Last month, Apple became the first company valued at a trillion dollars. With its new ring-shaped campus, all glass and curvy lines, it looks the part of a company bestriding an industry. But its dominance wasn’t always assured.
Twenty-five years ago, the computer revolution’s marquee company was in decline. Back then, it was just settling into shiny new headquarters, a campus of six buildings that formed a different kind of ring. Called Infinite Loop, the name is a reference to a well-known programming error—code that gets stuck in an endless repetition—though no one seems to know who applied it. Infinite Loop was the place where Apple’s leaders and engineers pulled off a historic turnaround, and it will always be the source of stories and legends—many of them untold. Until now.
A climate conference in California this week tried something different. The meeting, organized by the state’s governor, Jerry Brown, had far fewer national leaders present. Instead, an array of governors, mayors and business executives from around the globe met to promote their successes in cutting greenhouse gas emissions locally and to encourage one another to do more.
A key premise of the conference was that if a handful of leading-edge states, cities and businesses can demonstrate that it’s feasible — and even lucrative — to go green in their own backyards, they might inspire others to follow suit. That, in turn, could make it easier for national leaders to act more forcefully.
This blog post summarizes a paper describing the privacy and ethics process by which we organized the Fragile Families Challenge. The paper will appear in a special issue of the journal Socius. This post is cross-posted on the Freedom to Tinker blog.
Academic researchers, companies, and governments holding data face a fundamental tension between risk to respondents and benefits to science. On one hand, these data custodians might like to share data with a wide and diverse set of researchers in order to maximize possible benefits to science. On the other hand, the data custodians might like to keep data locked away in order to protect the privacy of those whose information is in the data. Our paper is about the process we used to handle this fundamental tension in one particular setting: the Fragile Families Challenge, a scientific mass collaboration designed to yield insights that could improve the lives of disadvantaged children in the United States.
This week in Seattle, geoscientists from around the world are crowding in front of laptops in a classroom at the University of Washington to discuss code.
The reason? It’s the 2018 Geohackweek, an interactive workshop focused on helping geoscientists push the boundaries of geospatial research by teaching them open-source software and data analysis tools.
Geohackweek is the latest in a series of workshops run by a team of researchers that span a half dozen institutions, including the University of Washington, New York University, and the University of California, Berkeley. Inspired by hackathons typical of the tech world, Geohackweek and other similar efforts give researchers a venue to deep dive into data within a small group to see what they can discover. They seek to tease out clear answers to questions like these: Is there a way to layer or filter the data to learn something new about a given region? What signals can be found in the noise of different data sets?
Follow the money. At least that’s what America’s college students are doing when it comes to choosing majors.
The share of bachelor’s degree holders in the U.S. age 25 and over who majored in computers, math or statistics rose to 4.7 percent last year from 4.2 percent in 2009 — an increase of nearly 1 million students over the period, and 224,000 alone in 2017, according to Census Bureau data released Thursday.
Bloomberg, Politics, Andrew M Harris and Daniel Flatley
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U.S. Secretary of Education Betsy DeVos lost a lawsuit brought by 19 states and the District of Columbia, accusing her department of wrongly delaying implementation of Obama-era regulations meant to protect students who took out loans to attend college from predatory practices.
A Washington federal court judge on Wednesday ruled the department’s postponement of the so-called Borrower Defense rule was procedurally improper.
The New York Times, Matt Phillips and Karl Russell
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Fast-growing pockets of debt, as in the last time around, look like potential sources of problems. They’re nowhere near as big as the mortgage bubble, and no blow-ups appear imminent.
“But what we saw last time around is that things can creep up on you,” said Wesley Phoa, a bond-fund manager at the Capital Group. “You can turn around and in three years’ time you can go from not much of a problem to a pretty big problem.”
