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Note that the question of model choice (the structure of the differentiable architecture used) is rather secondary, because as long as memorization capacity is sufficient, *any* model will do -- if there is training data to match. Even a single hidden Dense layer.
It just moves the threshold for "have we drawn enough data yet" by a bit -- by no more than a few orders of magnitude. But when infinite data is available, this is "just" the size of your cloud computing bill.
Yes, that would be new and significant, but also almost certainly not doable with differentiable programming
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