Reinforcement learning Chess experiments

Hi chess.com

There is an interesting code for reinforcement learning chess available on github at

https://github.com/Zeta36/chess-alpha-zero/tree/master/src/chess_zero

I have tested it out, it is a good working code. Little older style like alphaGo where policy and value use to have separate neural network unlike google alpha zero where both are combined. On a PC, self-learning is too slow. I  hope chess.com would have enough resources to test this code on GPUs and let it train for at least 2 days and then let it play against stockfish and evaluate the strength.

I am also interested to see, if we let it play (train) against stockfish in self-learning mode, how long it will take to get the strength of Google's alpha-zero. Unfortunately, I don't have enough resources to get the answer.

If anyone of you has resources to test it on Amazon EC2 etc kindly share the results