Earlier quoted context omitted.
Maybe this is dumb/naive, but I've wondered for quite a while - what if you take the latest deep learning/AI techniques and try to train a system to predict the approximate size of the hash from the input number? Has anyone seriously tried and failed?
If you could do it, you'd be famous for more than BTC. It would mean that you could factor numbers in polynomial time. Long story short, calculating the hash for BTC is intended to be a non-polynomial problem. If you can find a method (any method) that will reduce the search space of the answer such that you can calculate it in polynomial time, then you have proved that NP=P (If you can find a way to solve any non-po…
As schoen pointed out, no common hash function, including the ones used in Bitcoin, has a proof of NP-completeness.
Moreover, none of those hash functions involve factoring numbers, and factoring numbers is also not known to be NP-complete, although it is also not known to be tractable in polynomial time. One reason commonly-used proof-of-work functions do not involve integer factorization is that, while integer factorization is not known to be doable in polynomial time, there are a number of algorithms that require subexponential time, so an integer-factorization-based proof-of-work witness would be much larger than an equivalent hash-function-based proof-of-work witness.
Also, it is not the case that efficient integer factorization would completely break all current encryption. Not only do no commonly-used hash functions depend on it, neither do any commonly-used symmetric ciphers (such as AES), and the currently-most-popular asymmetric cryptosystems also do not depend on the difficulty of integer factorization; instead they depend on the difficulty of the elliptic-curve discrete logarithm problem.
ECDLP is also not known to be NP-complete, but the currently-known algorithms for it are much worse than currently-known algorithms for integer factorization, so elliptic-curve cryptosystems require much smaller keys and less computation to resist the known attacks than integer-factorization-based cryptosystems.
As little as ten years ago, algorithms that could be broken by better integer factorization algorithms were relatively much more important than they are today, because elliptic-curve cryptography was much less widely used. Many vulgar accounts of the situation intended for the ignorant are not up to date.
Finally, it is not true that a proof that P=NP would "completely break all current encryption", for two reasons. First, it might not be a constructive proof — it might show that a polynomial-time algorithm for factoring integers, solving ECDLP, or computing hash preimages exists without actually telling you how to compute it. Second, even a constructive proof of P=NP might not provide an algorithm that was adequately efficient — if it takes O(n²) time to encrypt and decrypt, where n is the size of a key, but O(n⁸) time to break a message or a key, you might be adequately safe with, say, RSA-4096. But an O(n⁸) algorithm for 3-SAT would definitely be a constructive proof of P=NP.
(Shor's algorithm on a quantum computer can break RSA, because it does depend on integer factorization, in O(n³) time, if quantum computers can exist, which they probably can. This would not make it impossible to do RSA encryption securely, but it would require much larger keys than are currently used.)
However, your fundamental point is that a successful attack on Bitcoin's hashing algorithm, using artificial neural networks or anything else, would be very surprising and have major implications, because that proof-of-work scheme is designed to require exponential work, and as far as anyone knows, it does. And that fundamental point is correct, even though you have made a number of errors in your supporting points.