I feel compelled to repeat the previous criticism on the games: - Stockfisch was never designed nor tested on so many cores. Running on 44 cores may degrade the

I feel compelled to repeat the previous criticism on the games: - Stockfisch was never designed nor tested on so many cores. Running on 44 cores may degrade the performance of Stockfish. - Stockfish was designed to start a game with an opening book. In games with opening book, Stockfish has won significantly more games, too. - Stockfish 8 was not a particularly good implementation. Stockfish 9 or 10 should be a better choice, though. Nevertheless, the performance of AlphaZero was impressive, especially the positional knowledge it has acquired is second none. In all existing chess engines, positional knowledge is under-represented through simple heuristics. Acquiring positional knowledge was a longtime dream of chess programmers many generations. The dream was to create an engine which plays a more human-like style of chess. AlphaZero has realized this dream and even goes beyond that: extending the humans knowledge of chess. I believe the most intriguing question right now is why AlphaZero stopped to improve after 9 hours of training? It’s due to the inherent problem of chess or due to the limits of ANN? If it’s the latter, how we can breakthrough and create a new generation of engines that can even surpass AlphaZero?