Yann LeCun makes a very clear and honest statement of why Deep Learning is not enough. It's not enough because there are functions that don't emerge intrinsically from the network.https://twitter.com/ylecun/status/1215286749477384192 …
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i asked three questions; i don't quite understand how this answers any of them or which it is intended as an answer to. there's LOTS of handcrafting in deep learning that you seem to be ignoring. Some of the handcrafting may have moved up a later but there is plenty left.
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Treaded discussion is hard on twitter. I agree that many DL solutions are hybrids (and don't think that this is a contested position). Automating architecture search/modification is only just beginning. But NLP and computer vision have basically dumped decades of prior work.
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I agree. This is the essential paradigm shift. That is, the 'handcrafting' is happening at different levels.https://medium.com/intuitionmachine/how-to-grow-the-innate-machinery-for-agi-a5cbbd755eae …
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Yes it was handcrafted before and giving a false sense of generalization. Now it gives a false sense of generation automatically... :)
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