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 accept that but now I have a provocative question. is deep learning possible outside the context of artificial neural networks?
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Yes, of course. CNNs are just the most popular area right now. I am wondering about a paradigm where each individual unit is an evolving reinforcement learner that utilizes an arbitrary shader program.
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There are many ways of doing that beyond regression, such as Monte Carlo, evolutionary algorithms, enumeration etc.
End of conversation
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is Monte Carlo Tree Search compositional function approximation?
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