- Shmoocon 2016 Videos (Internet Archive) — videos of the talks from an astonishingly good security conference.
- TipTalk — Samsung watchstrap that is the smart device … put your finger in your ear to hear the call. You had me at put my finger in my ear. (via WaPo)
- Ecorithms — Leslie Valiant at Harvard broadened the concept of an algorithm into an “ecorithm,” which is a learning algorithm that “runs” on any system capable of interacting with its physical environment. Algorithms apply to computational systems, but ecorithms can apply to biological organisms or entire species. The concept draws a computational equivalence between the way that individuals learn and the way that entire ecosystems evolve. In both cases, ecorithms describe adaptive behavior in a mechanistic way.
- Dataflow/Beam vs Spark (Google Cloud) — To highlight the distinguishing features of the Dataflow model, we’ll be comparing code side-by-side with Spark code snippets. Spark has had a huge and positive impact on the industry thanks to doing a number of things much better than other systems had done before. But Dataflow holds distinct advantages in programming model flexibility, power, and expressiveness, particularly in the out-of-order processing and real-time session management arenas.
The O’Reilly Data Show podcast: Vasant Dhar on the race to build “big data machines” in financial investing.
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In this episode of the O’Reilly Data Show, I sat down with Vasant Dhar, a professor at the Stern School of Business and Center for Data Science at NYU, founder of SCT Capital Management, and editor-in-chief of the Big Data Journal (full disclosure: I’m a member of the editorial board). We talked about the early days of AI and data mining, and recent applications of data science to financial investing and other domains.
Dhar’s first steps in applying machine learning to finance
I joke with people, I say, ‘When I first started looking at finance, the only thing I knew was that prices go up and down.’ It was only when I actually went to Morgan Stanley and took time off from academia that I learned about finance and financial markets. … What I really did in that initial experiment is I took all the trades, I appended them with information about the state of the market at the time, and then I cranked it through a genetic algorithm and a tree induction algorithm. … When I took it to the meeting, it generated a lot of really interesting discussion. … Of course, it took several months before we actually finally found the reasons for why I was observing what I was observing.