EPJ Data Science; Ajaykumar Manivannan, W. Quin Yow, Roland Bouffanais† and Alain Barrat
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Comprehensive and quantitative investigations of social theories and phenomena increasingly benefit from the vast breadth of data describing human social relations that is now available within the realm of computational social science. Such data are, however, typically proxies for one of the many interaction layers composing social networks, which can be defined in many ways and are composed of communication of various types (e.g., phone calls, face-to-face communication, etc.). As a result, many studies focus on one single layer, corresponding to the data at hand. Several studies have however shown that these layers are not interchangeable, despite the presence of a certain level of correlation between them. Here, we investigate whether different layers of interactions among individuals lead to similar conclusions with respect to the presence of homophily patterns in a population—homophily represents one of the widest studied phenomenon in social networks. To this aim, we consider a data set describing interactions and links of various nature in a population of Asian students with diverse nationalities, first language and gender. We study homophily patterns, as well as their temporal evolution in each layer of the social network. To facilitate our analysis, we put forward a general method to assess whether the homophily patterns observed in one layer inform us about patterns in another layer. For instance, our study reveals that three network layers—cell phone communications, questionnaires about friendship, and trust relations—lead to similar and consistent results despite some minor discrepancies. The homophily patterns of the co-presence network layer, however, does not yield any meaningful information about other network layers.
A Facebook executive confirmed reports that the social networking giant is hiring chip engineers and designing at least one ASIC. The news came at the @Scale event here, where Facebook announced that five chip companies will support Glow, an open-source, deep-learning compiler that it backs.
Facebook “is absolutely bringing up a silicon team focused on working with silicon providers, and we have a chip we’re building, but it’s not our primary focus,” said Jason Taylor, vice president of infrastructure at Facebook. The chip is “not the equivalent of [Google’s] TPU” deep-learning accelerator, he added, declining to provide further details on its focus or time frame.
All of the grand challenges facing humanity – ranging from healthcare to cybersecurity to environmental resilience – have this in common: Solving them will require increasingly sophisticated connections between the cyber and physical worlds. But the need to unleash the Internet of Things and harness big data is so urgent, it is outpacing the nation’s ability to prepare researchers with the skills and experience to solve large-scale, societal problems.
The University of Virginia School of Engineering’s Link Lab, a center of excellence in cyber-physical systems research and education, is developing a new program to train graduate students to make discoveries associated with cyber and the Internet of Things, then translate that knowledge into new technologies, products and services. The Link Lab has earned a $3 million National Science Foundation grant to create the training program, which is expected to become a national model for graduate education in cyber-physical systems.
“Cyber-physical systems have the potential to transform the economy and world,” said Jack Stankovic, Link Lab director, BP America Professor of Computer Science and co-chair of the National Academies of Sciences, Engineering and Medicine’s Committee on 21st Century Cyber-Physical Systems Education. Stankovic was co-author of the committee’s 2016 report that concluded a three-year study of the need for better training in the field.
Lobe’s simple visual interface lets people easily create intelligent apps that can understand hand gestures, hear music, read handwriting, and more.
Technology has already transformed the world we live in. Computers are ubiquitous, from the machines on our desks to the devices in our pockets and in our homes. Now, breakthroughs in artificial intelligence (AI) and deep learning are helping scientists treat cancer more effectively, farmers figure out how to grow more food using fewer natural resources, and give people from different countries the ability to communicate across language barriers.
Of the dozens of companies that have worked with DIU, just two have received multimillion-dollar “prototype-to-production” OTA awards that would enable them to scale their solutions across an entire agency or department-wide. Yet this approach has attracted controversy.
In February, the Pentagon issued a $950 million fast-track award to REAN Cloud LLC, only to scale it back to $65 million one month later, amid outcry from competitors and reports of poor coordination between DIU and Pentagon leadership. The contract was revoked altogether in late May after the Government Accountability Office sustained a bid protest from Oracle Corp., ruling that the Pentagon should put the contract to a competitive bid.
GAO’s decision has left the Pentagon’s nontraditional suppliers in a state of limbo. Officials remain reluctant to issue production-scale OTA awards out of a fear of inviting scrutiny from GAO or Congress. Meanwhile, few startups possess the experience and financial flexibility to navigate a months-long competitive bidding process.
New York, NY September 24, starting at 9 a.m., New York University Kimmel Center (60 Washington Square South, Suite 605). [free, registration required]
This open challenge, which will award up to $750,000 to a range of projects, is seeking fresh and experimental approaches to four specific problems at the intersection of AI and the news:
