Iddo Drori, CDS Adjunct Associate Professor, Kyunghyun Cho, Assistant Professor of Computer Science and Data Science, Claudio Silva and Juliana Freire, Professors of Data Science, Computer Science, and Engineering, Remi Rampin, CDS Research Engineer, and Yamuna Krishnamurthy, Raoni de Paula Lourenco, Jorge Piazentin, NYU Tandon School of Engineering, contributed to the recent paper, AlphaD3M: Machine Learning Pipeline Synthesis.
A personalized approach. That’s what the new Institute for Precision Nutrition, Responsive Agriculture and Health is seeking for consumers.
“We’re working toward a technology where you can eat something and then pick up your smart phone and learn how your body has responded to it,” said Susan Ballabina, deputy vice chancellor of Texas A&M AgriLife. [video, pre-roll + 3:22]
In 2018 we published a paper that showed how machine learning, when applied to medical records, can predict what might happen to patients who are hospitalized: for example, how long they would need to be in the hospital and, if discharged, how likely they would be to come back unexpectedly. Predictive models of various kinds have already been deployed in hospital settings by others, and our work aims to further improve potential clinical benefit by using new models that can make predictions faster, more accurate, and more adaptable for a broader range of clinical contexts.
Any endeavor to demonstrate the promise of machine learning requires intense collaboration between engineers, doctors, and medical researchers to make sure the work benefits patients, physicians, and health systems, and that it is equitable. Google is already fortunate to partner with some of the best academic medical centers in the world and we are now expanding this work to include Intermountain Healthcare, based in Utah.
The Mastercard Center for Inclusive Growth and The Rockefeller Foundation today announced Data Science for Social Impact. This transformational model for collaborative philanthropy will accelerate the use of data science by empowering non-profit, civic and government organizations with the tools, expertise and other capabilities they need to help solve the world’s most pressing challenges.
The collaborative was announced at the World Economic Forum’s Annual Meeting in Davos, Switzerland, with an initial commitment of $50 million from The Rockefeller Foundation and the Mastercard Impact Fund over five years and an invitation to other companies and philanthropies to join.
In a world full of data, how do we maximize the benefits and minimize the costs? And who is in the best position to see the broader picture?
I’m surely biased, but I believe universities have a responsibility to lead the way.
To be clear: This is not something universities can or should do alone. Companies need to make sure the data they generate is used well, and governments have a role to play, too — supporting research and preventing abuse.
A collaboration between Google and Adrian College is gaining steam to offer computer and data science courses to its undergraduate students.
Adrian College is one of only eight schools in the United States, and the only college in Michigan, collaborating with Google on courses aimed to increase undergraduate access to quality computer and data science education by leveraging new technologies and teaching techniques, according to a news release.
Coursera, the global online learning leader, announced the launch of its health vertical – a broad portfolio of health content from the world’s top universities curated specifically to help address the acute shortage of skilled workers in the health industry and meet the demands of a digital health economy.
University of Michigan, Michigan Institute for Data Science (MIDAS)
from
H.V. Jagadish has been appointed director of the Michigan Institute for Data Science (MIDAS), effective February 15, 2019.
Jagadish, the Bernard A. Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan, was one of the initiators of an earlier concept of a data science initiative on campus.
Last April, famed writer and hero-murderer George R.R. Martin announced that he was hoisting his ancient blog from his moldering LiveJournal onto his personal website. For casual Game of Thrones fans, it was a minor hiccup at best—most clicked the new link and never looked back. For a certain strata of enthusiasts, however, this was a far more momentous move. Described as “the last holdout” by longtime LiveJournal volunteer-turned-employee Janine Costanzo, Martin’s blog was perhaps the once-blogging-giant’s last bond to the world of great pop culture. So while the author may never finish his most beloved literary series, his simple act of Web hosting logistics truly marks the end of an era.
Growing up on the Web at the dawn of the social media age (circa 2007), it felt like all the connectivity-obsessed sites forming the burgeoning core of the new Internet were haunted by a faded spectre called LiveJournal. As a teen, I never actually knew anyone who had one, but I heard whispers and rumors about drama on the service all the time. And based on candid conversations with some of the figures who made LiveJournal what it was, it turns out that impression isn’t far off.
AI also could help companies create the perfect candy bar. Last year, Google used AI to find the perfect chocolate chip cookie recipe, according to Business Insider.
“Using artificial intelligence and a technique called ‘Bayesian Optimisation,’ the team spent two months trying to design the perfect chocolate chip cookie,” the article explains. “The team gave a computer a series of ingredients, without any other information, and told it to simply bake a cookie.”
Sales in the U.S. are at a nine-year high. One thing Jeff’s presentation made abundantly clear is that the company plans to keep those numbers up with artificial intelligence.
