative aims to investigate how mobile health (mHealth) technology, such as smartwatches and smartphones, can be used to study and improve health behaviors among hypertensive populations.
“Mobile technology has changed nearly all aspects of our lives. There is great hope that mHealth through smartphones and wearables could also transform how we practice clinical care and ultimately help people lead healthier lives. But a lot of the evidence for how this could or should happen remains unknown,” says Brahmajee Nallamothu, M.D., M.P.H., professor of cardiovascular medicine at U-M Medical School.
One of the sneakiest ways to spill the secrets of a computer system involves studying its pattern of power usage while it performs operations. That’s why researchers have begun developing ways to shield the power signatures of AI systems from prying eyes.
Among the AI systems most vulnerable to such attacks are machine learning algorithms that help smart home devices or smart cars automatically recognize different types of images or sounds such as words or music. Such algorithms consist of neural networks designed to run on specialized computer chips embedded directly within smart devices, instead of inside a cloud computing server located in a data center miles away.
This physical proximity enables such neural networks to quickly perform computations with minimal delay, but also makes it easy for hackers to reverse-engineer the chip’s inner workings using a method known as differential power analysis.
Although many doctors report that patients with COVID-19 are presenting with dangerously low blood oxygen levels, COVID-19 isn’t the only disease that can cause such a problem. Chronic lung diseases, like COPD, asthma and other non-COVID-19 lung infections can also result in a low oxygen count.
A low oxygen reading by itself is not enough to diagnose COVID-19, but your doctor would want to know about it, especially if you notice the level decreasing over time. And if you’ve been diagnosed with COVID-19, your doctor may want you to monitor your oxygen level to determine whether your condition is worsening or improving.
Big Data & Society journal; Aphra Kerr, Marguerite Barry, John D Kelleher
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This article draws on the sociology of expectations to examine the construction of expectations of ‘ethical AI’ and considers the implications of these expectations for communication governance. We first analyse a range of public documents to identify the key actors, mechanisms and issues which structure societal expectations around artificial intelligence (AI) and an emerging discourse on ethics. We then explore expectations of AI and ethics through a survey of members of the public. Finally, we discuss the implications of our findings for the role of AI in communication governance. We find that, despite societal expectations that we can design ethical AI, and public expectations that developers and governments should share responsibility for the outcomes of AI use, there is a significant divergence between these expectations and the ways in which AI technologies are currently used and governed in large scale communication systems. We conclude that discourses of ‘ethical AI’ are generically performative, but to become more effective we need to acknowledge the limitations of contemporary AI and the requirement for extensive human labour to meet the challenges of communication governance. An effective ethics of AI requires domain appropriate AI tools, updated professional practices, dignified places of work and robust regulatory and accountability frameworks.
In the short term, AI-enabled solutions that don’t require a big data strategy will begin to transform learning. The IDC study found that modernized learning and classrooms top the list of use cases for AI-enabled solutions over the next 12 to 18 months. Modernized learning refers to personalized learning enabled at scale, accessibility, and inclusion features for learners of all abilities, as well as AR/VR for blended learning. Modernized classrooms, likewise, refer to virtual workspaces and labs, as well as smart classrooms.
The top hurdles standing in the way of higher education goals that leverage AI include solution cost and lack of skills: 57 percent of institutions listed cost as the top challenge they face in adopting AI-enabled solutions today. Lack of skills, resources, and continuous learning came in second for employees. And nearly half of organizations said they’re planning to invest equally in developing AI solutions and closing the employee skills gap. The study also revealed a widespread lack of data strategy as well as gaps in data governance policies, quality, and availability. This indicates that many institutions need to better understand and plan for what is needed to support AI-enabled solutions in the long term.
“This new algorithm will need a lot of pictures of people. What if we use a morgue so we don’t have to worry about consent?” Although this is a fictitious example, modern-day tech workers often face similar questions.
Why? Because the rise of artificial intelligence based on machine learning has created a new class of sociotechnical challenges. Now is the time for industry and universities to acknowledge these new challenges and step up to meet them.
A team of graduate student researchers led by Stony Brook’s Andrew Schwartz, an assistant professor in the College of Engineering and Applied Science’s Department of Computer Science, and Stanford University’s Johannes Eichstaedt is using Twitter to track and analyze COVID-19 symptoms and mental health in U.S. communities. Large-scale analysis of linguistic patterns in social media offer one of the few (if not only) large-scale instruments for measuring the physical and psychological health of populations down to the county level, daily, across most of the country. The group also produces what seems to be the only county-level COVID time-tracker available.
PDF version
In 2018, psychiatrist Oleguer Plana-Ripoll was wrestling with a puzzling fact about mental disorders. He knew that many individuals have multiple conditions — anxiety and depression, say, or schizophrenia and bipolar disorder. He wanted to know how common it was to have more than one diagnosis, so he got his hands on a database containing the medical details of around 5.9 million Danish citizens.
He was taken aback by what he found. Every single mental disorder predisposed the patient to every other mental disorder — no matter how distinct the symptoms1. “We knew that comorbidity was important, but we didn’t expect to find associations for all pairs,” says Plana-Ripoll, who is based at Aarhus University in Denmark.
The study tackles a fundamental question that has bothered researchers for more than a century. What are the roots of mental illness?
In the hope of finding an answer, scientists have piled up an enormous amount of data over the past decade, through studies of genes, brain activity and neuroanatomy. They have found evidence that many of the same genes underlie seemingly distinct disorders, such as schizophrenia and autism, and that changes in the brain’s decision-making systems could be involved in many conditions.
Public schools play a range of roles in society beyond education. As child care for millions of working parents, they are a cornerstone of any attempt to reopen the economy. They are hubs for community relationships and distribution points for essential social services.
But, before any of that, they must be safe places for children. With those various functions in mind, education leaders are putting out plans that forecast some very big changes to what public school might look like in the coming months and even years.
The complications are leading to a patchwork effect and a disconnect between levels of government in many places.
Just a few hours ago the FDA greenlighted the first home-collected saliva sample for COVID-19. Rutgers Clinical Genomics Laboratory, which already landed an EUA in mid-April for its test, can now expand its efforts to include test kits for home collection.
Patients do so using a specially designed collection device. This sample is then sent off to the Rutgers Clinical Genomics Laboratory in a sealed package.
“Authorizing additional diagnostic tests with the option of at-home sample collection will continue to increase patient access to testing for COVID-19. This provides an additional option for the easy, safe and convenient collection of samples required for testing without traveling to a doctor’s office, hospital or testing site,” FDA Commissioner Dr. Stephen M. Hahn, said in a release.
Unemployment in May reached its highest levels since the Great Depression, but companies like Postmates and Uber have continued to hire new workers during the pandemic. If you’re interested in this kind of gig, however, there’s a good chance you’ll need to pass an AI-powered background check from a company like Checkr. This might not be as easy as it sounds.
Checkr is on the forefront of a new and potentially problematic kind of hiring, one that’s powered by still-emerging technology. Those hoping to quickly get extra work complain that Checkr and others using AI to do background checks aren’t addressing errors and mistakes on their criminal records reports. In these cases, a glitch in the system can cost someone a job.
Launched in the last week, the free app was designed by Oxford doctoral student Alex Barnes and his group in just three days. Using anonymised data, Crowdless allows users to see if their local supermarket is crowded – so you can check before you leave the house whether the queue goes round the block and, if so, go somewhere else.
Crowdless was created under the auspices of Lanterne, a UK-based social enterprise, led by Alex and a group of collaborators, including researchers and students from other UK institutions. One of the team, Sebastian Müller, says, ‘Lanterne has always been about helping people to stay safe, and the pandemic is arguably one of the biggest safety threats right now. Focusing on building something that helps people to cope with the current situation was therefore only logical.’
This is the largest study on COVID-19 conducted by any country to date, and therefore gives the strongest evidence on risk factors associated with COVID-19 death.
Compared to white people, people of Asian and Black ethnic origin were found to be at a higher risk of death. Previously, commentators and researchers have reasonably speculated that this might be due to higher prevalence of medical problems such as cardiovascular disease or diabetes among BME communities, or higher deprivation. The findings, based on detailed data, show that this only accounts for a small part of the excess risk. Consequently, further work must be done to fully understand why BME people are at such increased risk of death.
Additionally, people from deprived social backgrounds were also found to be at a higher risk of death, which also could not be explained by other risk factors.
A majority of Americans disapprove of protests against restrictions aimed at preventing the spread the coronavirus, according to a new poll that also finds the still-expansive support for such limits — including restaurant closures and stay-at-home orders — has dipped in recent weeks.
The new survey from the University of Chicago Divinity School and The Associated Press-NORC Center for Public Affairs Research finds 55% of Americans disapprove of the protests that have popped up in some states as some Americans begin chafing at public health measures that have decimated the global economy. Thirty-one percent approve of the demonstrations
The Great Smoky Mountains National Park that sprawls across 522,427 acres of North Carolina and Tennessee may seem like the perfect place to practice social distancing.
Yet visitors to its lush, mountainous terrain tend to congregate at well-known spots like Clingmans Dome, where they can stand at the highest point in Tennessee, or Grotto Falls, where they can walk behind a waterfall.
That tendency has park advocates and former employees worrying about its reopening last weekend — and the plan for other national parks to follow in coming weeks at the urging of President Donald Trump — even as coronavirus infections nationwide continue to climb.
“A lot of folks sort of casually say, ‘This is a 300,000-acre park. People can spread out,’” said Kristen Brengel, senior vice president of government affairs at the National Parks Conservation Association. “But we all want to see that arch, that waterfall, that historic site. We all want to see the best features in the parks. But so does everybody else.”
As a growing number of states ease stay-at-home restrictions imposed in response to the outbreak of the novel coronavirus, a majority of Americans (61%) say it is primarily the federal government’s responsibility to make sure there are enough COVID-19 tests in order to safely lift the restrictions.
Fewer (37%) say it is mainly the responsibility of state governments to ensure there is an adequate supply of tests.
Twitter CEO Jack Dorsey emailed employees on Tuesday telling them that they’d be allowed to work from home permanently, even after the coronavirus pandemic lockdown passes. Some jobs that require physical presence, such as maintaining servers, will still require employees to come in.
“We’ve been very thoughtful in how we’ve approached this from the time we were one of the first companies to move to a work-from-home model,” a Twitter spokesperson told BuzzFeed News. “We’ll continue to be, and we’ll continue to put the safety of our people and communities first.”
Yes! But hold on—data skills will be useful to public and school librarians as well. In a world of “big data”, “public data”, and “data science,” we’ve got a great chance to reach out and help people access, use, and share “data” about our world. In other words, data skills, like internet skills and book skills, will be handy for any librarian in the next few years.
In the vast majority of cases, COVID-19 is a respiratory infection that causes fever, aches, tiredness, sore throat, cough and, in more severe cases, shortness of breath and respiratory distress. Yet we now understand that COVID-19 can also infect cells outside of the respiratory tract and cause a wide range of symptoms from gastrointestinal disease (diarrhoea and nausea) to heart damage and blood clotting disorders. It appears that we have to add neurological symptoms to this list, too.
Several recent studies have identified the presence of neurological symptoms in COVID-19 cases. Some of these studies are case reports where symptoms are observed in individuals. Several reports have described COVID-19 patients suffering from Guillain–Barré syndrome. Guillain–Barré syndrome is a neurological disorder where the immune system responds to an infection and ends up mistakenly attacking nerve cells, resulting in muscle weakness and eventually paralysis.
First, I want to reiterate the point made so articulately by @nataliexdean
and @CT_Bergstrom
: Natural herd immunity is not a goal we should be striving for. Trying to reach the end of this pandemic via that path will lead to mass deaths. (2/)
But understanding heterogeneity in COVID-19 transmission is important as it’ll help to optimize social distancing and (eventually) vacc strategies. A recent thread by @mlipsitch
also discusses how heterogeneity may reduce herd immunity thresholds. (3/)
When Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, described the results of a remdesivir study a couple of weeks ago, he was cautious in characterizing how the experimental Gilead Sciences drug helped combat Covid-19.
Patients given the intravenous medicine recovered faster than those on a placebo by 31%, or four days, Fauci said, conceding the result was not a “knockout.” Nonetheless, he insisted in his trademark keep-it-simple-demeanor, that the data showed “remdesivir has a clear-cut, significant, positive effect…. This has proven that a drug can block this virus.”
By and large, this was good news, but there was a caveat — the data were based only on a preliminary analysis. Rather than release all the data, the National Institutes of Health, which sponsored the study, issued a press release saying a forthcoming report would have “more comprehensive data.”
The news: In its latest Community Standards Enforcement Report, released today, Facebook detailed the updates it has made to its AI systems for detecting hate speech and disinformation. The tech giant says 88.8% of all the hate speech it removed this quarter was detected by AI, up from 80.2% in the previous quarter. The AI can remove content automatically if the system has high confidence that it is hate speech, but most is still checked by a human being first.
Bloomberg; Mathieu Benhamou, Mira Rojanasakul and Allison McCartney
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Senator Richard Burr has called for an ethics investigation into himself and three other senators who sold off stock after receiving classified briefings on the coronavirus threat. … Here’s how well those stocks performed after he sold them.
An entire ecosystem of AI chip startups is already heading in that direction. Engineers and developers are looking at new, novel chip architectures capable of handling the unique demands of AI and its related technologies – both in data centers and the edge.
Bajic is the founder of one such company – Toronto-based Tenstorrent, which was founded in 2016 and emerged from stealth earlier this year. Tenstorrent’s goal is both simple and largely ambitious – creating chip hardware for AI capable of delivering the best all around performance in both the data center and the edge.
In a landmark acknowledgment of the toll that content moderation takes on its workforce, Facebook has agreed to pay $52 million to current and former moderators to compensate them for mental health issues developed on the job. In a preliminary settlement filed on Friday in San Mateo Superior Court, the social network agreed to pay damages to American moderators and provide more counseling to them while they work.
Each moderator will receive a minimum of $1,000 and will be eligible for additional compensation if they are diagnosed with post-traumatic stress disorder or related conditions. The settlement covers 11,250 moderators, and lawyers in the case believe that as many as half of them may be eligible for extra pay related to mental health issues associated with their time working for Facebook, including depression and addiction.
Most companies don’t have the personnel to do AI well, so they turn to platform vendors like Adobe for help. Like other platforms, it has been building AI into its product set for several years now, but wanted to give marketers a set of tools that take advantage of some advanced AI capabilities out of the box.
Today, the company announced five pre-packaged AI solutions specifically designed to give marketers more intelligent insight. Amit Ahuja, VP of ecosystem development at Adobe, says even before the pandemic, customers were struggling to deal with the onslaught of data and how they could use it to understand their customers better.
“There is so much data coming in, and customers are struggling to leverage this data — and not just for the purpose of analytics and insights, which is a huge part of it, but also to do predictive optimization,” Ahuja explained.
Universities do their best to develop and support various open source initiatives. Thus, there is the Open Source University Alliance, an initiative of the Erasmus Without Paper project. Their goal is to help all higher education institutions meet the latest demands of digital transformation.
The alliance is creating an open repository of source code and software so that the higher education community has access to multiple tools and services necessary for teaching and learning. Among HEIs that have already taken part in the initiative and shared open source solutions are the University of Porto, Aristotle University of Thessaloniki, University of Münster, and Ghent University.
University of Michigan, Public Engagement & Impact
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A University of Michigan startup is using advanced computer vision models and live public street cameras to track social distancing behaviors at some of the most-visited places in the world.
In this episode of Michigan Minds, Jason Corso, U-M professor of electrical and computer engineering and CEO of Voxel51, an Ann Arbor video analytics and data management company, discusses how Voxel51 is using custom AI to track how pedestrian and vehicle traffic is evolving amid stay-at-home orders in locations around the world. [video, 17:51]
Even before coronavirus, many workers hated the open-plan office. Now that shared work spaces are a public health risk, employers are rethinking office design.
After a person who attended an in-person religious service on Mother’s Day tested positive for the novel coronavirus, public health officials in Butte County issued a strongly worded warning to residents not to speed too quickly through the reopening process.
The person received a positive test result the day after the service, which had more than 180 attendees, officials said Friday in a news release.
Gatherings of any size remain prohibited, even in counties that are reopening more quickly than the rest of California. But the organization that held the service chose to open its doors despite the rules, exposing the entire congregation to the coronavirus, officials said.
American higher education was in crisis long before the coronavirus showed up at our doors. For what feels like an eternity, our sector has been criticized for being too slow to respond to changing realities. Student debt in the United States totals more than $1.5 trillion. Alternative credential providers are nipping at the heels of degree-granting schools. Unfavorable demographic trends suggest that the number of college students will decline. In this environment, we face fair questions about higher education’s business model, cost, and long-term prospects—and about whom higher education ultimately serves. Do we serve the students and families who appear at our doors each fall full of hope and faith? Or does self-preservation come first?
Last summer we announced that we were going to begin two new collaborative projects on data, one focused on teaching, and one on research. While we couldn’t have anticipated then the conditions we are facing now, we believe the research is more important than ever. The first project will examine instructors’ support needs teaching with data in the social sciences, while the second project will study the support needs of researchers who work with big data. We are excited to share that both projects will launch this month in partnership with 37 research libraries
Working with and understanding research data is emerging as a major issue during the pandemic. It is critical for researchers to share data to map the progression of the disease, to develop best practices for treating patients, and find a vaccine. At the same time, the public at large is confronted daily with data visualizations that they may not comprehend and misinformation is proliferating. Data was growing in importance as a topic for the higher education sector for several years, but its importance is now critical.
On May 10, just a few days before Advanced Placement tests were scheduled to begin for high-schoolers around the world, a Reddit user, Dinosauce313, created a new subreddit, APTests2020. Its stated purpose? “A community of students taking the 2020 AP Exams and wanting to use online resources while doing so.” As a result of coronavirus, all AP testing has moved online this year. Students are taking modified, shorter versions of the traditional tests, and this year’s iterations are open-book. Using class notes, or even Googling during the test, is kosher. The College Board, the organization that administers the exams, says wasting time doing so will not ultimately be beneficial given the way the truncated tests are written. What is not kosher, however, is conferring with another person during the exam. So Dinosauce313’s proposed efforts would be grounds for consequences, should any students get caught participating in a collective testing scheme.
Some things about Dinosauce313 didn’t strike other Redditors, namely real high-schoolers preparing for their exams, quite right. The account was created at the beginning of April, just a few weeks before the subreddit’s debut, and spoke in a lexicon that read more how do you do, fellow kids than, well, “How do you do, fellow kids.” On several social platforms, a theory began brewing: Dinosauce313 was actually a College Board employee setting a honey trap to catch would-be cheaters and disqualify them.
Late last Friday, the architect and manager of Florida’s COVID-19 dashboard — praised by White House officials for its accessibility — announced that she had been removed from her post, causing outcry from independent researchers now worried about government censorship.
The dashboard has been a one-stop shop for researchers, the media and the public to access and download tables of COVID-19 cases, testing and death data to analyze freely. It had been widely hailed as a shining example of transparency and accessibility.
But over the last few weeks it had “crashed” and gone offline; data has gone missing without explanation and access to the underlying data sheets has become increasingly difficult.
A Carnegie Mellon University student has sued the school in federal court and is seeking a refund for tuition and fees for the spring semester, saying CMU’s online instruction isn’t an adequate substitute for the real thing.
The suit, brought by undergraduate student Abigale Pfingsten, is seeking class-action status on behalf of all students like her affected by the shutdown of the campus in response to the coronavirus pandemic.
University of California-Los Angeles, UCLA Samueli School Of Engineering
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A machine-learning model developed at the UCLA Samueli School of Engineering is helping the Centers for Disease Control and Prevention predict the spread of COVID-19.
The model was created by a team led by Quanquan Gu, a UCLA assistant professor of computer science, and it is now one of 13 models that feed into a COVID-19 Forecast Hub at the University of Massachusetts Amherst. Data from that hub, in turn, feeds into the CDC’s online forecasts for how the disease might continue to spread.
Gu said his model is more accurate than most others because it does not rely only on confirmed COVID-19 cases and fatalities. It is epidemiology-driven and is one of only two models in the hub that use machine learning.
The best way to stop a pandemic is to never let it start. The majority of infectious diseases, including those responsible for pandemics, started out as animal pathogens. Generally speaking, these diseases don’t spring from wild animal populations to humans, either. They evolve from pathogens impacting domesticated animals: the avian flu from poultry; MERS likely from camels; swine flu, from, well, swine. There’s less consensus about the actual origin of the 1918 Spanish flu pandemic, but everyone agrees it was cross-species transmission, whether birds, swine, or horses were the culprit. But, according to James Spencer, who studies city planning at Clemson University and has conducted research on avian influenza, it’s not viruses that jump hosts in purely rural areas that go on to become pandemics. “If we want to prevent these things,” he says. “We have to do a better job of managing the extremely rapid changes going on where agriculture and urbanization are happening in the same space.”
Mike Webster normally would be trekking around the wilds of New England by now, searching for flashes of blue and white among the trees.
Each spring, he travels to the Hubbard Brook Experimental Forest in New Hampshire’s White Mountains to study the black-throated blue warbler — a tiny migratory songbird that splits its time between the Caribbean and eastern North America.
An ornithologist at Cornell University, Webster is part of a long-term study that’s kept tabs on the birds for decades. Webster joined in the 1990s, but the study has been ongoing since the mid-1980s.
Contact tracing is a proven tool in containing outbreaks of highly infectious diseases. But this particular virus could pose significant challenges to tracing programs in the US, based on new studies and emerging evidence from initial efforts. Stubbornly high new infection levels in some areas, the continued shortage of tests, and American attitudes toward privacy could all hamstring the effectiveness of such programs.
All Maddie Bender knew when she called the New Haven, Conn., family was that a child had tested positive for Covid-19. Anyone who lived with the child was at risk of catching the new virus, and Bender needed to find out if they had symptoms, if new cases were taking root. What she learned was that public health work during a pandemic is four parts shoe leather and intuition, one part empathy.
On the phone, the child’s mother complained she was breathing in short, sharp gasps. The woman had thought about seeking help at an emergency room, but heard on TV that “it was so bad at the hospitals.” In a state where the governor has repeatedly urged residents to stay home, the woman had the impression she shouldn’t go to an ER.
Bender, a Yale University graduate and public health master’s student, tried to stick with the script she’d been given by the New Haven Health Department. “But I felt this woman should have called her doctor. She hadn’t had a physical in three years,” Bender recounted. She told the woman she needed to self-quarantine for 14 days, but altered the line about contacting a physician first before getting urgent care. “It is OK to go to the emergency room if you need to go,” she said.
Yesterday, US biotech firm Moderna revealed the first data from a human trial: its COVID-19 vaccine triggered an immune response in people, and protected mice from lung infections of the SARS-CoV-2 coronavirus. The results — announced in a press release by the Cambridge, Massachusetts-based firm — were widely interpreted as positive and sent stock markets surging. But some scientists say that because the data aren’t published, they lack the details needed to properly evaluate those claims.
Entrepreneur First (EF), the London-headquartered “talent investor” that backs individuals pre-team and pre-idea to enable them to found startups, has appointed former Andreessen Horowitz partner Benedict Evans as a Venture Partner.
A well-respected analyst with a background in the tech and media industries, Evans will be tasked with providing “analysis, insight and recommendations” for new technologies and markets that offer opportunities for the EF company builder model and to support future EF cohorts.
This will include acting as an advisor to EF’s global portfolio, and supporting the current and upcoming cohorts at Investment Committee. Additionally, I’m told he’ll be working with EF’s Executive Committee on “strategy and portfolio composition direction” (whatever that means!).
There are two main findings that highlight the pitfalls of current evaluation trends for human+AI teams:
Results of human+AI team performance on proxy evaluation tasks, such as how well people simulate an AI’s decision, do not predict performance of a human+AI team on actual tasks.
Subjective evaluation measures, e.g., humans’ rating of trust in an AI, do not predict their performance as a human+AI team on actual tasks.
1st, collider bias is unintuitive. A collider is a variable that is influenced by two other variables of interest. Kinda the opposite of a confounder. While we want to adjust for a confounder (to break the induced association btw variables), we don’t want to adjust for a collider
On the face of it this seems easy to deal with: don’t condition on a collider in model = problem solved.
Sadly, it’s not as easy as this. The act of using a dataset can induce collider bias if the variables of interest influence being in the dataset. Confused?
Just as the Sept. 11 attacks irrevocably shrank personal freedoms as security-at-all-costs became a policy driver, Covid-19 will erode privacy in the name of public health. The potential market is immense for instruments far more intrusive than Big Brother’s telescreens. Richard Brooks, a computer engineering professor at Clemson University in South Carolina, told Bloomberg News: “If the ability to track social contacts exists to stop a contagion, I can guarantee you it will be used to track the spread of dissent.”
An Israeli court verdict that banned Shin Bet, the internal security agency, from using its Covid-19 tracking app shows the discomfort societies have with handing over a shiny, new lever of control to governments. Europe’s data protection laws will try to ensure that the emergency collection and processing of personal information is conducted with accountability, and for a limited purpose.
The Atlantic, Alexis C. Madrigal and Robinson Meyer
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The government’s disease-fighting agency is conflating viral and antibody tests, compromising a few crucial metrics that governors depend on to reopen their economies. Pennsylvania, Georgia, Texas, and other states are doing the same.
Twitter is testing a way to let you limit how many people can reply to your tweets. If you’re part of the test, when you compose a tweet, you’ll be able to select if you’ll allow replies from everyone, people you follow, or only people you @ mention. Twitter said in January that this feature would be coming to the platform sometime this year.
The website iFixit has long been known for its electronics repair kits and for its very public stance that repair manuals should be accessible to everyone. That’s one of the foundational arguments of the broader right-to-repair movement, which lobbies that regular consumers should be able to repair the products they’ve purchased—everything from smartphones to washing machines to farming equipment—without violating a warranty. Now, in the time of Covid-19, iFixit and a prominent consumer interest group are tackling a more immediate concern: access to repair manuals for medical devices.
The company said today it’s releasing what it calls the “most comprehensive medical equipment service database in the world.” The collection of thousands of files is supposed to help biomedical engineering technicians—the techs who update or fix medical equipment on site at health care facilities—repair everything from imaging equipment to EKG monitors to ventilators. iFixit founder and CEO Kyle Wiens (who also contributes to WIRED’s Ideas section) called it an “absolutely massive” undertaking for iFixit, a project that took more than two months to coordinate and required help from 200 volunteers.
In the early weeks of the US coronavirus outbreak, staff members in the U.S. Centers for Disease Control and Prevention had tracked a growing number of transmissions in Europe and elsewhere, and proposed a global advisory that would alert flyers to the dangers of air travel.
But about a week passed before the alert was issued publicly — crucial time lost when about 66,000 European travelers were streaming into American airports every day.
The delay, detailed in documents obtained by CNN, is the latest example to emerge of a growing sense of disconnect between the CDC and the White House.
A number of commercially available COVID-19 antibody tests, which look at a patient’s blood for signs of past infection, did not pass Mayo Clinic quality screening or meet their expectations for use, researchers from the hospital concluded in a joint investigation by the clinic and ABC News.
One rapid finger-prick test even wrongly displayed a positive result for antibodies after researchers decided to use a saline-like solution, instead of a blood sample, to see what happened. An automatic fail, doctors said.
Nick Bryner, a high school senior in Los Angeles, had just completed his AP English Literature and Composition test last week. But when he snapped a photo of a written answer with his iPhone and attempted to upload it to the testing portal, it stopped responding.
The website got stuck on the loading screen until Bryner’s time ran out. Bryner failed the test. He’s retaking it in a few weeks.
Bryner is among the many high school students around the country who completed Advanced Placement tests online last week but were unable to submit them at the end. The culprit: image formats.
University of California-Berkeley, Berkeley Public Health
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The initiative will test thousands of students, staff and faculty to determine the best methods to prevent and control the ongoing transmission of COVID-19.
University of Michigan, Public Engagement & Impact
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Are people still worried about getting COVID-19? How long will we need to continue social distancing? Will people accept a COVID-19 vaccine when one becomes available? One researcher at the University of Michigan is answering these questions by identifying perceptions of countermeasures to COVID-19 and how they are changing over time.
In this episode of Michigan Minds, Abram Wagner, research assistant professor of epidemiology at the School of Public Health, discusses his ongoing research examining how changes in the epidemiology of COVID-19 affects behaviors. [audio, 8:30]
The Guardian; Lydia McMullan, Garry Blight, Pablo Gutiérrez and Cath Levett
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Infectious diseases have wreaked havoc on human communities since ancient times.
From smashed crockery in ancient Syria to attacks on doctors in 1830s Britain, there are many documented examples of the despair and chaos experienced by those who lived through pandemics.
Our journey through the ages looks at the spread of disease in three case studies, and then explores a historical view on how we think about pandemics today.
States are to greater or lesser extents and with more less clear plans, exiting ‘lockdowns’ designed to prevent spread of the virus. Experts are predicting dire consequences. It’s probably a little more complicated than that. Lemme explain. 1/n
In simple models the transmission parameter has two components: the number of contacts, and the chance of transmission if a contact is made. A ‘lockdown’ reduces the first of these, but it’s a pretty blunt instrument with dire economic consequences 2/n
ACM has named Noga Alon of Princeton University and Tel Aviv University; Phillip Gibbons of Carnegie Mellon University; Yossi Matias of Google and Tel Aviv University; and Mario Szegedy of Rutgers University recipients of the ACM Paris Kanellakis Theory and Practice Award for seminal work on the foundations of streaming algorithms and their application to large-scale data analytics.
Alon, Gibbons, Matias and Szegedy pioneered a framework for algorithmic treatment of streaming massive datasets. Today, their sketching and streaming algorithms remain the core approach for streaming big data and constitute an entire subarea of the field of algorithms. Additionally, the concepts of sketches and synopses that they introduced are now routinely used in a variety of data analysis tasks in databases, network monitoring, usage analytics in internet products, natural language processing and machine learning.
As developers are increasingly tasked to learn how to build AI models, they regularly have to ask themselves whether the systems are “easy to explain” and that they “comply with non-discrimination and privacy regulations,” Microsoft notes in today’s announcement. But to do that, they need tools that help them better interpret their models’ results. One of those is interpretML, which Microsoft launched a while ago, but also the Fairlearn toolkit, which can be used to assess the fairness of ML models, and which is currently available as an open-source tool and which will be built into Azure Machine Learning next month.
