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>These models cannot even make legal chess moves. That’s incredibly basic logic, and it shows how LLMs are still completely incapable of reasoning or understanding.

Yeah they can. There's a link I shared to prove it which you've conveniently ignored.

LLMs learn by predicting, failing and getting a little better, rinse and repeat. Pre-training is not like reading a book. LLMs trained on chess games play chess just fine. They don't make the silly mistakes you're talking about and they very rarely make illegal moves.

There's gpt-3.5-turbo-instruct which i already shared and plays at around 1800 ELO. Then there's this grandmaster level chess transformer - https://arxiv.org/abs/2402.04494. They're also a couple of models that were trained in the Eleuther AI discord that reached about 1100-1300 Elo.

I don't know what the peak of LLM Chess playing looks like but this is clearly less of a 'LLMs can't do this' problem and more 'Open AI/Anthropic/Google etc don't care if their models can play Chess or not' problem.

So are they capable of reasoning now or would you like to shift the posts ?

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int_19h 3 days ago | parent [-]

I think the point here is that if you have to pretrain it for every specific task, it's not artificial general intelligence, by definition.

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og_kalu 3 days ago | parent [-]

There isn't any general intelligence that isn't receiving pre-traning. People spend 14 to 18+ years in school to have any sort of career.

You don't have to pretrain it for every little thing but it should come as no surprise that a complex non-trivial game would require it.

Even if you explained all the rules of chess clearly to someone brand new to it, it will be a while and lots of practice before they internalize it.

And like I said, LLM pre-training is less like a machine reading text and more like Evolution. If you gave a corpus of chess rules, you're only training a model that knows how to converse about chess rules.

Do humans require less 'pre-training' ? Sure, but then again, that's on the back of millions of years of evolution. Modern NNs initialize random weights and have relatively very little inductive bias.

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sceptic123 2 days ago | parent [-]

People are focussing on chess, which is complicated, but LLM fail at even simple games like tic-tac-toe where you'd think, if it was capable of "reasoning" it would be able to understand where it went wrong. That doesn't seem to be the case.

What it can do is write and execute code to generate the correct output, but isn't that cheating?

	▲	int_19h 2 days ago \| parent [-]
		Which SOTA LLM fails at tic-tac-toe?