Linux (Debian/Ubuntu), newer-style Cloud TPU VM.It is not very insightful and often wrong but shows some promise for the limited data it has been able to train on. Stronger neural network evaluations let it search better, and stronger search results let it train its neural network evaluation more effectively.Д¬hessCoach can also feed its chess knowledge into an additional neural network to comment on moves and positions in English. The neural network at the core of the engine is trained by playing against itself, using a feedback cycle to start from almost zero knowledge вЂ“ just the rules of chess вЂ“ and learn new ways to beat itself as it grows stronger. It uses a large, slow neural network just like AlphaZero or Leela Chess Zero (Lc0) to evaluate each position, unlike classical engines which aim for speed with a much simpler evaluation, or more recent NNUE engines, which are a stronger hybrid of both styles. It plays chess with a rating of approximately 3450 Elo, which means it should usually beat even the strongest human players at 2850 Elo, and many other engines, but will often lose to the strongest, such as Stockfish 14 at 3550 Elo.ДЄs with all engines, ChessCoach relies on examining millions of chess positions to decide on the best move to play.

On Lichess: Watch | Stats | Challenge (1+0 or 0+1 up to 15+10) OverviewД¬hessCoach is a neural network-based chess engine capable of natural-language commentary.

Endgame tablebase search or explorer