University of Illinois faculty want to install six “smart sensors” around Champaign to keep track of its climate, air quality and noise levels.
Under a proposal to be voted on Tuesday by the Champaign City Council, the sensors would be placed on city traffic-signal poles and provide real-time data for researchers and the public to use.
The Array of Things, which has been developed since 2013 in partnership with scientists at several universities, “will essentially serve as a ‘fitness tracker’ for the city,” staff wrote in a report to council.
U.S. Customs and Border Protection ditched a plan to use iris scanning to track people coming in and out of the country after a federal contractor couldn’t explain flaws in the technology. The agency switched gears instead to facial recognition, a move that independent reviewers say highlights the risks and opportunities that come with the growing use of artificial intelligence in the federal government.
The border agency wasn’t able to fully understand what went wrong with the scans, meant to use unique patterns in travelers’ irises to confirm their identities against their identification documents, according to internal agency records. That’s because the unnamed contractor that created the system didn’t want to divulge proprietary information.
“If CBP fails to understand the flaws in its own technology, it can expose itself to known vulnerabilities and fail to detect adversarial attacks,” researchers said in a first-of-its-kind examination of federal government use of artificial intelligence set for release Tuesday. “More broadly, agencies that lack access to a contractor’s proprietary technology may be unable to troubleshoot and adapt their own systems.”
Scientists think the universe is undergirded by a cosmic web of filaments and knots made of dark matter, a mysterious substance that accounts for most of the mass in the cosmos. These large-scale structures guide the evolution of galaxies, but their exact mechanics are currently unknown and hard to observe because dark matter, annoyingly, does not emit light like stars or galaxies.
Enter Dark Emulator: a sophisticated artificial intelligence tool created to model these immense cosmic processes. Using machine learning, the program is able to generate complex virtual universes that predict the behavior of large-scale structures, according to an October 2019 study in The Astrophysical Journal.
One example is the University of British Columbia’s Data Science Institute (DSI), which is conducting leading-edge data science research with a particular focus on biomedicine. Of the 16 studies that have emerged from the DSI across its almost five-year history, 11 have focused on various aspects of understanding, diagnosing and treating human illnesses such as cancer, Alzheimer’s disease, chronic obstructive pulmonary disease and autism.
The biomedical focus was influenced by the expertise of its founding director, Raymond Ng, who has studied data mining for the last two decades, much of it focused on health informatics. Dr. Ng, who holds the Canada Research Chair in Data Science and Analytics at UBC, says the DSI funds each project for 18 months, and then investigators are typically able to attract additional funding from external sources such as the federal research granting councils and healthcare-focused agencies and foundations.
Humans are error-prone and biased, but that doesn’t mean that algorithms are necessarily better. Still, the tech is already making important decisions about your life and potentially ruling over which political advertisements you see, how your application to your dream job is screened, how police officers are deployed in your neighborhood, and even predicting your home’s risk of fire.
But these systems can be biased based on who builds them, how they’re developed, and how they’re ultimately used. This is commonly known as algorithmic bias. It’s tough to figure out exactly how systems might be susceptible to algorithmic bias, especially since this technology often operates in a corporate black box. We frequently don’t know how a particular artificial intelligence or algorithm was designed, what data helped build it, or how it works.
Typically, you only know the end result: how it has affected you, if you’re even aware that AI or an algorithm was used in the first place. Did you get the job? Did you see that Donald Trump ad on your Facebook timeline? Did a facial recognition system identify you? That makes addressing the biases of artificial intelligence tricky, but even more important to understand.
As mental disorders rise — the cost to the global economy is projected to be $16 trillion over the next decade, according to the Lancet Commission — caring for patients with precision is a Holy Grail for mental-health professionals. Current diagnosis and treatment methods, while skilled and insightful, cannot fully capture the unique needs and complexity of every patient — not without time, money and a willingness that many people simply do not have. AI-based therapies have the potential to be faster and cheaper, and therefore more effective, which in turn can encourage patients to continue their counseling.
Data-based precision mental health also appeals to cost-conscious employers and insurance plans. Startups with traction in this area include Quartet Health, whose backers include GV (formerly Google Ventures), a unit of Alphabet GOOG, +0.22% GOOGL, +0.27%, which has partnered with health-care systems and health plans in several U.S. states, with a particular focus on underserved Medicaid patients. Another startup, Lyra Health, matches employees to health professionals using big data to diagnose mental conditions, and counts eBay EBAY, -0.65% and Amgen AMGN, +0.50% among its customers.
“We were so pleased to see the volume and quality of responses to this call for proposals,” says Brent Harris, Director of Governance and Strategic Initiatives. “Our team learned a great deal just from reviewing these submissions, and so we’re hopeful that the work that comes out of these awards will contribute positively to the broader conversation on content governance.”