Personalization
Say sales were abnormally low at one store because a supplier shipped items late. In the past, that anomaly would take several days to identify. An internal analytics platform called the Flight Deck can figure out in minutes.
Many of today’s entrepreneurs live by Facebook founder Mark Zuckerberg’s now-famous motto: “Move fast and break things.” Zuckerberg intended for this to inform internal design and management processes, but it aptly captures how entrepreneurs regard disruption: more is always better. We raced to put our products into consumers’ hands as fast as possible, without regard for the merit of—and rationale for—offline systems of governance. This is increasingly untenable.
Larry Fink’s 2018 letter to CEOs articulated the need for a new paradigm of stakeholder accountability for businesses across the spectrum. In the technology sector, venture capitalists must play a role in driving this change. The technologies of tomorrow—genomics, blockchain, drones, AR/VR, 3D printing—will impact lives to an extent that will dwarf that of the technologies of the past ten years. At the same time, the public will continue to grow weary of perceived abuses by tech companies, and will favor businesses that address economic, social, and environmental problems.
In short, the “move fast and break things” era is over. “Minimum viable products” must be replaced by “minimum virtuous products”—new offerings that test for the effect on stakeholders and build in guards against potential harms.
Despite pouring billions into programs meant to spur innovation, Canada is lagging behind the developed world when it comes to its innovation performance, according to a Fraser Institute report.
The report, Innovation in Canada: An Assessment of Recent Experience, by Fraser Institute resident scholar Steven Globerman and senior fellow Joel Emes compares two key innovation indices (the World Economic Forum’s Global Competitiveness Report and Cornell University and INSEAD’s Global Innovation Index) to measure Canada’s performance when it comes to innovation.
According to the report, which was released last Tuesday, Canada’s ranking on the global indices is the lowest since 2011 and 2008, indicating that the gap between Canada and the developed world is growing.
“Are you interested in joining a community of practice and learn from your peers regarding their approaches for data sharing while sharing your expertise and experience?”
“If you have a technical background, this is your chance to step up as a volunteer leader, help influence the direction of ODK 1 (Collect, Build, Aggregate, Briefcase, JavaRosa, XForms), and help us grow! If you are interested in this opportunity or the process, read on for more important information.” Deadline for solicitations is January 31.
While diverse thinking and disagreements can be uncomfortable, they are more likely to lead partners or a team to make progress, innovate, and come up with breakthrough solutions than consensus and “nice” conversations in which people hold back what they think.
In theory this means that a group such as, say, the U.S. Congress, ought to be pretty good at solving problems. The hundred members of the U.S. Senate come from 50 different states and several generations and should thus have a variety of viewpoints. (Perhaps they still don’t have enough variety, but we’ll leave that discussion for another day.) And boy do they argue. But the way they argue is rife with intellectual dishonesty. And the “rules” that govern their debates, especially on television, are ineffective at encouraging productive debate.
Unfortunately, most of the rest of us fall into similar pitfalls. We get sucked into trying to “win”— so we look good or don’t make the group we represent look bad — which leads us to ignore logic and evidence that go against our original beliefs. And so we fight without making much progress.
We can change this dynamic, moving toward more effective discourse (exchanging diverse ideas) and debate (arguing honestly for and against the merits of those ideas), by training people to adopt the right habits. Here’s how.
[Sibrina] Collins is a rare example of a scientist willing to speak on the record to Nature about her tenure denial. Over four months, just seven scientists agreed to speak to Nature about their experiences; of these, two requested anonymity for themselves and for the institutions that denied them tenure. (“This took place 30 years ago and it still brings up hugely negative feelings,” one anonymous interviewee wrote.) Many declined to be interviewed, citing litigation, non-disclosure agreements, stigma and ongoing trauma. Others ignored e-mailed interview requests.
Researchers who agreed to speak on the record say that it is crucial that scientists maintain an active professional network, be as visible as possible through attending and speaking at conferences and within their institutions, and remain open to all career paths.
To accelerate the transfer of natural language processing (NLP) applications to many more languages, we have significantly expanded and enhanced our LASER (Language-Agnostic SEntence Representations) toolkit. We are now open-sourcing our work, making LASER the first successful exploration of massively multilingual sentence representations to be shared publicly with the NLP community. The toolkit now works with more than 90 languages, written in 28 different alphabets. LASER achieves these results by embedding all languages jointly in a single shared space (rather than having a separate model for each). We are now making the multilingual encoder and PyTorch code freely available, along with a multilingual test set for more than 100 languages.
Over-checking email wastes 21 minutes per day. On average, professionals check their email 15 times per day, or every 37 minutes. Do most people expect a response within that time frame? No. In fact, only 11% of customers/clients and 8% of coworkers expect a response in less than an hour. But about 40% of people expect a response in about an hour. If people checked their email hourly rather than every 37 minutes, they could cut six email checks from their day.