Google’s parent company, Alphabet, has launched a business that aims to make industrial robots easier to use, less costly and more flexible. The announcement of the business, called Intrinsic, follows more than five years of stealth development inside Alphabet’s secretive X “moonshot factory” which works on future technologies.
Most knowledge work today operates with no deliberate structure at all. Instead of carefully constructed processes to get the most out of each person, we just hand out tasks and leave people to organise themselves organically in whatever way feels easiest to them.
Since the 1990s, when everyone got an email address and most lost their assistants, that lack of direction has led to what Cal calls the ‘hyperactive hive mind’: everyone sends emails and chats to everyone else, all throughout the day, whenever they need anything.
Rather than strategic thinkers, managers work as human switchboards, answering and forwarding dozens of emails on any and every topic to keep the system from seizing up.
International Research Center for Neurointelligence
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NTT Research, Inc., a division of NTT (TYO:9432), today announced that it has entered a joint research agreement with The University of Tokyo’s International Research Center for Neurointelligence (IRCN) to develop Coherent Ising Machine (CIM)-related technologies. The agreement calls for the two research organizations to develop new numerical tools and a simulator for the CIM, an information processing platform based on photonic oscillator networks. The principal investigator (PI) for the three-and-a-half year research project is IRCN Deputy Director Kazuyuki Aihara, a University Professor at the University of Tokyo and expert in the mathematical modeling of complex systems and applications to neurointelligence. His counterpart at NTT Research is Physics & Informatics (PHI) Lab Senior Research Scientist Dr. Satoshi Kako, whose research is focused on the potential capability and application of coherent network computing.
A key component of the PHI Lab’s research agenda, a CIM addresses problems that have been mapped to an Ising model, which is a mathematical abstraction of magnetic systems composed of interacting spins, or angular momentums, of fundamental particles.
The people who spread new and controversial ideas—changes in diet, exercise routine, political leaning, or even attitudes about vaccination—may not be the Kim Kardashians and Paris Hiltons. According to a recent study in Nature Communications, those with the most actual influence are often on the periphery of the social network. Coauthor and computational sociologist Douglas Guilbeault says that what makes these people special is that they are embedded in a tight-knit group with many connections to other tight-knit groups, even if each individual has fewer contacts than the most popular or famous person in the network.
“Think of a blue-collar worker at a car factory, who, let’s say, starts to adopt a vegan diet and is surrounded by people who don’t eat that way,” says Guilbeault, at the University of California, Berkeley. Maybe the factory worker has one or two good friends who also decide to try veganism in the lunchroom. Their small group, though not famous or particularly aware of their influence, would likely spread positive attitudes about veganism through the workplace much more effectively than a famous person on YouTube. “If it comes from someone embedded in the network,” Guilbeault explains, “it can spread in a peer-to-peer fashion.”
LSU and Louisiana Tech University are proud to announce the establishment of the Center for Innovations in Structural Integrity Assurance, or CISIA, the first Industry/University Cooperative Research Center, or I/UCRC, for either institution.
CISIA will serve as a trusted source for transformative insights, predictive capabilities, and materials innovations across broad industrial sectors, focusing on structural integrity assurance for small and large structures and mechanical components.
British Journal of Sports Medicine; Daniel J McDonough, Xiwen Su, Zan Gao
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Objective To analyse the comparative effectiveness of different health wearable-based physical activity (PA) promotion intervention strategies against each other and control for reducing body weight and body mass index (BMI) in individuals with overweight/obesity and chronic comorbidities.
Design Systematic review and network meta-analysis (PROSPERO identifier: CRD42020158191).
Data sources We performed two independent searches from December 2019 to September 2020 in PubMed, MEDLINE, Scopus, Web of Science, Central Register of Controlled Trials, EMBASE and PsycINFO databases for articles published in English between 2007 and 2020.
Eligibility criteria for selecting studies Inclusion criteria were based on the PICOS framework. We included randomised controlled trials of health wearable-based interventions using two or more PA intervention arms/strategies and compared their effects on participants’ body weight (kg) and BMI (kg/m2) with a control group. Data were analysed using a Bayesian network meta-analysis to directly and indirectly compare the effects of the six different intervention strategies (comparators). The six comparators were: (1) control group (ie, usual care, waitlist); (2) comparison group (ie, traditional, non-health wearable PA interventions); (3) commercial health wearable-only intervention (eg, Fitbit, Polar M400); (4) research grade health wearable-only intervention (ie, accelerometers or pedometers); (5) multicomponent commercial health wearable intervention (eg, Fitbit + nutrition counselling); and (6) multicomponent research grade health wearable intervention. The results were reported as standardised mean differences (SMDs) with associated 95% credible intervals (CrIs).