Our team would like to thank all those who took the time to submit a proposal, and we offer our congratulations to the winners.
Data science is expanding rapidly in higher education. Colleges and universities around the world adds data science as a major, a center, or as a separate college. But at the K-12 level, few schools have implemented data science in their classrooms. To bridge that gap, the Data Science Institute at Columbia University (DSI) has several initiatives to help K-12 teachers and students learn the foundations of data science.
Dell Technologies announced today that it was selling legacy security firm RSA for $2.075 billion to a consortium of investors led by Symphony Technology Group. Other investors include Ontario Teachers’ Pension Plan Board and AlpInvest Partners.
RSA came to Dell when it bought EMC for $67 billion in 2015. EMC bought the company in 2006 for a similar price it was sold for today, $2.1 billion. The deal includes several pieces, including the RSA security conference held each year in San Francisco.
U.S. law says only humans can obtain patents, Iancu said. That’s why the patent office has been collecting comments on how to deal with inventions created through artificial intelligence and is expected to release a policy paper this year. Likewise, the World Intellectual Property Office, an agency within the United Nations, along with patent and copyright agencies around the world are also trying to figure out whether current laws or practices need to be revised for AI inventions.
The debate comes as some of the largest global technology companies look to monetize massive investments in AI. Google’s chief executive officer, Sundar Pichai, has described AI as “more profound than fire or electricity.” Microsoft Corp. has invested $1 billion in the research company Open AI. Both companies have thousands of employees and researchers pushing to advance the state of the art and move AI innovations into products.
A Pittsburgh artificial intelligence startup built on decades of search technology launched Monday with an aim to change the way news is published, delivered and consumed online.
MeSearch, founded as a joint venture with 535Media, will start the first tests of its technology with Trib Total Media to provide neighborhood news, said Joe Lawrence, the company’s CEO and general counsel for Trib Total Media.
A team of scientists using the Low Frequency Array radio telescope in the Netherlands has observed radio waves that carry the distinct signatures of aurorae, caused by the interaction between a star’s magnetic field and a planet in orbit around it.
Jeff Bezos, the richest man in the world, announced the launch of the “Bezos Earth Fund” in an Instagram post on Monday, committing $10 billion to the effort. The Amazon founder and owner of The Washington Post will use the money to start a global initiative that will fund scientists, activists or NGOs, as well as “any effort that offers a real possibility to help preserve and protect the natural world.” The fund will begin issuing grants this summer.
Accra, Ghana June 17-19 at University of Ghana. ” The 2nd Ghana Data Summit 2020 (dubbed IndabaX Ghana) is organized by the Data Science Network (a non-profit organization) and Wave-2 Analytics Ltd., a Ghanaian-based analytics startup in partnership with Deep Learning Indaba.” [application required]
University of California-Santa Barbara, National Center for Ecological Analysis and Synthesis (NCEAS)
Santa Barbara, CA February 27, starting at 5:30 p.m. “As we grapple with the challenge of how to eat healthy, support our local economy and protect the planet, choices about what food to eat can be difficult. In celebration of its 25th Anniversary, the National Center for Ecological Analysis and Synthesis (NCEAS) presents to you an engaging conversation between two leading marine ecologists that specialize in fisheries and ocean health.” [free]
Erty Seidohl, Julia Evans, Danielle Sucher, Kiran Bhattaram, Ahmed Abdalla, and Alicja Raszkowska
New York, NY May 9-10. “!!Con (pronounced “bang bang con”) 2020 is two days of ten-minute talks (with lots of breaks, of course!) to celebrate the joyous, exciting, and surprising moments in computing.” [save the date]
New York, NY April 22-24. “Jonah will be joined by fellow Stan developers Ben Bales and Rob Trangucci, and other members of the Stan Development Team will make some guest appearances at various times throughout the course.” [$$$$]
“For the past three years, we, at UN Global Pulse, have been working with UNOSAT to build a software tool that leverages artificial intelligence to identify and count structures from satellite images. From there, we expanded to a web-based toolkit that can be easily adapted to other remote sensing applications and which allows incorporation of models created by other users. Today, we officially launched the toolkit at the AAAI conference on artificial intelligence in New York.”
Neural networks for Natural Language Processing (NLP) have advanced rapidly in recent years. Transformer architectures in particular have shown they perform very well on many different NLP tasks, appearing to extract generally useful linguistic features. A recent Google Brain paper looks into Google’s hugely successful transformer network — BERT — and how it represents linguistic information internally.
Much work has been done on analyzing language processing models. Such work includes syntactic feature extraction and a geometric representation of parse trees in BERT’s activation space. In this article, Synced will give a brief introduction to the BERT model before exploring the contributions of this paper.