As for differential privacy, which makes it possible to get insights from private data while still protecting private information, Microsoft today announced WhiteNoise, a new open-source toolkit that’s available both on GitHub and through Azure Machine Learning. WhiteNoise is the result of a partnership between Microsoft and Harvard’s Institute for Quantitative Social Science.
As California and the American West head into fire season amid the coronavirus pandemic, scientists are harnessing artificial intelligence and new satellite data to help predict blazes across the region.
Anticipating where a fire is likely to ignite and how it might spread requires information about how much burnable plant material exists on the landscape and its dryness. Yet this information is surprisingly difficult to gather at the scale and speed necessary to aid wildfire management.
Now, a team of experts in hydrology, remote sensing and environmental engineering have developed a deep-learning model that maps fuel moisture levels in fine detail across 12 western states, from Colorado, Montana, Texas and Wyoming to the Pacific Coast.
Princeton University, The Daily Princetonian student newspaper, Marie-Rose Sheinerman and Zachary Shevin
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The University’s Department of Sociology will not accept graduate school applications during the 2021 admissions cycle, according to an announcement on the department’s website.
“The decision to eliminate a cohort of future students was not an easy one, but we have decided that our priority during these unsettled times is to take care of those who are already matriculated in the department,” the announcement states. “We look forward to reading applications again in the fall of 2021 for the 2022 cohort.”
Leading coronavirus expert Dr. Anthony Fauci delivered precautionary advice to colleges that plan on bringing their athletes back to campus as soon as June 1. The first step, unsurprisingly, consists of testing.
Fauci, the director of the National Institute of Allergy and Infectious Diseases, spoke with the Chronicle of Higher Education on Friday about the strategies universities should be using in bringing students back to campus. It was the same day the NCAA announced that athletes in all sports could return for voluntary workouts starting June 1.
Based on data that’s emerged in the intervening months, I no longer believe that a direct WA1 introduction is a likely hypothesis for the origin of the Washington State outbreak. 2/18
The war on coronavirus demands the best of our science and scientists, and premier research universities across America and around the world have answered the call, Rutgers’ President Robert Barchi says.
On this somber Memorial Day weekend, America is approaching the grim milestone of 100,000 Covid-19 deaths in a population of 330 million. Six Asia-Pacific nations — Australia, Japan, Korea, New Zealand, Taiwan and Vietnam — have just over 1,200 coronavirus deaths in a combined population almost the same as the US, 328 million. On May 23, the Johns Hopkins coronavirus tracker shows that America recorded 1,208 new deaths, while the six Asia-Pacific countries recorded just 13 deaths: 12 in Japan, 1 in Australia, and 0 in the others.
America has failed to control the epidemic while many other countries, and not just the six in the Asia-Pacific, have succeeded.
The American political system has not been focused on how to end the epidemic. Our political debates from the first days of the epidemic have taken the bait of Donald Trump’s nonsensical Twitter feed: chloroquine, Clorox, China pro and con, WHO pro and con, filling church pews by Easter, the liberation of states, the bailout of the post office, the loyalty of Fox News, and whether or not to wear a face mask at the Ford Motor plant. This is not the politics of problem solving; it is the politics of distraction.
Undark published a story about the controversy late last month. Ioannidis did not respond to multiple requests for comment before publication. But, less than an hour after the story went up, he sent me a warm note expressing appreciation for the scientists who had criticized him. We arranged a time to talk.
A few weeks later, the team released a revised version of the paper. The new draft, which, like the original version, has not yet received formal peer review, softens some of the more controversial claims, and acknowledges more uncertainty about the true number of infections.
The following interview — which covers the papers as well as Ioannidis’ appearances on partisan television — has been edited for length and clarity.
I left my engineering career to pursue a doctoral degree at the intersection of behavioral science and engineering. And it wasn’t until I read a new book, which investigates how buildings affect public health, that it clicked. Healthy Buildings argues that the job of engineers, designers, and developers is to create buildings where health is the top priority.
I reached out to one of the book’s co-authors, Joseph Allen, a professor of public health at Harvard University, to learn more. In our conversation, we discussed what makes a building healthy, how our indoor environment impacts our mental and physical health, and what it might mean to reframe the building industry as a healthcare service. We also touched on the advice he would give to real-estate investors and professionals who want to create healthy buildings. Our conversation has been edited for length and clarity.
This post reviews some successful visioning in computer architecture and related fields. It argues why visioning is necessary for our field to flourish and discusses how the Computing Community Consortium (CCC) has facilitated some of this. Visioning is especially critical now as disruptions arrive from many quarters.
There is a devastating cost associated with the current chaotic and uncoordinated reopening of states and cities across the US and the globe after the COVID-19 shutdown because “pandemics are interdependent phenomena,” a new study shows. “Viruses and people’s adherence to the government policies designed to contain them spill over from region to region,” according to the study by the Social Analytics Lab at the MIT Initiative on the Digital Economy.
This means the welfare of states is “reduced dramatically when reopening is not coordinated,” the study said.
medRXiv; Mihaela Curmei, Andrew Ilyas, Owain Evans, Jacob Steinhardt
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Introduction and Goals: SARS-CoV-2 is transmitted both in the community and within households. Social distancing and lockdowns reduce community transmission but do not directly address household transmission. We provide quantitative measures of household transmission based on empirical data, and estimate the contribution of households to overall spread. We highlight policy implications from our analysis of household transmission, and more generally, of changes in contact patterns under social distancing. Methods: We investigate the household secondary attack rate (SAR) for SARS-CoV-2, as well as R_h, which is the average number of within-household infections caused by a single index case. We estimate the SAR through a meta-analysis of previous studies. Taking a Bayesian approach, we correct estimates for the false-negative rate (FNR) of testing and compute posterior credible intervals for SAR. We estimate R_h using results from population testing in Vo’, Italy and contact tracing data that we curate from Singapore. The code and data behind our analysis are publicly available at: https://github.com/andrewilyas/covid-household-transmission. Results: Our analysis of eight recent attack rate studies yields an SAR estimate of 0.28 (0.10, 0.61). From contact tracing data, we infer an R_h value of 0.32 (0.22, 0.42). Blanket testing data from Vo’ yields an R_h estimate of 0.37 (0.34, 040) and a CRI estimate of 0.5 after correcting for FNR and asymptomatic cases. Interpretation: Our estimates of R_h suggest that household transmission was a small fraction (5%-35%) of R before social distancing but a large fraction after (30%-55%). This suggests that household transmission may be an effective target for interventions. A remaining uncertainty is whether household infections actually contribute to further community transmission or are contained within households. This can be estimated given high-quality contact tracing data. More broadly, our study points to emerging contact patterns (i.e., increased time at home relative to the community) playing a role in transmission of SARS-CoV-2. We briefly highlight another instance of this phenomenon (differences in contact between essential workers and the rest of the population), provide coarse estimates of its effect on transmission, and discuss how future data could enable a more reliable estimate.
We are all caregivers now. The COVID-19 pandemic has touched and continues to re-shape our daily lives. One reality that the coronavirus era has revealed is that caregiving is a daily life-flow for everyone around the world. In the U.S., this has particularly acute impacts — physical, emotional, and financial.
The 2020 AARP report on caregiving was published this month, and the survey research into caregivers uncovered fresh insights about caregivers’ demographics, financial stressors, and intensity of tasks both in volume and time. In addition, more caregivers are looking for and turning to technology to help them hack effort, time and tasks as caregiving commitments grow both for physical needs and financial.
Reservations used to be, um… reserved …for special occasions. If you wanted to nosh at that buzzy restaurant with the Michelin star, appointment dining might have been your only option.
But now that more businesses are reopening, you’ll start seeing appointment-driven everything: reservation shopping, reservation hiking, even reservation auto safaris.
And Modern Retail says reservation platforms are expanding their services to help businesses control who gets in when.
GZERO Media; Gabriella Turrisi , Gabrielle Debinski and Ari Winkleman
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The United States reached a grim milestone Wednesday, surpassing 100,000 deaths from the coronavirus in just twelve weeks. It’s the highest death toll in the world – and by a big margin. But Americans are not united by grief. In fact, they are more divided than ever. Polls show that Democrats overwhelmingly support stay-at-home orders, anxious to contain the virus’ spread, while Republicans are more likely to be concerned with the economic impact of lockdowns and want to get back to work, regardless of the public health toll. Here’s a look at how the pandemic, and the measures to contain it, have affected each state to date.
Vuzix® Corporation (NASDAQ: VUZI), (“Vuzix” or, the “Company”), a leading supplier of Smart Glasses and Augmented Reality (AR) technology and products, today announced that TensorMark, a US cloud-based AI and computer vision technology company, will include the Vuzix Blade Smart Glasses as a part of the options to venues in its strategic initiative to make returning to work, restaurants, and entertainment safer.
The combined solution of TensorMark’s patent-pending technology and the Vuzix Blade Smart Glasses will enable employers, retail venues, sports arenas, and concert venues to validate in real-time a person’s recent test results for the COVID-19 virus directly to the Vuzix Blade display. Only permission-based consumer information will be included in compliance with applicable guidelines and privacy laws, including HIPAA.
A team of engineers have trained a robot to prepare an omelette, all the way from cracking the eggs to plating the finished dish, and refined the ‘chef’s’ culinary skills to produce a reliable dish that actually tastes good.
The researchers, from the University of Cambridge in collaboration with domestic appliance company Beko, used machine learning to train the robot to account for highly subjective matters of taste. The results are reported in the journal IEEE Robotics and Automation Letters, and will be available online as part of the virtual IEEE International Conference on Robotics and Automation (ICRA 2020).
The California research outfit OpenAI is back with another gigantic deep learning model, GPT-3. While it shows that bigger can be better in natural language processing, it also points to a potential absolute limit on the whole practice of language modeling.
Beginning in fall 2020, the University of Maine at Machias will be the only public university in Maine to offer a four-year degree program in geographic information systems (GIS).
The bachelor’s degree in environmental geographic information science replaces UMM’s major in environmental studies.
