NYU Data Science newsletter – January 19, 2016

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Loose pieces of DNA course through our veins. As cells in our body die, they cast off fragments of genes, some of which end up in the bloodstream, saliva and urine.

Cell-free DNA is like a message in a bottle, delivering secrets about what’s happening inside our bodies.

… “I don’t think you can state it strongly enough,” says David van Dyk, a member of the American Statistical Association. “I’m not sure what the future will hold. That is to say, it could be a big data bubble. It could be that our hopes are getting too high and people will turn to something else because it [big data] really has a life of its own.

From Apple’s Siri to Honda’s robot Asimo, machines seem to be getting better and better at communicating with humans.

But some neuroscientists caution that today’s computers will never truly understand what we’re saying because they do not take into account the context of a conversation the way people do.

Hi, my name is John Hammersley and I am the co-founder of Overleaf, a collaborative writing and publishing system that makes the whole process of producing academic papers quicker for authors and publishers. In a previous life I worked on the first passenger trials for Heathrow’s Driverless Car and I have a PhD in Mathematics. I am here today to discuss successful career transitions and my shift from academia to industry, and then to an academic industry.

Without getting into identifiable details, here’s what’s happening so far in a search I’m co-chairing for the Harvard FAS Center for Systems Biology, together with Sharad Ramanathan, with some thoughts on how this process works.

We got 182 applications. The applicants are remarkably strong, which is great. I thought that in an open application process we’d get more of a range of qualifications. Apparently people self-select pretty strongly.

The National Institutes of Health today launched the Centers for Common Disease Genomics (CCDG). With funding from the National Human Genome Research Institute (NHGRI), and the National Heart, Lung, and Blood Institute (NHLBI), the new CCDG centers could receive $260 million over four years.

In addition, NIH announced the expansion of the Centers for Mendelian Genomics (CMG). With funding from the National Human Genome Research Institute (NHGRI), the National Heart, Lung, and Blood Institute (NHLBI), and the National Eye Institute (NEI), the CMG will receive about $49 million over four years. A new Coordinating Center will receive approximately $4 million to facilitate research collaborations among the program grantees over four years, and to contribute to data analysis and program outreach.

CCDG will explore the genomic contributions to common diseases such as heart disease, diabetes, stroke and autism. CCDG researchers plan to develop approaches for using genome sequencing to study common disease more broadly. By sequencing an expected 150,000 to 200,000 genomes of individuals with these diseases, the CCDG program hopes to improve understanding of how genomic differences among people influence disease risk and develop models for future studies of common disease.

More than half of major new business processes and systems will incorporate some element of the Internet of Things (IoT) by 2020, according to Gartner.

The impact of the IoT on consumers’ lives and corporate business models is rapidly increasing as the cost of “instrumenting” physical things with sensors – and connecting them to other devices, systems and people – continues to drop, the analyst firm said.

The history of artificial intelligence has been marked by seemingly revolutionary moments — breakthroughs that promised to bring what had until then been regarded as human-like capabilities to machines.

The AI highlights reel includes the “expert systems” of the 1980s and Deep Blue, IBM’s world champion-defeating chess computer of the 1990s, as well as more recent feats like the Google system that taught itself what cats look like by watching YouTube videos.

But turning these clever party tricks into practical systems has never been easy. Most were developed to showcase a new computing technique by tackling only a very narrow set of problems, says Oren Etzioni, head of the AI lab set up by Microsoft co-founder Paul Allen. Putting them to work on a broader set of issues presents a much deeper set of challenges.

Denver will become a smart city by improving energy efficiency, water conservation, public safety, healthcare and other public services. And Panasonic Corp. of North American will provide the technology to help the city achieve its goals.

“We want to make it a smarter, more sustainable place to live, to travel, and to work,” said Joseph Taylor, CEO of Panasonic North America, at CES last week.

Panasonic’s CityNow approach, which is based on the company’s experience in smart city planning and integration around the world, will be the linchpin of the company’s initiatives in the Denver metro area.

The picture above is not actually a map of the topography* (height variation) of the Indian Ocean seafloor, as much as it looks like it.

It’s actually a map of the change in the Earth’s gravity field across the Indian Ocean seafloor, and it’s so cool I can hardly stand it.

Why is it cool? For a lot of reasons. One is how it was made: using data from a bunch of different satellites, including Jason-1 and CryoSat-2.

The New York Genome Center (NYGC) has been awarded $40 million, over four years, from the National Human Genome Research Institute (NHGRI), a division of the National Institutes of Health (NIH), to create a Center for Common Disease Genomics (CCDG), which will establish a collaborative large-scale genome sequencing program.

Last week, car companies from around the world lined up at the Consumer Electronics Show (CES) in Las Vegas to announce their latest technology and investment in autonomous driving.

General Motors said that it would spend $500 million with car-hailing service Lyft to build “an integrated network of on-demand autonomous vehicles in the US”. Toyota is building a new research institute to work on autonomy, while Audi, BMW, Ford and others also announced progress in their efforts to develop driverless cars. Mercedes has developed a self-driving research vehicle (pictured) and taxi app Uber has already announced billions of dollars in autonomous car investment

In this special guest feature, Miles Johnson and Sam Hochgraf of IBB Consulting Group, discuss how to build small, highly-specialized teams of experts that can work collaboratively to support the data science pipeline.

Last May I was working on hobby project similar to this: https://github.com/zakjan/cert-chain-resolver/ . As I found the cert-chain-resolver project a couple of days later I did nothing with the results, but I got some nice comments on how I used 1 VM to download & process 10TB in a couple of hours on this HN thread recently so I decided to do a write up on the process and publish the data.