Technology

2025 Mazda MX-5 Miata 'got absolutely wrecked' by Inflatable Boat in beginner's boat racing match — Mazda's newest model bamboozled by 1930s technology.

If you don't play chess, the Atari is probably going to beat you as well.

LLMs are only good at things to the extent that they have been well-trained in the relevant areas. Not just learning to predict text string sequences, but reinforcement learning after that, where a human or some other agent says "this answer is better than that one" enough times in enough of the right contexts. It mimics the way humans learn, which is through repeated and diverse exposure.

If they set up a system to train it against some chess program, or (much simpler) simply gave it a tool call, it would do much better. Tool calling already exists and would be by far the easiest way.

It could also be instructed to write a chess solver program and then run it, at which point it would be on par with the Atari, but it wouldn't compete well with a serious chess solver.

this is because an LLM is not made for playing chess

Tbf, the article should probably mention the fact that machine learning programs designed to play chess blow everything else out of the water.

An LLM is a poor computational/predictive paradigm for playing chess.

ChatGPT has been, hands down, the worst AI coding assistant I've ever used.

It regularly suggests code that doesn't compile or isn't even for the language.

It generally suggests AC of code that is just a copy of the lines I just wrote.

Sometimes it likes to suggest setting the same property like 5 times.

It is absolute garbage and I do not recommend it to anyone.

Sometimes it seems like most of these AI articles are written by AIs with bad prompts.

Human journalists would hopefully do a little research. A quick search would reveal that researches have been publishing about this for over a year so there's no need to sensationalize it. Perhaps the human journalist could have spent a little time talking about why LLMs are bad at chess and how researchers are approaching the problem.

LLMs on the other hand, are very good at producing clickbait articles with low information content.

I suppose it's an interesting experiment, but it's not that surprising that a word prediction machine can't play chess.

I swear every single article critical of current LLMs is like, "The square got BLASTED by the triangle shape when it completely FAILED to go through the triangle shaped hole."

LLM are not built for logic.

A strange game. How about a nice game of Global Thermonuclear War?

Can ChatGPT actually play chess now? Last I checked, it couldn't remember more than 5 moves of history so it wouldn't be able to see the true board state and would make illegal moves, take it's own pieces, materialize pieces out of thin air, etc.

Ah, you used logic. That's the issue. They don't do that.

Hardly surprising. Llms aren't -thinking- they're just shitting out the next token for any given input of tokens.

The Atari chess program can play chess better than the Boeing 747 too. And better than the North Pole. Amazing!

All these comments asking "why don't they just have chatgpt go and look up the correct answer".

That's not how it works, you buffoons, it trains off of datasets long before it releases. It doesn't think. It doesn't learn after release, it won't remember things you try to teach it.

Really lowering my faith in humanity when even the AI skeptics don't understand that it generates statistical representations of an answer based on answers given in the past.

Using an LLM as a chess engine is like using a power tool as a table leg. Pretty funny honestly, but it's obviously not going to be good at it, at least not without scaffolding.