Betafish (gavinong.com)

A developer has successfully built "Betafish," an innovative JavaScript chess engine that combines elements from the renowned chess algorithms AlphaZero and Stockfish. Initially inspired by the surge in chess popularity during the pandemic, the creator aimed to develop an AI that could reliably defeat them in the game. Betafish boasts an estimated Elo rating of approximately 2000, having performed well against strong opponents on chess platforms like Lichess and chess.com. It employs a Negamax search algorithm with advanced techniques such as move ordering, quiescence search, and alpha-beta pruning, enabling it to process around 800,000 nodes per second and pass various chess position tests. The creation of Betafish is significant for the AI/ML community as it illustrates practical applications of AI in understanding and mastering complex strategies in games like chess. Through detailed exploration of algorithms like Minimax and enhancements like tapered evaluation and iterative deepening, the developer highlights the intricate considerations required for effective chess AI programming. The project serves not only as a platform for further development—such as potential implementation of an opening book and rewriting the engine in a compiled language for performance gains—but also as a learning resource for both enthusiasts and newcomers interested in the intersection of AI and game development.