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There are no ‘loss functions’, our brain doesn’t optimize in machine learning sense

• visarga 8y ago
  I think that if it learns, it must have loss functions. We just don't know how they are implemented. If we did, we could replicate the brain priors. They are probably distributed, unlike ML loss functions which distill everything to a single number.
  • bra-ket 8y ago
    well if it learns by remembering sets of features and matching new stimuli against this "database" than we can talk about distance functions in associative memory, and the problem of optimization reduces to a problem of matching (as well as generalizing, i.e constructing abstract representations from simpler ones, as in "chunking"). brain priors would be the distributed representations of stimulus-response pairs stored in memory