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A comment on Empiricism and the limits of gradient descent. Parent comment

Re:Empiricism and the limits of gradient descent by joe_the_user on Sunday May 27, 2018 @11:08PM (#17170395)
Given sufficient data, according to the Universal Approximation Theorem, a neural network can learn to model physics.

The ability of a system of linked functions to approximate any continuous function seems rather far from the ability to "learn modern physics".

It would seem like knowing modern physics would involve symbolic calculations rather than just approximating the behavior of any system.

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Re:Empiricism and the limits of gradient descent by AstralStorm on Monday May 28, 2018 @03:45AM (#17171124)
A lot of physics is functions with singularities. ANN can only approximate these to a specified limit...

I want to see a neutral network that correctly solves SAT-3.

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