The difference is that ANNs make approximations. It could be manageably small and learn an approximation of the PRNG code that succeeds for a large number of outputs, even if running a fully accurate network is impossible. I think the complexity of the PRNG recursive algorithm , when unrolled through time for large number of steps, is the relevant complexity here. The ANN is not necessarily trying to devise a new function that recovers the seed.