Paul Allen has made a name for himself as a co-founder of Microsoft, a supporter of artificial intelligence research and a contributor to causes such as wildlife conservation — so it only makes sense that the Seattle-area billionaire wants to use machine learning to further his philanthropic goals.
His latest contribution comes through the Seattle-based Vulcan Machine Learning Center for Impact, or VMLCI. “Its mission will be to apply the tools of machine learning and AI for good,” Bill Hilf, CEO of Paul Allen’s Vulcan Inc., said today in a tweet.
VMLCI’s strategy meshes with the mission of the Allen Institute for Artificial Intelligence, whose motto is “AI for the Common Good.” The center aims to forge collaborative partnerships with corporations, academic institutions and other organizations to help connect folks working on social and environmental causes with the machine-learning resources they need.
On the one hand, one cannot but be impressed with, and enjoy, what we have been able to accomplish with neural networks. On the other hand, mainstream scientific intuition stands in the way of accepting that a method that does not require explicit modeling or sophisticated reasoning is sufficient for reproducing human-level intelligence. This dilemma is further amplified by the observation that recent developments did not culminate in a clearly characterized and profound scientific discovery (such as a new theory of the mind) that would normally mandate massive updates to the AI curricula. Scholars from outside AI and computer science often sense this dilemma, as they complain they are not receiving an intellectually satisfying answer to the question: “What just happened in AI?”
The answer lies in a careful assessment of what we managed to achieve with deep learning and in identifying and appreciating the key scientific outcomes of recent developments in this area of research. This has unfortunately been lacking to a great extent. My aim here is to trigger such a discussion, encouraged by the positive and curious feedback I have been receiving on the thoughts expressed in this article.
Many fitness trackers are not accurate at measuring heart rate, and can backfire when it comes to weight loss. It’s easy enough to cheat with fitness devices, but John Hancock isn’t worried about that either. “These programs are going to be in place for an average of 20 years and often much longer,” Tingle says, “and while people might figure out a way to get more steps in the short term, people aren’t going to do that for two decades.”
Though the program is optional, experts worry that it’ll change down the line. “At this stage, they’re saying it’s voluntary,” Ann Cavoukian, who served as Ontario’s Information and Privacy Commissioner until 2014 told CBC.”My gut says over time it’s not going to be voluntary, or it will be less voluntary, or there will be consequences for not doing it. Like you’ll pay higher premiums because … you’re not willing to share that data. That’s what disturbs me.” (For his part, Tingle stresses that it’s important “the customer has total choice about whether they participate.”)
Another worry is that this will fundamentally change how we measure our lives, according to Dan Bouk, a historian at Colgate University.
I am nevertheless convinced that digital ID, writ large, poses one of the gravest risks to human rights of any technology that we have encountered. Worse, we are rushing headlong into a future where new technologies will converge to make this risk much more severe.
For starters, we are building near-perfect facial recognition technology and other identifiers, from the human gait to breath to iris. Biometric databases are being set up in such a way that these individual identifiers are centralized, insecure, and opaque. Then there is the capacity for geo-location of identifiers—that is, the tracking of digital “you”—in real time. A constant feed of insecure data from the Internet of Things may well connect you (and your identity) to other identities and nodes on the network without your consent.
The store is arranged in five or six rough sections, especially privileging books, home and kitchen goods, devices and electronics, and kids’ toys. The shopping experience itself isn’t all that different from what you might encounter anywhere else. (There’s no cashierless payment system here; you wait in line to pay an old-fashioned human at an old-fashioned checkout counter.) But the diversity and range of the items sold is unusual. That’s not just because you can buy items from Amazon’s private label brands, from Rivet-branded blankets to Stone and Beam-branded lighting, that can’t be found at other physical stores. But there’s also just so much of everything. I heard one guy marveling that Amazon 4-star is like a futuristic flea market. It’s more than that, but in some respects he’s right.
Shares of Nvidia Corp . had their best single-day performance since April after an analyst said he saw more than 40% upside for the stock.
