  Neural networks are being used to improve the probing of the state spaces of
many particle systems as approximations to wavefunctions and in order to avoid
the recurring sign problem of quantum monte-carlo. One may ask whether the
usual classical neural networks have some actual hidden quantum properties that
make them such suitable tools for a highly coupled quantum problem. I discuss
here what makes a system quantum and to what extent we can interpret a neural
network as having quantum remnants.
