Cardinal Analytx, a new population health management company founded by Cardinal Partners investor Thomas McKinley based on research from Stanford University, has raised $6.1 million. Cardinal Partners led the round, with participation from the Stanford-StartX Fund and Premera Blue Cross, which also participated in a large pilot study that has provided some initial validation for the company.
The company builds on the research of Dr. Arnold Milstein and Dr. Nigam Shah, whose areas of expertise include managed care and machine learning in healthcare.
Engineers at MIT have devised a framework for identifying key patterns that precede an extreme event. The framework can be applied to a wide range of complicated, multidimensional systems to pick out the warning signs that are most likely to occur in the real world.
“Currently there is no method to explain when these extreme events occur,” says Themistoklis Sapsis, associate professor of mechanical and ocean engineering at MIT. “We have applied this framework to turbulent fluid flows, which are the Holy Grail of extreme events. They’re encountered in climate dynamics in the form of extreme rainfall, in engineering fluid flows such as stresses around an airfoil, and acoustic instabilities inside gas turbines. If we can predict the occurrence of these extreme events, hopefully we can apply some control strategies to avoid them.”
arXiv, Statistics > Methodology; Blakeley B. McShane, David Gal, Andrew Gelman, Christian Robert, Jennifer L. Tackett
from
In science publishing and many areas of research, the status quo is a lexicographic decision rule in which any result is first required to have a p-value that surpasses the 0.05 threshold and only then is consideration–often scant–given to such factors as prior and related evidence, plausibility of mechanism, study design and data quality, real world costs and benefits, novelty of finding, and other factors that vary by research domain. There have been recent proposals to change the p-value threshold, but instead we recommend abandoning the null hypothesis significance testing paradigm entirely, leaving p-values as just one of many pieces of information with no privileged role in scientific publication and decision making. We argue that this radical approach is both practical and sensible.
Economists across the political spectrum agree that the single biggest threat to future job growth is neither immigration nor trade — it’s the artificial intelligence revolution already underway.Studies by Oxford University, McKinsey and Pricewaterhouse Coopers forecast that up to 50% of current jobs could be replaced by smart machines within the next 20 years. Already, more than 5 million U.S. factory jobs have been lost to automation since 2000. It’s become clear: If a job can be automated in the future, it will be.
What’s less clear is how educational institutions — the incubators of human talent — will respond to this sea change in the future of work. Despite being the envy of the world, American universities have been slow to modernize — too often educating students for 20th century career fields that will be obsolete by the time they graduate. Beyond simply conferring degrees, the foundational purpose of colleges and universities must be to educate — and that means equipping people of all ages, at all stages of their careers, to build successful and fulfilling lives. This means we need to take several important steps to make our students robot-proof.
Stephen Hsu reports on his team work to use novel machine learning methods (“compressed sensing”) to ~500,000 genomes from UK Biobank, resulting in an accurate predictor for human height which uses information from thousands of SNPs.
Hsu has also predicted that with the gene sequences of about 1 million people we could construct a good genomic predictor for cognitive ability and identify most of the associated common SNPs.
Logistics giant DHL and tech titan Huawei Technologies will test a Narrowband-IoT (NB-IoT) network to connect trucks carrying parts and other assets to an automotive assembly plant in Liuzhou, China.
The firms expect to expand the tests, which will remain in the proof-of-concept phase until the end of September, to other areas of China once this initial phase is completed. NB-IoT is a low-power, wide-area network (LPWAN) standard designed to connect enterprise IoT devices that use very little power and transmit very little data.
Anaconda, Inc., the most popular Python data science platform provider, today announced it is partnering with Microsoft to embed Anaconda into Azure Machine Learning, Visual Studio and SQL Server to deliver data insights in real time. Microsoft and Anaconda will partner to deliver Anaconda for Microsoft, a subset of the Anaconda distribution available on Windows, MacOS and Linux. Anaconda, Inc. will also offer a range of support options for Anaconda for Microsoft.
This week, we are hosting 27 Facebook PhD Fellows and Emerging Scholars at our Menlo Park headquarters to share their work and network with the broader Facebook and fellowship community. … We had a chance to catch up with three Facebook Fellows whose research ranges from boosting Internet performance to social roles in online communities to addressing global inequality. Here is a little more about them and their research.
