Check out https://github.com/glinscott/leela-chess. We are getting close to kicking off the distributed version now that we have validated it's possible to get a strong network through supervised training.
Question : when you switch to self-play reinforcement learning, do you plan on starting from the networked obtained in supervised learning or tabula rasa? I understand starting from tabula rasa will require more comptuting power/time, but if you start from the supervised learning network, isn't there a risk you inherit human biases in the game style? It would also defeat the purpose of having the system discover existing chess theory and possibly new one.
A nice win against Gnuchess (a very weak opponent, but nonetheless :) - https://github.com/glinscott/leela-chess/issues/47#issuecomm...