Almost all ML is basically searching through a (latent) space of possible answers and indexing the results. So it outperform most known methods. Like when Alpha

Almost all ML is basically searching through a (latent) space of possible answers and indexing the results. So it outperform most known methods. Like when AlphaGo using MCTS beat Rybka, etc. I would be interested to know if ML can be used to reverse hashes, such as to more quickly solve the numbers that satisfy the Bitcoin Hash challenge. Maybe it can even get P and NP closer together! Are there theoretical results on SHA-256 or something that preclude finding an ML algorithm that, with a billion parameters, can speed up the search for a Bitcoin Hash input?