The Pervasive Technology Institute at Indiana University has been awarded a $10 million grant from the National Science Foundation to deploy Jetstream 2, a distributed cloud computing system to support on-demand research, artificial intelligence, and enhanced large-scale data analyses for the nation.
Jetstream 2’s signature innovation is its ability to make high-performance computing and software easy to use by researchers who have limited experience with supercomputing systems. This is especially helpful for smaller academic communities with little previous access to such resources. IU is expected to receive nearly $20 million in total from the NSF to create, implement, and operate Jetstream 2 over five years.
The use of artificial intelligence and machine learning is now widespread with wide-ranging practical applications in many Earth science domains, including climate modeling, weather prediction, and volcanic eruption forecasting. This current revolution in computing has been driven largely by rapid improvements in computer software and algorithms.
But now, we’re approaching a second computing revolution of redesigning our hardware to meet new computing challenges, said Jean Anne Incorvia, a professor of electrical and computer engineering at the University of Texas at Austin.
Traditional silicon-based computer hardware (like the computer chips found in your laptop or cell phone) has bottlenecks in both speed and energy efficiency, which may impose limits on their use in increasingly intensive computational problems.
To break these limitations, some engineers are drawing inspiration from biological neural systems using an approach called neuromorphic computing. “We know that the brain is really energy efficient at doing things like recognizing images,” said Incorvia. This is because the brain, unlike traditional computers, processes information in parallel, with neurons (the brain’s computational units) interacting with one another.
On its face, it was a major finding: Antimalarial drugs touted by the White House as possible COVID-19 treatments looked to be not just ineffective, but downright deadly. A study published on 22 May in The Lancet used hospital records procured by a little-known data analytics company called Surgisphere to conclude that coronavirus patients taking chloroquine or hydroxychloroquine were more likely to show an irregular heart rhythm—a known side effect thought to be rare—and were more likely to die in the hospital.
Within days, some large randomized trials of the drugs—the type that might prove or disprove the retrospective study’s analysis—screeched to a halt. Solidarity, the World Health Organization’s (WHO’s) megatrial of potential COVID-19 treatments, paused recruitment into its hydroxychloroquine arm, for example.
But just as quickly, the Lancet results have begun to unravel—and Surgisphere, which provided patient data for two other high-profile COVID-19 papers, has come under withering online scrutiny from researchers and amateur sleuths.
Harvard Health Publishing, Harvard Health Blog, Robert H. Shmerling, MD
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Generally, contact tracing means locating and testing people known to have been in close contact with a sick person, to prevent an illness like COVID-19 from spreading to an ever-widening circle of people. This strategy works best when case numbers are low — not high or rising fast, as they did in hot spots like New York and California in late March and early April. After the peak passes, contract tracing is feasible. It’s proven effective in countries such as Germany, China, and South Korea.
Just how can we make contact tracing work in the US? Public health authorities are trying to figure that out, even as cities and towns recruit people to train as contact tracers. In some places, contact tracers are volunteers; others are paid. And they have a variety of backgrounds, including public health workers, retired healthcare professionals, furloughed hospitality workers, and students. Being able to speak the language and understand the culture of those who will be called are major advantages. So is a healthy amount of empathy.
Personal styling company Stitch Fix, a company that uses machine learning to help consumers find clothes they like, is apparently taking a bold approach to company expansion: it’s “significantly reducing” the number of employees it has so that it can hire people in other states.
The Health Foundation; Tim Elwell-Sutton, Sarah Deeny, Mai Stafford
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As countries around the world struggle to contain coronavirus (COVID-19), there is growing recognition that rather than being a great leveller, the pandemic may exacerbate existing inequalities (see also the recent Health Foundation long read on inequalities). Understanding is advancing very rapidly as researchers publish new studies every week.
This article sets out some of the key points emerging from recent research on COVID-19 and health inequalities. It reviews the evidence that black and minority ethnic communities are at greater risk of catching and dying from the virus. It also considers the reasons why these groups are at greater risk. The economic impacts of the pandemic on black and minority ethnic groups are not covered.
An artificial intelligence firm hired to work on the Vote Leave campaign may analyse social media data, utility bills and credit rating scores as part of a £400,000 contract to help the government deal with the coronavirus pandemic.
The company, Faculty, was awarded the contract by the Ministry of Housing, Communities and Local Government last month. However the full details of its work for the government are unknown because the published version of the contract was partly redacted.
The disclosure comes amid questions from civil liberties groups as to how private companies hired by the government during the pandemic are using confidential data.
Dozens of journalists have been sacked after Microsoft decided to replace them with artificial intelligence software.
Staff who maintain the news homepages on Microsoft’s MSN website and its Edge browser – used by millions of Britons every day – have been told that they will be no longer be required because robots can now do their jobs.
Around 27 individuals employed by PA Media – formerly the Press Association – were told on Thursday that they would lose their jobs in a month’s time after Microsoft decided to stop employing humans to select, edit and curate news articles on its homepages.
The group behind CES plans to hold the enormous tech convention in person in Las Vegas next January, despite concerns that the coronavirus pandemic may still be a threat. The Consumer Technology Association has announced that it intends to give exhibitors a way to showcase their products “both physically in Las Vegas and digitally.”
The stakes are high for CES. It’s one of the largest conventions held each year in Las Vegas, responsible for bringing a huge number of visitors to the city, with around 175,000 attendees last year. The Las Vegas Convention Center, the primary venue where the event is held, is scheduled to complete a $980 million expansion just in time for next year’s show. And while consumers may know CES as the event where new TVs, cars, and other gadgets are announced, it also remains an important venue for meetings between retailers, manufacturers, and all the companies in between.
A new mobile app can help clinicians determine which patients with the novel coronavirus (COVID-19) are likely to have severe cases. Created by researchers at NYU College of Dentistry, the app uses artificial intelligence (AI) to assess risk factors and key biomarkers from blood tests, producing a COVID-19 “severity score.”
Current diagnostic tests for COVID-19 detect viral RNA to determine whether someone does or does not have the virus—but they do not provide clues as to how sick a COVID-positive patient may become.
“Identifying and monitoring those at risk for severe cases could help hospitals prioritize care and allocate resources like ICU beds and ventilators. Likewise, knowing who is at low risk for complications could help reduce hospital admissions while these patients are safely managed at home,” said John T. McDevitt, PhD, professor of biomaterials at NYU College of Dentistry and professor of chemical and molecular engineering at NYU Tandon School of Engineering, who led the research.
PR Newswired, York University School of Continuing Studies
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The York University School of Continuing Studies has launched Canada’s first university continuing education Certificate in People Analytics, with classes beginning completely online this September. The School is offering this program during a critical time for organizations and their human resources departments, as the COVID-19 pandemic has created many workforce and business challenges.
Thanks to a motivated staff member and some LinkedIn connections, Cardinal Peak connected with Columbia University. The school was developing a research tool for collecting and distributing data related to Covid-19 and needed help in developing an Android solution. … Cardinal Peak, a Lafayette-based full-service engineering firm specializing in hardware, embedded software, cloud and mobile product development, donated engineering services to Columbia University to support the school’s effort to develop CovidWatcher, a research tool for collecting and distributing Covid-19 outbreak data.
Open Humans is a community of close to 9000 members who perform ‘self-research’ by sharing personal data for analysis by the community. While some of the data shared by participants is genetic information, one of the most recent projects, Quantified Flu, relies on data uploaded from participant wearables, such as smartwatches.
The project’s genesis was in a community call with participants who were already collecting, sharing and analysing their personal data. In response to the global pandemic, they felt motivated to do something with that data.
‘Basically, people were like, what we are doing right now seems a bit pointless,’ says Bastian Greshake Tzovaras, director of research at the Open Humans Foundation and a fellow at the Centre for Research and Interdisciplinarity in Paris, France.
With the growing cost of research equipment and a trend toward larger, more fluid interdisciplinary teams, the university’s Long-Range Vision calls for an expansion of shared resources and facilities to enable research of the future, including equipment shared amongst diverse groups, expertise to support new research directions and funding for faculty creating new platforms.
Stanford Vice Provost and Dean of Research Kathryn Moler described this model as similar to a library, where anyone can check out what they need to enable research.
“Imagine if all faculty members and students had the resources they need to share the latest data sets, methods and instruments,” Moler said. “People have called it an increased democratization of access to resources.”
Over the past 200 years, the population of the United States grew more than 40-fold. The resulting development of the built environment has had a profound impact on the regional economic, demographic, and environmental structure of North America. Unfortunately, constraints on data availability limit opportunities to study long-term development patterns and how population growth relates to land-use change. Using hundreds of millions of property records, we undertake the finest-resolution analysis to date, in space and time, of urbanization patterns from 1810 to 2015. Temporally consistent metrics reveal distinct long-term urban development patterns characterizing processes such as settlement expansion and densification at fine granularity. Furthermore, we demonstrate that these settlement measures are robust proxies for population throughout the record and thus potential surrogates for estimating population changes at fine scales. These new insights and data vastly expand opportunities to study land use, population change, and urbanization over the past two centuries.
As backtracks go, this one should go a little further.
The Centers for Disease Control is no longer recommending that employers incentivize their workers to commute by car alone as businesses reopen during the COVID-19 pandemic, but the agency’s revised guidelines still don’t do enough to protect workers from the novel coronavirus — or the myriad public health threats posed by our unsafe transportation network.
African American women under age 35 have rates of breast cancer two times higher than caucasian women under age 35.
African Americans under age 35 die from breast cancer three times as often as caucasian women of the same age.
Researchers believe that access to healthcare and the quality of healthcare available may explain these disparities. But scientists continue to investigate.
Google surreptitiously amasses billions of bits of information –every day — about internet users even if they opt out of sharing their information, three consumers alleged in a proposed class action lawsuit.
“Google tracks and collects consumer browsing history and other web activity data no matter what safeguards consumers undertake to protect their data privacy,” according to the complaint filed Tuesday in federal court in San Jose, California.
The lawsuit argues that while Google lets users turn off data collection when using its Chrome web browser, other Google tools used by websites themselves scoop up their data anyways. The suit includes claims for invasion of privacy and violations of federal wiretapping law.
Colleges and universities sent students home in March and are grappling with when it will be safe to bring them back for classes. Hotels, which have emptied out during the pandemic, are emerging as an option for schools that need more space to allow social-distancing.
