An AGI prediction on the bold end (5 years, because Deep Learning carries us all the way), by @IntuitMachinehttps://medium.com/intuitionmachine/near-term-agi-should-be-considered-as-a-possibility-9bcf276f9b16 …
What second incarnation do you have in mind? I suspect that it may be a thesis that concerns universal function approximators. Is there a class of computable functions that can effectively approximate all computable functions, and how big is the subset of efficient approximators?
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I was actually referring to the idea that neural networks can approximate any computable function, which as far as we known is sound.
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Are you sure? What if the search space is very high dimensional and discontinuous?
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