chess

Proposes DD-Elo, a chess rating system that integrates move-level data via a drift-diffusion model to accelerate skill assessment and rating adaptation, while maintaining alignment with traditional Elo.

An informal experiment using a chessboard reveals that vision language models often fail at spatial reasoning and precise structured output, despite correctly recognizing pieces, highlighting a key gap in VLM evaluation.

Boxwood Chess is a chess pattern training tool without timers, streaks, or ratings.

A user demonstrates using a custom AI skill with a chess engine and game API to fetch recent games, analyze them, and generate personalized lessons with interactive visuals and puzzles.

Wired reviews the best smart chess boards of 2026, focusing on Chessnut and Millennium models, highlighting their electronic features, design, and online play capabilities.

A chess coaching tool that uses an LLM to explain moves in natural language like a grandmaster, replacing raw engine evaluations with contextual coaching narratives. It analyzes user games from Chess.com and Lichess with local Stockfish, detects recurring mistakes, and offers personalized chat and spaced repetition for blunders.

The article models chess as a concurrent system and derives state and transition invariants, demonstrating formal verification techniques using TLA+.

Nicholas Carlini's project implements a 2-ply minimax chess engine using 84,688 regular expressions, executed sequentially to play valid chess moves. The post explains the design of a regular expression computer that interprets instructions.

Trained transformer-based chess models for rating buckets from 800 to 2500+, predicting moves, thinking time, and outcome. Achieves strong accuracy with only 9M parameters, and includes a novel thinking-time prediction component.