"New Theory Cracks Open the Black Box of Deep Learning"

Here is the video of the talk, and here is the associated paper on arXiv.

Geoffrey Hinton, a pioneer of deep learning who works at Google and the University of Toronto, emailed Tishby after watching his Berlin talk. “It’s extremely interesting,” Hinton wrote. “I have to listen to it another 10,000 times to really understand it, but it’s very rare nowadays to hear a talk with a really original idea in it that may be the answer to a really major puzzle.”

Also worth noting: Tishby’s work wasn’t accepted for NIPS 2017.

I have no clue about the likelihood of proposed explanatory theories, but deep learning is one area of computation that I am optimistic about. It is very easy to improve the efficiency of deep learning workloads right now, and it should be straightforward to gradually improve precision in the future.

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