> In addition to what the author mentions, there is an entirely separate issue: whether or not what you're attempting to do is possible with the approach you've

> In addition to what the author mentions, there is an entirely separate issue: whether or not what you're attempting to do is possible with the approach you've chosen. I had a fun project I tried once. I wanted to see if a neural network could be fed a Bitcoin public key and output the private key. To make things simple, I tried to see if it could even predict a single bit of the private key. 256 bits of input, 1 bit of output. I created a set of 1000 public/private key pairs to act as the test set. Then, I looped, generating a new set of 1000 key pairs, trained for several epochs, then tested on the test set. After 3 days of training (granted, on a CPU several years ago), the results on the test set did not converge. Nearly every trial on the test set was 47-53% correct. I think I had one run that was 60% correct, but that was likely pure lock. Do enough trials of 1000 coin flips and you'll likely find one where you get at least 600 heads. Back to your original comment...Is what I was attempting to do even possible? Did my network need more layers? More nodes per layer? Or was it simply not possible? Based on what I know about cryptography, it shouldn't be possible. A friend of mine said that for a basic feed-forward neural network to solve a problem, the problem has to be solvable via a massive polynomial that the training will suss out. Hashing does not have such a polynomial, or it would indicate the algorithm is broken. But I still always wonder...what if I had a bigger network...