Deep networks probably mostly just memorize and regurgitate their training data. This seems likely all that AlphaGo Zero does, for instance.
Relevant post from @nostalgebraist
@xuenay
http://ift.tt/2t36Ix2 pic.twitter.com/UCaeQaoT3S
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Well… the question is to what extent there actually is a higher level feature space. In the image recognizers, there is, although I think to a lesser degree than is usually supposed. In other applications, maybe not much at all.
sure, but at least for images do you think that feature space counts as a success for NN? or is it just a fluke bc images are fundamentally easier/different than other domains? can see the argument we've figured out the magic of visual cortex and are now misapplying it everywhere
[I’ll leave @nostalgebraist & @xuenay out of follow up to avoid spamming their mentions]
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