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Neural networks are universal function approximators, not Turing machines. They can theoretically learn any series of "if...then..." functions with enough neuro
by Houshalter 12y ago
Neural networks are universal function approximators, not Turing machines. They can theoretically learn any series of "if...then..." functions with enough neurons. But there are a lot of functions they can't represent very efficiently or without absurdly large numbers of neurons and training data.
- a-priori 12y agoYes, but computation can be performed with a function approximator where each iteration is a function `f :: (state, input) -> (state', output)`. This is the basis of an architecture called a 'neural turing machine' (http://arxiv.org/abs/1410.5401 http://arxiv.org/abs/1410.5401) and it is, indeed, Turing complete and can be trained through standard neural network training algorithms to perform arbitrary computations.