Northeastern University has secured an additional 2,000 beds in hotels and apartments near its Boston campus to reduce density in its residence halls, according to Michael Armini, a spokesman for the school.
It’s easy to look around right now and conclude that popular public opinion has turned against scientists. Twitter hashtags have urged the president to fire Anthony Fauci. A widely shared video claimed government scientists planned the novel coronavirus pandemic. Politicians have waded in as well: “Frustration … stems from this idea that you people don’t know what’s best for you, and we’re just going to bring in these Harvard-educated Ivy League public health experts, and they’re going to know better than you and better than your family,” said Michigan state Rep. Beau LaFave while explaining the anti-lockdown protests in his state.
But survey data suggests public trust in scientists is not actually eroding. In fact, it’s gone up during the pandemic. And while that may be surprising to people watching with concern as anti-vaccine extremists join forces with people who don’t want to wear facemasks, the dichotomy between a perceived anti-science zeitgeist and what people actually tell pollsters is nothing new. The scientific and medical communities remain among the most trusted institutions in America — even among people who might seem ideologically primed to reject them. “I do think there’s maybe a lack of trust about the science of trust in science, though,” said David Lazer, a professor of political science at Northeastern University.
The use of AI in health care also poses new risks. Biased algorithms could perpetuate discrimination along racial and economic lines, and lead to the adoption of inadequately vetted products that drive up costs without benefiting patients. Understanding these risks — and weighing them against the potential benefits — requires a deeper understanding of AI itself.
It’s for these reasons that we created STACI: the STAT Terminal for Artificial Computer Intelligence. She will walk you through the key concepts and history of AI, explain the terminology, and break down its various uses in health care. (This interactive is best experienced on screens larger than a smartphone’s.)
Fadi Alsaleem is using blue-tooth thermometers to look for abnormal spikes in the number of people with fevers in a certain area.
“With this fever, you are at home, you measure yourself, you send your data to the cloud, then we compare to the past history and we can tell there’s something ongoing in this county, in this city, even in this zip code,” said Fadi Alsaleem, a UNL researcher and assistant professor of Architectural Engineering.
With that information being sent to a cloud network, Alsaleem uses the data as an indicator of where coronavirus may pop up.
MIT engineers have designed a “brain-on-a-chip,” smaller than a piece of confetti, that is made from tens of thousands of artificial brain synapses known as memristors — silicon-based components that mimic the information-transmitting synapses in the human brain.
The researchers borrowed from principles of metallurgy to fabricate each memristor from alloys of silver and copper, along with silicon. When they ran the chip through several visual tasks, the chip was able to “remember” stored images and reproduce them many times over, in versions that were crisper and cleaner compared with existing memristor designs made with unalloyed elements.
A bipartisan cadre of tech-focused legislators in the House and Senate have introduced legislation that would direct the federal government to develop a national cloud computing infrastructure for artificial intelligence research.
Introduced by Sens. Rob Portman, R-Ohio, and Martin Heinrich, D-N.M., Thursday, the National Cloud Computing Task Force Act would convene a mix of technical experts across academic, industry and government. The group would develop a nuanced roadmap for how the nation should build, deploy, govern and sustain a national research cloud for AI.
This October, City, University of London will establish a new National Centre for Creativity enabled by Artificial Intelligence (CebAI), funded by UK Research and Innovation’s (UKRI) Research England Development Fund and industrial partners including Grant Thornton and SAGE Publishing.
The Centre is committed to delivering new, more scalable forms of knowledge exchange.
It will provide new types of service to augment the creative capabilities of UK businesses. These services will combine artificial intelligence algorithms, interactive tools, creativity consulting practices and leadership training into new offerings for business partners.
Scientists recommend protecting at least 30% of the ocean by 2030 to safeguard biodiversity, avoid fishery collapse and build ocean resistance to climate change.
In 2018 and 2019, representatives from the United Nations were negotiating a high seas treaty to meet this goal through a network of marine protected areas (MPAs) throughout the open ocean, but the meeting meant to finalize the treaty in March was delayed due to COVID-19.
Two reports were presented to show how to practically protect 30% of the ocean: one from a group of researchers from University of Oxford, the University of York and Greenpeace, and the other from the University of California, Santa Barbara, and other universities and institutions.
From a community organizer’s perspective, this is a major setback, but in truth, prior to COVID, we were already seeing trends that indicated a change was in order. COVID has merely accelerated a shift in the marketplace for data practitioners, and companies approaching AI.
Also, it has forced us to re-assessed the effectiveness of our gatherings, and adopt new ways for our community to meet and network. The good news is, these changes offer new opportunities for those looking to build skills and network effectively with peers. It just takes some creativity and an open mind.
Even as most California hospitals have avoided an incapacitating surge in coronavirus patients, some facilities near the Mexican border have been overwhelmed. They include El Centro Regional Medical Center in Imperial County and Scripps Mercy Hospital Chula Vista in San Diego County, which link the spike in COVID-19 patients to their communities’ cross-border lifestyle.
Some U.S. citizens and legal residents who live in Mexico are crossing the border from Tijuana and Mexicali into the U.S. for treatment. Dr. Juan Tovar, an emergency physician and chief operations executive for Scripps Mercy Hospital Chula Vista, said 48% of COVID-positive patients who visited the emergency room between May 24 and May 30 said they had recently traveled to Mexico.
There are two components to SIERA’s safety solution, accident prevention and cloud-based data collection and reporting. Once a forklift has the S3 device and software installed, it automatically senses and stops the vehicle from colliding with people, pallets, totes, and racks without driver intervention. At the same time, the S3 software tracks the forklift’s movement and delivers real-time performance data to management for analysis and insight into behavior, accident-prone areas within a facility and how best to proceed. Any forklift, regardless of maker, can be retrofitted with SIERA.AI’s software.
For the last few years, the music industry has only known one direction: up. Global sales have climbed 5 years in a row, buoyed by the rise of streaming services Spotify and Apple Music, while concert ticket sales eclipsed $10 billion, a new high.
The pandemic changed all that. Concerts have been canceled for most of 2020, and music listening has fallen by about 550 million streams a week (3.4%) for the last 10 weeks, according to Billboard/MRC Data. The decline has impacted almost every kind of music, with dance, latin and hip-hop/R&B suffering the most.
But two genres have been spared the covid crunch: children’s music and country. Country in particular has thrived. U.S. residents have listened to an average of 11.1% more country since mid-March—an increase of 127 million streams a week. And while growth in kids’ music has subsided as more people return to work, country has only accelerated. Country music streaming climbed 22.4% in the final full week of May.
One of Texas’ biggest contractors, Dallas-based Rogers-O’Brien Construction, claims it is owed $34 million by Microsoft Corp. for work on a problem-plagued new data center project in San Antonio.
The company made the claim in a lawsuit filed June 3 in federal district court in San Antonio. It blames Microsoft and an unnamed designer and vendors for failing to help correct the troubles. Microsoft has yet to answer with a reply to the complaint and a spokesman for the company could not be reached for comment.
Imagine a world in which we can produce meat without animals, cure previously incurable diseases by editing an individual’s genetic fabric, and manufacture industrial chemicals in yeast factories. The foundational technologies that could make all this possible largely exist. Rapid and ever-cheaper DNA sequencing has deepened our understanding of how biology works and tools such as CRISPR are now being used to recode biology to treat diseases or make crops less vulnerable to climate change. This is what we call the Bio Revolution.
Explored in a new McKinsey Global Institute research report, which we helped co-author, the Bio Revolution is already benefiting society. A confluence of breakthroughs in biological science and ever faster and more sophisticated computing, data analytics, and artificial intelligence technologies has powered scientific responses to the Covid-19 pandemic. Scientists sequenced the virus’ genome in weeks rather than months, as was the case in previous outbreaks. Bio innovations are enabling the rapid introduction of clinical trials of vaccines, the search for effective therapies, and a deep investigation of the transmission patterns of the virus.
The report estimates that bio innovations could alleviate between 1% and 3% of the total global burden of disease in the next 10 to 20 years from these applications — roughly the equivalent of eliminating the global disease burden of lung cancer, breast cancer, and prostate cancer combined.
Cox Communications is lowering Internet upload speeds in entire neighborhoods to stop what it considers “excessive usage,” in a decision that punishes both heavy Internet users and their neighbors.
Cox, a cable company with about 5.2 million broadband customers in the United States, has been sending notices to some heavy Internet users warning them to use less data and notifying them of neighborhood-wide speed decreases. In the case we will describe in this article, a gigabit customer who was paying $50 extra per month for unlimited data was flagged by Cox because he was using 8TB to 12TB a month.
A new study finds just how divergent the interests of US partisan donors are from those of the party base. With the 2020 election expected to be the costliest ever, the potential for consensus narrows as politicians dial for dollars.
I was a police officer for nearly ten years and I was a bastard. We all were.
This essay has been kicking around in my head for years now and I’ve never felt confident enough to write it. It’s a time in my life I’m ashamed of. It’s a time that I hurt people and, through inaction, allowed others to be hurt. It’s a time that I acted as a violent agent of capitalism and white supremacy. Under the guise of public safety, I personally ruined people’s lives but in so doing, made the public no safer… so did the family members and close friends of mine who also bore the badge alongside me.
Students from underrepresented groups start college with the same level of interest in STEM majors as their peers, but leave STEM at higher rates. We tested the hypothesis that low grades in general chemistry contribute to this “weeding,” using records from 25,768 students. In the first course of a general chemistry series, grade gaps based on binary gender, race/ethnicity, socioeconomic status, and family education background ranged from 0.12 to 0.54 on a four-point scale. Gaps persisted when the analysis controlled for academic preparation, indicating that students from underrepresented groups underperformed relative to their capability. Underrepresented students were less likely than well-represented peers to persist in chemistry if they performed below a C−, but more likely to persist if they got a C or better. This “hyperpersistent zone” suggests that reducing achievement gaps could have a disproportionately large impact on efforts to achieve equity in STEM majors and professions.
The spread of Covid-19 associated with a University of Vermont men’s basketball playoff game appears to be more extensive than was previously reported.
Ten more people who attended the March 10 game said they later experienced symptoms, bringing the total to at least 16 Vermonters. Three of them have died of the virus.
Some of those reporting severe symptoms were not able to get a test, so there is no way to determine with certainty the full extent of the actual spread.
