[hyperbovine]

It's not really that deep, imo: a typical deep net these days has O(10^8) parameters (e.g. http://stackoverflow.com/questions/28232235/how-to-calculate...). You can store a hell of a lot of patterns in that many parameters, making them the best pattern matchers the world has ever seen. (Un)fortunately, pattern matching != intelligence. More interesting deep questions for which there is precious little theory revolve around the design of the networks themselves.

[shostack]

Is "pattern matching != intelligence" what occurred when the Google image recognition stuff in the news recently was shown to recognize the pattern of a "dumbbell" as always having a large muscular arm attached to it?

Seemed like a great way to highlight the limitations of patterns.

[hyperbovine]

I hadn't heard about that but it sounds like what I'm talking about. With their ever expanding training corpus Google's net will eventually learn that dumbbells and arms are separate entities, but it will never deduce that on its own. And if it did it would not be able to generalize that to the fact that wedding rings and fingers are different (I hypothesize). Basically there is a whole other component of "intelligence" that feels absent from neural nets, which is why visions of AI lording over humanity don't exactly keep me up at night. (Autonomous weapons otoh...)