Results From 641 screened records, 31 studies were included. For body weight reduction in individuals with overweight/obesity and chronic comorbidities, accelerometer/pedometer-only (SMD −4.44, 95% CrI −8.94 to 0.07) and commercial health wearable-only (SMD −2.76, 95% CrI −4.80 to −0.81) intervention strategies were the most effective compared with the three other treatments and control. For BMI reduction, multicomponent accelerometer/pedometer (SMD −3.43, 95% CrI −4.94 to −2.09) and commercial health wearable-only (SMD −1.99, 95% CrI −4.95 to 0.96) intervention strategies were the most effective compared with the other four conditions.
Conclusion Health wearable devices are effective intervention tools/strategies for reducing body weight and BMI in individuals with overweight/obesity and chronic comorbidities. [full text]
In a preprint posted online Thursday night, researchers at Google in collaboration with physicists at Stanford, Princeton and other universities say that they have used Google’s quantum computer to demonstrate a genuine “time crystal.” In addition, a separate research group claimed earlier this month to have created a time crystal in a diamond.
A novel phase of matter that physicists have strived to realize for many years, a time crystal is an object whose parts move in a regular, repeating cycle, sustaining this constant change without burning any energy.
“The consequence is amazing: You evade the second law of thermodynamics,” said Roderich Moessner, director of the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany, and a co-author on the Google paper. That’s the law that says disorder always increases.
The COVID-19 pandemic forced these companies to operate with mostly remote workforces for months straight. And since many of them are based in areas with relatively high vaccination rates, the calls to return to the physical office began to sound over the summer.
But thousands of high-paid workers at these companies aren’t having it. Many of them don’t want to go back to the office full time, even if they’re willing to do so a few days a week. Workers are even pointing to how effective they were when fully remote and using that to question why they have to keep living in the expensive cities where these offices are located.
Some tech leaders (like Twitter’s Jack Dorsey) agreed, or at least they saw the writing on the wall. They enacted permanent or semipermanent changes to their companies’ policies to make partial or even full-time remote work the norm. Others (like Apple’s Tim Cook) are working hard to find a way to get everyone back in their assigned seats as soon as is practical, despite organized resistance.
In either case, the work cultures at tech companies that make everything from the iPhone to Google search are facing a major wave of transformation.
Twitter has announced its first algorithmic bias bounty challenge, offering cash prices ranging from $500 to $3,500 for those who can help the social media giant identify a range of issues.
After significant backlash last year, the company admitted in May that its automatic cropping algorithm repeatedly cropped out Black faces in favor of White ones. It also favored men over women, according to research from Twitter. Multiple Twitter users proved this fact using pictures of themselves or of famous figures, like former President Barack Obama.
Rumman Chowdhury, director of Twitter META, explained that the company decided to change the algorithm and admitted that companies like Twitter often “find out about unintended ethical harms once they’ve already reached the public.”
Yale University has tapped the same search firm that helped Harvard and Stanford find their endowment chiefs, as the school looks for a successor to its longtime chief investment officer, David Swensen, who died in May.
Yale hired New York-based David Barrett Partners, according to a person familiar with the matter. The firm recently conducted a search for the Howard Hughes Medical Institute, which named its new CIO in June and had $21.2 billion of assets at the end of fiscal 2020. Yale has given little indication of how long it will take to find Swensen’s successor since appointing Alex Banker to run the fund on an interim basis in May.
At Ohio State, the number of students reporting feelings of burnout leapt 31 percentage points during the last academic year — from 40 percent of students in August 2020 to 71 percent in April, according to a university study. The report also found marked increases in anxiety, depression and unhealthy coping mechanisms such as substance use, lack of physical activity and social isolation over the eight-month period. Researchers plan to survey students again this fall.
Their findings aligned with the American Psychological Association’s Stress in America study: Gen Z adults ages 18 to 23 reported significantly higher stress levels than other generations. Of the Gen Z adults who said they are in college, 87% said their education was a significant source of stress, and stress is often linked to burnout. The association describes burnout as “physical, emotional, or mental exhaustion accompanied by decreased motivation, lowered performance, and negative attitudes toward oneself and others.” Hirabayashi said it’s often used as a catchall term, but ultimately it means, “the opposite of thriving.”
