Something weird is happening with LLMs and chess

I don't understand why educated people expect that an LLM would be able to play chess at a decent level.

It has no idea about the quality of it's data. "Act like x" prompts are no substitute for actual reasoning and deterministic computation which clearly chess requires.

This is a puzzle given enough training information. LLM can successfully print out the status of the board after the given moves. It can also produce a not-terrible summary of the position and is able to list dangers at least one move ahead. Decent is subjective, but that should beat at least beginners. And the lowest level of stockfish used in the blog post is lowest intermediate.

I don't know really what level we should be thinking of here, but I don't see any reason to dismiss the idea. Also, it really depends on whether you're thinking of the current public implementations of the tech, or the LLM idea in general. If we wanted to get better results, we could feed it way more chess books and past game analysis.

LLMs like GPT aren’t built to play chess, and here’s why: they’re made for handling language, not playing games with strict rules and strategies. Chess engines, like Stockfish, are designed specifically for analyzing board positions and making the best moves, but LLMs don’t even "see" the board. They’re just guessing moves based on text patterns, without understanding the game itself.

Plus, LLMs have limited memory, so they struggle to remember previous moves in a long game. It’s like trying to play blindfolded! They’re great at explaining chess concepts or moves but not actually competing in a match.

> but LLMs don’t even "see" the board

This is a very vague claim, but they can reconstruct the board from the list of moves, which I would say proves this wrong.

> LLMs have limited memory

For the recent models this is not a problem for the chess example. You can feed whole books into them if you want to.

> so they struggle to remember previous moves

Chess is stateless with perfect information. Unless you're going for mind games, you don't need to remember previous moves.

> They’re great at explaining chess concepts or moves but not actually competing in a match.

What's the difference between a great explanation of a move and explaining every possible move then selecting the best one?

>Chess is stateless with perfect information. Unless you're going for mind games, you don't need to remember previous moves.

In what sense is chess stateless? Question: is Rxa6 a legal move? You need board state to refer to in order to decide.

They mean that you only need board position, you don't need the previous moves that led to that board position.

There are at least a couple of exceptions to that as far as I know.

Yes, 4 exceptions: castling rights, legal en passant captures, threefold repetition, and the 50 move rule. You actually need quite a lot of state to track all of those.

It shouldn't be too much extra state. I assume that 2 bits should be enough to cover castling rights (one for each player), whatever is necessary to store the last 3 moves should cover legal en passant captures and threefold repetition, and 12 bits to store two non-overflowing 6 bit counters (time since last capture, and time since last pawn move) should cover the 50 move rule.

So... unless I'm understanding something incorrectly, something like "the three last moves plus 17 bits of state" (plus the current board state) should be enough to treat chess as a memoryless process. Doesn't seem like too much to track.