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Comment by foldr | Hacker News Reader

Humans don't need a lot of training and finite tuning to make only legal moves.

An intelligent adult could simply read a short summary of the rules of chess and then, if they were careful, play a very bad game of chess without making illegal moves.

An LLM that has not been trained on any chess data cannot do that, at present. If you doubt it, take a current model and tell it that you want to play it at a variant of chess where, say, knights can also move diagonally like bishops. A human can easily adapt to this new ruleset (even if they make tactical mistakes, not having practiced with this variant of the rules).

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How long a prompt do you think would be required to cajole an LLM into making legal moves at the rate of a human? Or do you think no amount of prompting could do that?

I don't know. My understanding is that current models will eventually fall into making illegal moves in longer chess games, and that no amount of prompting reliably gets them to stop doing so.

I've not noticed this happening if you give it the FEN each move. The alternative is just blindfold chess and very few humans can do that for long.

I haven't tried it myself, but people seem to report that the illegal moves surface eventually. It just takes longer: https://news.ycombinator.com/item?id=49720751

Nothing is forcing the LLM to play 'blind'. If it's smart, it should be able to create its own representation of the chess board and update it with every move, just like a human would. Any chess engine that's sensitive to how the moves are formatted is clearly not very capable.

A human wouldn't do that, they'd look at the board. I'm not disagreeing that to demonstrate clear superhuman ability the LLM should be able to do this, but it plays better than most humans blindfolded, and with fair prompts seems very good otherwise.

That's what a human will do if they already have a physical board to look at. But if someone, say, posed you a chess exam question via FEN notation, or as a sequence of moves in algebraic notation, you'd sketch a visual representation of the board off your own initiative to help you answer the question. There is nothing in principle to stop the LLM creating its own board representations in whatever format enables it to easily keep track of game state and legal and illegal moves. If it fails to do so, that's a sign of its own limited understanding of chess as compared to a human.

The LLM would only be playing 'blindfolded' if you somehow forbade it from making notes (as you effectively do by literally blindfolding a human, given how limited human working memory is). But you are not doing that. The LLM is free to keep track of the game state via whatever means it chooses.

None of this is about superhuman ability. Any human who understands a given chess notation can convert it to a visual representation of a chess board and then use that representation to choose their next move, with their usual level of performance.

I maintain that the amount of effort to teach a human to do this vastly outweighs the amount of effort to teach an LLM to do this unless you're deliberately trying to make them fail. I honestly have no bigger point than that, I just think this isn't a very good thing by which to evaluate LLM capabilities. If there's no argument you'll accept, I am happy to move on.

You don’t need to teach a human anything except the rules of chess and the details of a particular chess notation. No special skill or training is required to make a sketch of a chess board. Surely there is no chess player who, if confronted with a sequence of chess moves in algebraic notation, would not think to construct a representation of the chess board in order to understand what was going on.

> I just think this isn't a very good thing by which to evaluate LLM capabilities

I don’t think any single task is a good way to evaluate LLM capabilities, but I don’t see why chess is worse than a lot of other tasks. (Of course it is of no practical consequence whether LLMs can play chess, so if you are just making that point, then yes, I agree.)

> If there's no argument you'll accept

It’s a little unfair to suggest that I wouldn’t accept any argument whatever for your position just because I haven’t been convinced by your very brief comments so far. I could equally well say the same thing to you!

More importantly, beginner human players don't exhibit that tendency. The history of the position doesn't bother a human (except as required for castling and en passant rules), and the analysis becomes generally easier as pieces come off the board.

Humans do make these errors when playing blindfolded. If you even the playing field and give the LLM the position at each turn, it does not make mistakes.

> If you even the playing field and give the LLM the position at each turn, it does not make mistakes.

It absolutely still makes mistakes if you ask it to draw the board each turn, which should be equivalent to giving it the position because it only has to update one move at a time and then it has the position in the context window.

Yes, we can come up with all sorts of weird situations where you can get it to be confused. But what I'm saying is it's _trivial_ to give it a simple prompt that prevents it from ever making any errors, and so I don't think it's this big LLM gotcha (of which there are many!)

The actual question is backwards: how do we keep the prompt and context small enough so the LLM doesn't start hallucinating basic rules of chess.

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