The Pittsburgh Supercomputing Center has won a $5 million award from the National Science Foundation to build Neocortex, an AI supercomputer that incorporates the Cerebras Systems Wafer Scale Engine technology introduced last year along with Hewlett Packard Enterprise’s shared memory Superdome Flex hardware.
PSC, a joint research organization of Carnegie Mellon University and the University of Pittsburgh, said the Cerebras–HPE system will be available by the end of this year.
A game-changing technique for imaging molecules known as cryo-electron microscopy has produced its sharpest pictures yet — and, for the first time, discerned individual atoms in a protein.
By achieving atomic resolution using cryogenic-electron microscopy (cryo-EM), researchers will be able to understand, in unprecedented detail, the workings of proteins that cannot easily be examined by other imaging techniques, such as X-ray crystallography.
The breakthrough, reported by two laboratories late last month, cements cryo-EM’s position as the dominant tool for mapping the 3D shapes of proteins, say scientists. Ultimately, these structures will help researchers to understand how proteins work in health and disease, and lead to better drugs with fewer side effects.
University of Pittsburgh, Swanson School of Engineering
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Computational catalysis, a field that simulates and accelerates the discovery of catalysts for chemical production, has largely been limited to simulations of idealized catalyst structures that do not necessarily represent structures under realistic reaction conditions.
New research from the University of Pittsburgh’s Swanson School of Engineering, in collaboration with the Laboratory of Catalysis and Catalytic Processes (Department of Energy) at Politecnico di Milano in Milan, Italy, advances the field of computational catalysis by paving the way for the simulation of realistic catalysts under reaction conditions. The work, published in ACS Catalysis, was authored by Raffaele Cheula, PhD student in the Maestri group; Matteo Maestri, full professor of chemical engineering at Politecnico di Milano; and Giannis “Yanni” Mpourmpakis, Bicentennial Alumni Faculty Fellow and associate professor of chemical engineering at Pitt.
If you’ve ever wanted to try out OpenAI’s vaunted machine learning toolset, it just got a lot easier. The company has released an API that lets developers call its AI tools in on “virtually any English language task.”
Basically, if you’ve got a task that requires understanding words in English, OpenAI wants to help automate it. The various abilities of the GPT-3 family of natural language understanding models are at the disposal of developers, at least if you can get into the private beta. (Request access here.)
Harvard Institute for Applied Computational Science
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Cambridge, MA January 21-24, 2020, at Harvard University Science Center. “Organized by the Harvard Institute for Applied Computational Science (IACS) and open to the public, ComputeFest is four days of advanced applied machine learning workshops led by IACS researchers, students, alumni, and industry presenters.” [$$$]
New York, NY March 5, starting at 6:30 p.m., National Museum of Mathematics (11 E 26th St). “How can we capture human intelligence in engineering terms, and what are the prospects for someday building machines that are as smart as we are? Join Dr. Joshua B. Tenenbaum, Professor of Computational Cognitive Science at the Massachusetts Institute of Technology and 2019 MacArthur Fellow, to explore the mathematics of minds, both natural and artificial.” [registration required, museum admission applies]
University of Chicago, Argonne National Laboratory
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Online April 29. “The event is designed to provide new insights into managing research data and storage at scale, as well as building and using cutting-edge applications, portals and gateways.” [registration required]
“To accelerate distributed applications and close the yawning performance gap, DARPA initiated the Fast Network Interface Cards (FastNICs) program. FastNICs seeks to improve network stack performance by a factor of 100 through the creation of clean-slate networking approaches. Enabling this significant performance gain will require a rework of the entire network stack – from the application layer through the system software layer, down to the hardware.” Deadline for responses is October 8.
This “contest challenges high school and college students to use statistics to dig into the data and come up with their own ideas to help solve homelessness.”
“Through this contest, you will put your statistical and data visualization skills to work with a team of your high school or undergraduate peers to help find ways to reduce and resolve the homelessness crisis, using HUD’s 2018 Point-in-Time Estimates of Homelessness in the US dataset.” Deadline for submissions is October 28.
“”We’re looking for imaginative proposals for component technologies that, when brought together with our OFFSET physical testbeds, can lead to technological breakthroughs for future swarm capabilities. says Timothy Chung, program manager in DARPA’s Tactical Technology Office (TTO). ‘The ability to enhance commercial-off-the-shelf (COTS) air and ground platforms can lead to new modes of swarm operations and disruptive swarm tactics for warfighters.'” Deadline for proposals is November 12.
“As of November, 2017, the nomination process has slightly changed. The selection subcommittees are now public, and there is a required nomination process. We welcome and encourage numerous nominations. Please keep in mind that lobbying (even informally) of committee members is not allowed.” Deadline for nominations is November 17.
Dublin, Ireland April 20-24, 2020, at Trinity College, Dublin. “This conference series aims to bring together a wide variety of developers, educators and other contributors to Python packages in the context of all forms of astronomy.” Deadline to apply to attend is January 6, 2020.
“We’re bringing back the Android Developer Challenge and asking you to help us unlock new experiences on Android! As we kick off this challenge, the first area we’ll be focusing on is On-Device Machine Learning.” Deadline for proposals is December 2.
“The Center for Data Science at New York University invites applications for its CDS Moore-Sloan Faculty Fellow positions. Building on the successes with the Moore-Sloan Fellows program, CDS has created a Faculty Fellow program to continue to develop outstanding researchers in Data Science.” Deadline to apply is December 23.
“Predictive Analytics for Business Analysts: Using AI to Drive Strategy” is specifically curated to match the needs of executive professionals. Link below for more info.
“We are seeking proposals for software tools that will tackle some of the challenges currently facing social scientists and enable more researchers to engage with computational methods.” Deadline for applications is February 23.
“we are launching the 2020 Foundational Integrity Research: Misinformation and Polarization request for proposals. We will award $2 million in unrestricted gifts to support independent social science research on misinformation and polarization related to social communication technologies.” Deadline for proposals is April 1.
The UK has rainfall records dating back 200 years or so, but the vast majority of these are in handwritten form and can’t easily be used to analyse past periods of flooding and drought.
The Rainfall Rescue Project is seeking volunteers to transfer all the data into online spreadsheets.
“Upload short recordings of cough and breathing and report symptoms to help researchers from the University of Cambridge detect if a person is suffering from COVID-19. Healthy and non-healthy participants welcome.”
We call for collaborations to analyze 250M+ tweets about #COVID19. We will select up to 10 projects and provide the proponents with processed data to speed up the analysis.
Website for those who want to volunteer for a potential future human challenge trial for a COVID-19 vaccine and/or advocate for the use of such trials to speed development
Participate in our IASGE Survey! … The time has come: survey time! Do you work in an academic institution, of any kind? Have you been introduced to Git and/or actively use Git? Or maybe you heard about Git, and want to try it, but haven’t found the time?
… The Stanford Healthcare Innovation Lab recently launched the COVID-19 wearables study aimed at determining whether smartwatches (like your Garmin) can predict the onset of an infectious disease (like COVID-19) before actual symptoms are noticeable. This stems from a previous study conducted by Michael Snyder, Ph.D., professor and chair of genetics at the Stanford School of Medicine, which showed how specific patterns of heart rate variation can indicate illness, sometimes even while the individual is asymptomatic. Because of evidence that suggests many people were contagious before they presented symptoms, having this information early on could be extremely valuable in slowing and stopping the spread of infectious diseases.
“Last August, we invited the research community to join us in accelerating self-driving technology with the release of one of the largest multi-sensor self-driving datasets available today. Even as COVID-19 continues to develop, we are committed to fostering an environment of innovation and learning – one that can continue to grow and thrive in our temporarily virtual world. That is why today, we are launching the next phase of our program: expanding the Waymo Open Dataset by an additional 800 segments and inviting researchers to participate in Waymo’s Open Dataset Challenges.” Deadline for submissions is May 31.
Best practices on collaborations between people and AI systems – including those for issues of transparency and trust, responsibility for specific decisions, and appropriate levels of autonomy – depend on a nuanced understanding of the nature of those collaborations.
With the support of the Collaborations Between People and AI Systems (CPAIS) Expert Group, PAI has developed a Human-AI Collaboration Framework, containing 36 questions that identify some characteristics that differentiate examples of human-AI collaborations. We have also prepared a collection of seven case studies that illustrate the Framework and its applications in the real world.
AI systems promise to augment human perception, cognition, and problem-solving abilities. They also pose risks of manipulation, abuse, and other negative consequences, both foreseen and unintended. Today’s AI technologies interact with humans increasingly often and in varied contexts and modalities – a human might seek mental health services from a chatbot, use autonomous vehicles for transportation, and even learn from an intelligent tutoring system. It is therefore vital that we do not think about AI systems as isolated technical systems, but rather as technologies embedded into people’s lives.
To help developers and users better understand the nature of these interactions, PAI’s Collaborations Between People and AI Systems (CPAIS) Expert Group [1] has conducted a series of research projects, with a focus on reviewing relevant literature, developing case studies with practitioners, and producing useful tools and high level insights. Developing best practices for these collaborations is a key part of PAI’s mission to advance the responsible and socially beneficial development and deployment of AI.
“In part 1 of this series, we discussed the sources of uncertainty in machine learning models, and techniques to quantify uncertainty in the parameters, and predictions of a simple linear regression model. … In this part of our series we’re going to look at a technique that can provide uncertainty estimates at prediction time for any Neural Network architecture, without making any changes to how the network is trained.”
How can you overcome this challenge and move your idea from a science project to true data science?
Start small, with a project that addresses a core competency of the business. Make sure all parties agree on the business value and technical feasibility of the project.
Select a project that will offer a win within a year. Know going into the project what a win looks like and how it will be measured.
Look for opportunities to automate and expand your use of analytics. Automation can multiply the results of your project exponentially.
#1 Understand the Advantages of Connecting to the Internet
Don’t connect your smart device to the internet just because it has the capability. First you should check what features are available in your device without connecting it to the internet. You might discover that your smart device has good features which are available without internet connection. In that scenario, it is better to use the device offline. This is a good way of protecting your security without having to spend anything.
