Disregarding the /s bc i want to rant

I guess if you described board states in language and got them to recognize chess board states from images (by describing them in language), and trained them on real games, you could probably make a really inefficient chess bot.

But that said, you could use an "agentic" model with an mcp to route queries about chess to an api that links the LLM to an actual chess bot.

Then it'd just be like going to the chess bot website and entering the board states to get the next move. No magic involved, just automated interaction with an api. The hype and fear and mysticism around llms bugs me. The concepts behind how they work aren't hard, just convoluted

A solution for chess exists, but the space is too big to calculate with current technology

Well no, it's not a memorization game. Part of a grandmaster's strategy is deciding when to go "off book" and cause their opponent to have to reason through a position. An attribute of a chess engine like Stockfish is its "depth" which is a measurement of how many permutations it searches through in a tree of possibilities. You get some ridiculous number of permutations very quickly on a chess board.

That's not to say that a competitor doesn't do anything assload of memorization of the "correct" moves as proven in landmark games. But you don't just memorize chess and solve it as such like you can do with tic tac toe. Unrelated but I think a spectrum is fun: tic tac toe, solved, memorizable. Connect 4, solved, unmemorizable. Checkers, surprisingly solved, in your dreams. Chess, unsolved.

Yes, chess can be solved by simply knowing every possible board state. However there's like 10^50 possible positions (we think, it's actually unknown how many possible legal positions there are) and storing that amount of information would require more than the sun's volume in hard drives

No offense, but you're wrong about this.

Machine learning does have valid use cases, and chess (and go and other board games) is one of them. The thing about chess is that there's a definitive win state that the AI is trying to reach. This is a huge difference from language and image models, which require human input to tell them if they're any good or not, and feeding the output back into it makes it more and more gibberish. With chess AI, the goal isn't to play like a human, but to win, which means it can judge it's own output against that metric and train off of that, with no need for human games at all. You can start it off playing random nonsense moves, and then let it run, and it'll play millions of games getting a little better with each one, as fast as the hardware allows. The end result is something much, much better than what any human or brute force algorithm can achieve. Speaking as a go player, AI has completely revolutionized the way we play the game, and I believe the chess world has had a similar experience.

Having said that, there have been some problems with go AI. A while back, somebody discovered a trick that anybody could use to beat otherwise unbeatable AI. It involved intentionally letting a group get surrounded with no way to live, and then surrounding the group surrounding that group in order to kill it. It was a nonsense strategy that any human player would catch on to and subvert, but because it was a bad strategy, the AI never tried it and so it wasn't in its training data. This served as an important reminder that the AI isn't perfect and isn't actually thinking.

However, without exploits like that, nobody, not even the top professionals, have any chance whatsoever of beating a top AI. And that only started being the case with go relatively recently, because the brute force algorithms weren't good enough but the machine learning algorithms were a huge leap forward, and they're getting better and better.

I'm as much of an AI skeptic as the next person, but a W is a W.

If I didn't have an argument with a pro-"AI" (it's not AI, I refuse to call it that) person in my fucking post history about just this fucking issue, maybe I'd be more willing to agree with you here. But no, the people who keep trying to get me to use so-called "AI" seem to believe that it can reason, or, at least, that it can be convinced to reason. So yes, I will use this article to "hate on AI", because the "AI" lovers seem to believe that chatGPT should be capable of something like this. When clearly, fucking obviously, it isn't. It isn't those of us who hate so-called "AI" that are trying to claim that these text predictors can reason, it's the people who like them and want to force me to use them that make this claim.

We're hating on AI right now.

we are, you are correct. but singularity next week or w/e