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I have a hash, e.g. 552c51576e2a6dec462b0d56af8c31713e26a763c0e2a3d48ebbf4b99958eeba. This hash hashed again, is 39f20b3e5cc0181d6fbe2a4d52c7b3c315e8526e35da3cd0b18e25d10b670dc3.

Now I only know the last hash 39f20b3e5cc0181d6fbe2a4d52c7b3c315e8526e35da3cd0b18e25d10b670dc3. It matches value 1.58. I do not know the first hash, as this is a security feature (that all hashs are generated and we go from top to bottom to not re-calculate the hashes).

A new round starts. last round had hash 39f20b3e5cc0181d6fbe2a4d52c7b3c315e8526e35da3cd0b18e25d10b670dc3 and resulted with 1.58. The next round does not reveal the hash at the start, but I want to guess the resulting value already, which should be 4.06. When the values gets revealed, I also get the hash.

Do you understand what I want to achieve?

I have a hash of a hash, which results in a value. Now, my AI system should predict the next value which is based on the hash which got hashed and then resulted in e.g. 1.58. I know a 'next hash' of the current input hash (which I don't know) and the 'previous' value of the 'next' hash. Then, I want to guess the current value (without knowing its hash already).

Any idea how I could implement this in python or what method or keyword I should do research on? I am absolute new to AI and do not know what I need to look up for that project.

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  • $\begingroup$ The wording of this question is very confusing, so I might not fully understand. But in the event that you are essentially trying to predict a value that is derived from a hash produced by some hashing function, current day neural networks will never be able to achieve this. It's not possible. If they could, someone would have won one of the millennium awards for showing P=NP, which has not happened. $\endgroup$ – Recessive Feb 5 at 5:32

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