Five of New York City’s universities announced today a partnership aimed at supporting and defending journalism and independent news media — one of the most critical elements of our democracy — as they are increasingly under threat. This unique, first-of-its kind program and collaboration will bring together Cornell Tech, Columbia University, City University of New York, New York University, and The New School — in partnership with the NYC Media Lab — to investigate and understand the various threats to journalism and media, and attempt to address these challenges using design, engineering, and computational methods and techniques. The effort will gather graduate students with backgrounds and expertise in journalism, design, and engineering/technology from these institutions in a special course to kick off in Spring 2018.
TheHill, Reps. Elise Stefanik (R-N.Y.) and Scott Peters (D-Calif.)
from
NIH is America’s medical research agency and the largest funder of biomedical research in the world. But between 2003 and 2016, NIH’s purchasing power eroded by nearly 25 percent. That forced NIH to abandon half of its promising research every year, with potentially serious long-term consequences for America’s health and future.
Conservatives and progressives agree that the federal government should do everything it can to cure devastating diseases like cancer and Alzheimer’s. That’s why each year NIH competitively invests in the innovative ideas of researchers across the country.
In the past 4 years, a movement has begun sweeping across the life sciences: the practice of sharing draft papers, known as preprints, online before they are submitted to a journal for peer review. The shift has been catalyzed, in part, by endorsements from high-profile scientists, as well as the 2013 launch of the bioRxiv preprint server by Cold Spring Harbor Laboratory in New York; it now holds more than 15,000 papers. But in contrast to physics, where preprints took off nearly 3 decades ago without much fanfare or controversy, the leap into preprints is stirring strong passions in the hypercompetitive world of the life sciences. Proponents argue that preprints will accelerate the pace of science—and improve its quality—by publicizing findings long before they reach journals. Many biologists remain wary, however. For those debating whether to take the plunge, Science offers this guide.
In reality, that system needs work; Siri still disappoints more often than it delights. But under tightly controlled conditions, it is now possible to visit the conversational future we’ve all been waiting for. The good news is that Siri sounds more human than ever and it’s not creepy at all.
The bad news is that the capital-d Dream of a virtual assistant that manages your digital life while you live your real one is probably a lie. The real problem with voice assistants isn’t that they’re underpowered, or that their neural nets aren’t sophisticated enough to intuit our requests. It’s that user interfaces will always demand your attention—whether they’re graphical, conversational, or, hell, telepathic.
In a typical week, the state Department of Corrections receives a list of 1,000 inmates who need to be assigned to one of its 25 correctional facilities.
The process isn’t straightforward. There are nearly 100 factors that determine where an inmate ends up — from the medical care they require and their age to their family’s proximity to the prison and which programs they need to become eligible for parole.
It used to take seven corrections employees a week to figure out where they would go.
Now, with the push of a button, an algorithm designed by a group of Lehigh University engineering students and their professors assigns the same number of inmates in 10 minutes.
As part of its agreement, Amazon reportedly gets to sell two minutes of ads on its stream per hour. (Other reports say it’s ten 30-second ads, which would equal five minutes total, which would be fewer than two minutes of ads per hour, since the average game lasts for 3 hours 7 minutes; Amazon will not answer which is correct.) The rest of the ads that you’ll see will be the same as the national spots that appear on cable networks.
For the Amazon-only ads, Amazon has sold packages that reportedly cost $2.8 million. It’s unclear exactly how many minutes are included in each package, and Amazon will not share how many separate packages it has sold, but Amazon does say the packages include banner ads elsewhere on Amazon.com, that don’t run during the games.
“Ever since we open sourced Hadoop in 2006, Yahoo – and now, Oath – has been committed to opening up its big data infrastructure to the larger developer community. Today, we are taking another major step in this direction by making Vespa, Yahoo’s big data processing and serving engine, available as open source on GitHub.”
“We are open sourcing Abseil, a collection of libraries drawn from the most fundamental pieces of Google’s internal codebase. These libraries are the nuts-and-bolts that underpin almost everything that Google runs. Bits and pieces of these APIs are embedded in most of our open source projects, and now we have brought them together into one comprehensive project.”
“After almost ten years of development, we have the regret to announce
that we will put an end to our Theano development after the 1.0 release,
which is due in the next few weeks. We will continue minimal maintenance
to keep it working for one year, but we will stop actively implementing
new features.”