Evercore’s C.J. Muse boosted his price target on the shares to $400 from $300 on Friday, making him the most bullish analyst tracked by FactSet. He thinks the company’s deep-learning platform is nearing a major breakthrough and predicts that Nvidia ’s (NVDA) stock will continue to post strong gains as the company deepens its artificial-intelligence push.
“We view Nvidia as being on the cusp of a tipping point in the company becoming the AI standard platform,” Muse wrote. He sees a number of applicable business areas, including gaming, high-performance computing, pro visualization, transportation, health care, and autonomous machinery.
Hangzhou International Marathon on Nov. 4 will use face recognition to prevent fraud and highlight the advanages of modern technology, said organizers.
Yang Yong, general manager of the road race project at Alibaba Group’s sports arm Alisports, said Hangzhou will increase the use of technology in this year’s race, which passes along West Lake and Qiantang River.
The Daily Free Press student newspaper, Dane Persky
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A new data sciences building, to be constructed at 645-655 Commonwealth Ave. was proposed by Boston University in a letter of intent Tuesday.
The letter from Senior Vice President for Operations Gary Nicksa, addressed to Brian Golden, director of the Boston Planning and Development Agency, detailed the university’s plan to replace the parking lot next to the Sargent College of Health and Rehabilitation Sciences with a 350,000 square-foot, 19-story building.
The space is intended to unify “closely allied data sciences disciplines,” and will offer “open space, pedestrian amenities and landscape features,” according to the letter.
npg Digital Medicine; Vijaya B. Kolachalama & Priya S. Garg
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Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools could play a key role by defining the way medicine will be practiced. Educating the next generation of medical professionals with the right ML techniques will enable them to become part of this emerging data science revolution.
Unity Technologies (https://unity3d.com/), creator of the world’s leading real-time 3D development platform, announced today its collaboration with DeepMind, the world leader in artificial intelligence (AI) research, that will enable the development of virtual environments and tasks in support of the company’s fundamental AI research program.
Demis Hassabis, co-founder and CEO of DeepMind, said: “Games and simulations have been a core part of DeepMind’s research programme from the very beginning and this approach has already led to significant breakthroughs in AI research. As a former video game designer myself, I couldn’t be more excited to be collaborating with Unity, creating virtual environments for developing and testing the kind of smart, flexible algorithms we need to tackle real-world problems.”
Providence, RI October 3-4 at Brown University. “This unique conference offers the research community a unique opportunity to look at how data and evidence are transforming research policy and strategy.” [$$$]
Miami, FL November 29-30 at University of Miami. ” Tapestry is an event designed to advance interactive online data storytelling. Tapestry brings different viewpoints together with the goal of generating a rich conversation about data storytelling. This two-day conference includes keynotes, short stories, discussion, and a demo theater designed to provoke ideas and discussion across disciplines.” [$$$]
“Can we use the content of news analytics to predict stock price performance? The ubiquity of data today enables investors at any scale to make better investment decisions. The challenge is ingesting and interpreting the data to determine which data is useful, finding the signal in this sea of information. Two Sigma is passionate about this challenge and is excited to share it with the Kaggle community.” Deadline for submissions is January 8, 2019.
Facebook today open-sourced its general purpose programming language Skip — aka “Reflex” — on Github, under an MIT source license. Skip is an experimental research language project that Facebook developed over the last three years: “Skip tracks side effects to provide caching with reactive invalidation, ergonomic and safe parallelism, and efficient garbage collection. Skip is statically typed and ahead-of-time compiled using LLVM to produce highly optimized executables.”
With the ever-changing landscape, forecasting opening box office revenue has become increasingly difficult and traditional ways of forecasting have seen higher error rates in more recent years, especially with the recent surge of record-breaking films in the superhero category despite a decline of total box office revenue in the industry. National Research Group, the primary tracking service for all major film studios, has implemented a more comprehensive data science framework to combine survey data with other sources of information that has mitigated these obstacles to forecasting. This article will explain this framework which can also be used in a variety of applications and forecasting objectives.