Show HN: Maia Chess – Human-like chess AI for playing, learning, and more

maiachess.com

7 points by ashtonanderson 20 hours ago

We're thrilled to announce that www.maiachess.com is now in open beta, meaning everyone can access it! Maia is the most human-like chess AI, and is an ongoing research project at the University of Toronto developing fun, useful, and novel human-AI collaboration in chess. Please give it a try and let us know what you think. We're still rapidly improving and iterating on it.

* Play Maia-2: Play the (updated) most human-like chess engine, tailored to your skill level

* Analyze your games: See how you (or the pros!) stack up with both Maia’s human-based predictions and classic Stockfish evaluation

* Try Maia-powered puzzles: Tactics puzzles curated and analyzed through Maia’s unique lens

* Openings drill: Brand new! Select openings, play through them against Maia, and get instant, personalized feedback

* Hand & Brain: Play this fun team variant where you play with Maia as a human-AI team

* Bot-or-not: A chess Turing Test: can you spot the bot in a real human-vs-bot game?

* Leaderboards: See how you rank in each mode, and challenge yourself to climb higher

We’d love your feedback: what works, what doesn’t, what’s missing, or what would make the platform more valuable for you. Join our Discord to chat with us and other users (https://discord.gg/hHb6gqFpxZ).

If you're interested in our research behind Maia, you can check out these papers:

Aligning Superhuman AI with Human Behavior: Chess as a Model System, KDD 2020

Detecting Individual Decision-Making Style: Exploring Behavioral Stylometry in Chess, NeurIPS 2021

Learning Models of Individual Behavior in Chess, KDD 2022

Designing Skill-Compatible AI: Methodologies and Frameworks in Chess, ICLR 2024

Maia-2: A Unified Model for Human-AI Alignment in Chess, NeurIPS 2024

Learning to Imitate with Less: Efficient Individual Behavior Modeling in Chess, under review

unrealdrip 19 hours ago

The bot-or-not mode sounds cool, never seen something like that before.