NYU Data Science newsletter – August 27, 2015

GROUP CURATION: N/A

One of the most crucial pieces of the James Webb Space Telescope, the flight backplane, arrived on Aug. 25, on schedule for Webb’s 2018 launch date at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, for mirror assembly. The backplane is the “spine” of the telescope, responsible for holding its 18 hexagonal mirrors and instruments steady while the telescope is looking into deep space.

African countries may be coming late to the information revolution, but they will be able to exploit the lessons learned from those that have trodden the path before. The UK’s attempt to centralise its health system was an expensive failure. African countries don’t now need to spend £10bn to learn the lessons derived from that misguided effort. They could develop infrastructures for commerce, administration and health that exploit all the advantages of a distributed data system.

Recent initiatives by the White House for a data-driven government like the Precision Medicine Initiative and the Police Data Initiative demonstrate the nation’s progress in open and responsible data use, according to a recent memo by DJ Patil, U.S. chief data scientist in the Office of Science and Technology Policy.

In his memo, Patil outlined the work his team has been doing to create federal data policies to make shared services possible, collaborate with federal agencies to fulfill these goals, recruit top technologists in data science and build long-term sustainability.

One company hopes to come up with something a lot smarter by providing a platform that lets software learn how to behave within a game, whether in response to basic stimuli or to more complex situations. The hope is that this kind of learning will eventually allow complex behavior to emerge in game characters—and make for better AI in a range of applications.

Keen Software, based in the Czech Republic and the U.K., makes several “sandbox” games in which players can construct complex virtual structures and machines using realistic materials and physics. This July, the company spun out a business called GoodAI that aims to develop sophisticated AI using machine learning. Marek Rosa, Keen’s CEO, invested $10 million of his own money in the new company.

Face it: Siri sucks. So often, she has no clue what you’re saying. And when she does, there’s a pretty good chance she’ll respond with nothing more than a page filled with Internet links.

Part of the problem is that Apple’s talking digital assistant is built on old technology. But even if the company upgrades Siri to the latest in artificial intelligence, she’ll fall well short of an assistant made of flesh, blood, and neurons. As far as artificial intelligence has come in the last few years, it’s still a long way from intelligence.

With M, its new virtual assistant, Facebook admits as much.

Joseph Traub, a leading figure in developing the field of computational complexity, passed away Monday morning, August 24, in Santa Fe.

At the time of his passing Traub, 83, was the Edwin Howard Armstrong Professor of Computer Science at Columbia University and an external professor of the Santa Fe Institute.

Are there any instances you know of where alternative data visualization methods have led to breakthroughs in fundamental science?

Let me start at the top – it’s both a good question and a hard one!

I have multiple answers along a continuum of speculation (which is arguably a big word for weaselling) depending on just how high the bar is for ‘breakthrough’.

The most rock-solid answer is the least satisfying: no, I don’t.

Maps are amazing for their ability to show us something we can’t see directly, from the path of the Curiosity rover on Mars, to the tangle of underground fracking wells in North Dakota, to clusters of unvaccinated schoolchildren in California. For journalists, maps can be both a powerful data-visualization tool and a reporting tool.

“Maps are some of the most information-dense ways of communicating data,” says Len De Groot, director of data visualization at the Los Angeles Times. People understand maps intuitively because they use them in their everyday lives, De Groot says. “You can do a lot in a map because people already understand the fundamentals—unlike, say, a scatterplot.”

Contingency theory postulates that leadership style should adjust based on the situation, and I agree. Victor Vroom and Phillip Yetton developed one of my favorite outgrowths from the contingency theory movement in the 1970s, and then Vroom extended his ideas with Arthur Jago in the 1980s. Their model suggests five decision-making styles with varying levels of group involvement. Let’s explore the Vroom-Yetton-Jago model as it applies to leading a modern-day data science team.