The deployment and use of digital twins in urban contexts are gaining momentum. Cities are increasingly discovering its benefits for both the planning and operational management of their assets. According to a new report by global tech market advisory firm ABI Research, cities are expected to achieve cost savings of US$280 billion by 2030 by using digital twins for more efficient urban planning.
“Digital twins will become the ultimate tool for city governments to design, plan and manage their connected infrastructure and assets in an efficient and cost-effective way. Cost savings can be obtained in key areas, such as energy and utilities, transportation, safety and security, and infrastructure (roads/buildings). However, urban digital twins also offer many other advantages in terms of supporting and improving sustainability, circularity, decarbonization and the overall quality of urban living,” says Dominique Bonte, Vice President End Markets at ABI Research.
National Institutes of Health, Center for Advanced Imaging Innovation and Research
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Florian Knoll, PhD, was among the first developers of machine learning reconstruction of magnetic resonance images from raw data. He is an outgoing assistant professor of radiology at NYU Langone Health and the incoming chair of imaging at Friedrich-Alexander University Erlangen-Nürnberg (FAU).
University of California-Berkeley, Berkeley Computing, Data Science, and Society
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California is amidst a period of intensifying drought. As of July 8(link is external), Governor Gavin Newsrom (D-Calif.) had issued drought emergency declarations for 50 of the state’s 58 counties and had urged local residents to voluntarily reduce their water use. Californians have seen dry periods like this before that prompted water scarcity concerns. But climate change is increasing the frequency and severity of these events, leading to increased public health(link is external) and environmental(link is external) concern.
We spoke with Laurel Larsen(link is external), a UC Berkeley associate professor of geography and Berkeley Institute for Data Science faculty affiliate who researches future clean water availability using data science. Larsen, who is currently on leave from Berkeley while serving as lead scientist at the Delta Stewardship Council(link is external), talked about water resource management in California and data science’s role in it.
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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
“While Stanford introduced me to the theory of certain topics like deep learning and computer vision, industry introduced me to teams that are actively providing value to the world by applying these practices at scale,” [Samuel] Kwong wrote.
Due to the sheer quantity of applications that companies like Facebook, Google and Amazon receive, sometimes an online application can be swept away and never even read by an employee, Forbes reported. Although a prestigious school, solid resume and high GPA can be assets, pure luck can sometimes turn out to be the most important factor in the equation. First-year computer science Ph.D. student Aaron Mishkin’s success in landing an internship at Amazon Research was a matter of being aligned on a research topic with recruiters, getting along well with Amazon faculty members during a research conference and engaging in constructive conversations during interviews.
Mishkin described as a misconception the notion that landing a job is purely based on a series of difficult technical interviews. “It’s actually more about knowing someone who can get you in the door,” he said.
Harvard Data Science Review, Jessica Hullman and Andrew Gelman
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Research and development in computer science and statistics have produced increasingly sophisticated software interfaces for interactive and exploratory analysis, optimized for easy pattern finding and data exposure. But design philosophies that emphasize exploration over other phases of analysis risk confusing a need for flexibility with a conclusion that exploratory visual analysis is inherently “model free” and cannot be formalized. We describe how without a grounding in theories of human statistical inference, research in exploratory visual analysis can lead to contradictory interface objectives and representations of uncertainty that can discourage users from drawing valid inferences. We discuss how the concept of a model check in a Bayesian statistical framework unites exploratory and confirmatory analysis, and how this understanding relates to other proposed theories of graphical inference. Viewing interactive analysis as driven by model checks suggests new directions for software and empirical research around exploratory and visual analysis. For example, systems might enable specifying and explicitly comparing data to null and other reference distributions and better representations of uncertainty. Implications of Bayesian and other theories of graphical inference can be tested against outcomes of interactive analysis by people to drive theory development.
Neo4j is among the graph database vendors who have been around the longest, and it now is the best-funded one, too. But that does not mean it’s the only one worth keeping an eye on. AWS entered the graph database market in 2018 with Neptune, and it has been making lots of progress since.
Today, AWS is unveiling support for openCypher, the open-source query language based on Neo4j’s Cypher. We take the opportunity to unpack what this means, and how it’s related to the future of graph databases, as well as revisit interesting developments in Neptune’s support for machine learning and data science.