Although it is important to be proficient in understanding the inner workings of the algorithm, it is far more essential to be able to communicate the findings to an audience who may not have any theoretical / practical knowledge of machine learning. Just showing that the algorithm predicts well is not enough. You have to attribute the predictions to the elements of the input data that contribute to your accuracy. Thankfully, the random forest implementation of sklearn does give an output called “feature importances” which helps us explain the predictive power of the features in the dataset. But, there are certain drawbacks to this method that we will explore in this post, and an alternative technique to assess the feature importances that overcomes these drawbacks.
In this third post in our three part series I’ll focus on two bedrock components of the European Union’s General Data Protection Regulation (GDPR): data mapping and data inventories. Previously, we covered the core pillars of Obsidian’s data guardianship and why we position ourselves as data guardians not privacy watch dogs.
When data reporting was composed of a jumble of scribbled numbers, we couldn’t imagine technology has revolutionized the data reporting: beautiful, convenient, and closely integrated with various systems. Today, data reports have been the basis of data-decisions, as well as been closely connected with data analysis and business intelligence to help us discover the insights in our business.
In this article, I will explain what data reporting is, use the real case to clarify the five steps to make your data reports stand out, and in the end, I will provide the best industry data reports examples for you.
David Malan does a really great job of this bottom-up approach to code without accidentally screening for prior knowledge in Harvard’s CS50 course. Whenever he calls on a student, he celebrates the reasonable misconceptions of beginners, and acknowledges but does not glorify the more advanced students’ out-of-scope questions (which can alienate those with less experience).
But odds are, you aren’t David Malan. So I want to propose an inversion of the lesson structure that lets you welcome beginners with the same enthusiasm that he does.
This python based tool maps the stream network, banks, and floodplain and then extracts common geomorphic characteristics from digital elevation models (DEMs).
Looking for the right Google Cloud machine learning tool for your application? In this overview, you’ll get an overview of our suite of machine learning products. Whether you’re an application developer, data scientist, or ML engineer, there’s something for you. [video, 4:58]
Wayfair Data Science blog, Dave Harris and Tom Croonenborghs
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“At Wayfair, we are constantly working to improve our customers’ shopping experiences. If we are not able to personalize a customer’s experience, for example, because they are a first-time customer and we do not yet know their preferences, then it is important that we make it easy for them to find the products with the broadest appeal. This post features a new Bayesian system developed at Wayfair to (1) identify these products and (2) present them to our customers.”
Harvard Business Review, H. James Wilson and Paul R. Daugherty
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More than three quarters of large companies today have a “data-hungry” AI initiative under way — projects involving neural networks or deep-learning systems trained on huge repositories of data. Yet, many of the most valuable data sets in organizations are quite small: Think kilobytes or megabytes rather than exabytes. Because this data lacks the volume and velocity of big data, it’s often overlooked, languishing in PCs and functional databases and unconnected to enterprise-wide IT innovation initiatives.
But as a recent experiment we conducted with medical coders demonstrates, emerging AI tools and techniques, coupled with careful attention to human factors, are opening new possibilities to train AI with small data and transform processes.
“It’s better to be guided by data than to rely on hearsay,” advises Cleveland Clinic infectious disease specialist Steven D. Mawhorter, MD, Medical Director of the International Travel Clinics. “People perceive that gas prices always go up before holiday weekends — but data tells us that prices go up and down equally before holidays. The same selective recall can be true with air travel and sickness.”
What only insiders generally know is that data scientists, once hired, spend more time building and maintaining the tools for AI systems than they do building the systems themselves. A recent survey of 500 companies by the firm Algorithmia found that expensive teams spend less than a quarter of their time training and iterating machine-learning models, which is their primary job function.
Now, though, new tools are emerging to ease the entry into this era of technological innovation. Unified platforms that bring the work of collecting, labelling and feeding data into supervised learning models, or that help build the models themselves, promise to standardize workflows in the way that Salesforce and Hubspot have for managing customer relationships. Some of these platforms automate complex tasks using integrated machine-learning algorithms, making the work easier still. This frees up data scientists to spend time building the actual structures they were hired to create, and puts AI within reach of even small- and medium-sized companies, like Seattle Sports Science.
Frustrated that its data science team was spinning its wheels, Seattle Sports Science’s AI architect John Milton finally found a commercial solution that did the job. “I wish I had realized that we needed those tools,” said Milton. He hadn’t factored the infrastructure into their original budget and having to go back to senior management and ask for it wasn’t a pleasant experience for anyone.
We know data preparation requires a ton of work and thought. In this provocative article, Hugo Bowne-Anderson provides a formal rationale for why that work matters, why data preparation is particularly important for reanalyzing data, and why you should stay focused on the question you hope to answer. Along the way, Hugo introduces how tools and automation can help augment analysts and better enable real-time models.
Memorize these five Zoom hacks and you can have the best video calls on your side of the Mississippi.
Change your Zoom background
I’m not 100 percent sure what the makers of Zoom had in mind when they developed the virtual background feature, but right now, it’s a crucial part of having fun with your friends during social distancing.
Use cases are useful for identifying, clarifying and illustrating requirements and their possible solutions. Metadata 2020 is gathering specific examples help illustrate the challenges and potential of working toward the Metadata Best Principles and Practices.
As you explore these use cases, we recommend looking at the unfamiliar in addition to those that may be close to your work. There may be cases that are directly related to your needs, while other surface where your experiences might be applied.
Hello from the Warren for President Tech Team. Over the past year, our team worked as hard as we could to make getting involved with Elizabeth’s campaign as easy as possible — whether it was connecting new volunteers with organizers in their area, empowering volunteers to text voters, or making finding your polling place as easy as possible.
We are so grateful for the hundreds of thousands of Warren supporters who used our tools to help our grassroots movement: Thank you.
In our work, we leaned heavily on open source technology — and want to contribute back to that community. So today we’re taking the important step of open-sourcing some of the most important projects of the Elizabeth Warren campaign for anyone to use.
“We recently shared our top five remote-first tips with Cloud AI leadership, our parent organization within Google. Now, we want to share our advice with you! The advice we put together is based on the things that we believe either require the biggest behavior shift or stand the best chance of increasing productivity to address pain points in this time of transition.”
In data science fields, tons of papers and articles are published every day. Many websites like Medium have an efficient recommendation system that does a good job of recommending the articles on which we cannot resist clicking. One article after another appears to be useful. So we keep reading, and either closing the tab or saving the article for future reference. Since we come across many articles every day, we must be informed by new information, right? Not quite so.
The best way for us to absorb new knowledge is to use it. No matter how many technical articles we read, if we don’t apply the new knowledge, we will retain almost nothing. We might retain something now but will forget it a week later. But think about it. In a fast pace and overload society, what is our common strategy for reading an article?
Curiosity Studies stages an interdisciplinary conversation about what curiosity is and what resources it holds for human and ecological flourishing. These engaging essays are integrated into four clusters: scientific inquiry, educational practice, social relations, and transformative power. By exploring curiosity through the practice of scientific inquiry, the contours of human learning, the stakes of social difference, and the potential of radical imagination, these clusters focus and reinvigorate the study of this universal but slippery phenomenon: the desire to know.
This repository contains the code for Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference. The paper introduces pattern-exploiting training (PET), a semi-supervised training procedure that reformulates input examples as cloze-style phrases and significantly outperforms regular supervised training in low-resource settings.
Scientific American, Behavior & Society; Francesca Gino, Julia Minson, Mike Yeomans
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… Our research focuses on improving what we call conversational receptiveness—the extent to which parties in disagreement can communicate their willingness to engage with each other’s views. Conversational receptiveness involves using language that signals a person is truly interested in another’s perspective. When individuals appear receptive in conversation, others find their arguments to be more persuasive, our work shows. In addition, receptive language is contagious: it makes those ones disagrees with more receptive in return. People also like others more and are more interested in partnering with them when they seem receptive. Disagreements that may have spiraled into heated conflicts instead lead to conflict resolution.
Getting machine learning (ML) into production is hard. In fact, it’s possibly an order of magnitude harder than getting traditional software deployed. As a result, most ML projects never see the light of production-day and many organizations simply give up on using ML to drive their products and customer experiences.1
From what we’ve seen, a fundamental blocker preventing many teams from building and deploying ML to production at scale is that we have not yet successfully brought the practices of DevOps to machine learning. MLOps solutions have emerged that solve the process of building and deploying ML models — but they lack support for one of the most challenging parts of ML: the data.
In this article we’ll be concentrating on high value software projects and why driving engineers to create detailed estimates for these projects, and then pressuring them to complete the software according to those estimates, is a value destroying mistake.
Most of us in the software industry have been asked over and over to participate in predictive planning for software projects. Predictive planning is the flawed idea that software projects lend themselves to being planned out like a construction project, using a tool like a Gantt chart. While it is true that a narrow set of low value software projects are tamable with a Gantt chart, high value software projects that fill previously unmet needs do not lend themselves to being tamable by predictive scheduling techniques.
AI agents have the ability to discern understanding from complex patterns but falsely labelling or recognising a phenomena has to be fixed in this space. There are just some things we can’t afford to get wrong.
In what follows, I cover a few methodologies to remove these biases from machine learning datasets, and how we these rules can be implemented.
Last week someone ask me for advice about a setup where an NLG system produced a draft text, which would be edited by a human domain expert before being released; this is what the MT community calls post-editing. They also wanted to know if it was possible for the NLG system to automatically learn from human post-edits.
This kind of thing is often suggested for contexts where an NLG system produces texts which are mostly OK, but occasionally need fixing before being released to users (for example, because handling of edge cases is limited).
Language on the Move, Gregory Haimovich and Herlinda Márquez Mora
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The Covid-19 pandemic has brought the persistent health disadvantage of Indigenous populations into focus, as well as the exclusion of Indigenous languages from public health communication. In this latest contribution to our series of language aspects of the COVID-19 crisis, Gregory Haimovich and Herlinda Márquez Mora report on an ongoing project that aims to provide bilingual services in Nahuatl and Spanish in rural Mexico
Hello my friends. Especially if you’re in the United States, it’s a pretty scary time right now. Protests against police brutality and lack of accountability have led to a violent escalation by the police across the country. It’s easy to feel overwhelmed and helpless, especially if police brutality isn’t an issue that’s been on your radar. I’ve written this guide for my fellow non-Black folks in tech to help you figure out for yourself what specific actions you can take to help, now and into the future.