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turnip_burrito t1_jdqhcoi wrote

Reply to comment by RadioFreeAmerika in Why is maths so hard for LLMs? by RadioFreeAmerika

I'd have trouble making a sentence with 8 words in one try too if you just made me blast words out of my mouth without letting me stop and think.

I don't think this is a weakness of the model, basically. Or if it is, then we also share it.

The key is if you think about how you as a person approach the problem of making a sentence with 8 words, you will see how to design a system where the model can do it too.

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RadioFreeAmerika OP t1_jdqlcsd wrote

I also don't think it is a weakness of the model, just a current limitation I didn't expect from my quite limited knowledge about LLMs. I am trying to gain some more insights.

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FoniksMunkee t1_jdqs9x9 wrote

It's a limitation of LLM's as they currently stand. They can't plan ahead, and they can't backtrack.

So a human doing a problem like this would start, see where they get to, perhaps try something else. But LLM's can't. MS wrote a paper on the state of ChatGPT4 and they made this observation about why LLM's suck at math.

"Second, the limitation to try things and backtrack is inherent to the next-word-prediction paradigm that the model operates on. It only generates the next word, and it has no mechanism to revise or modify its previous

output, which makes it produce arguments “linearly”. "

They argue too that the model was probably not trained on as much mathematical data as code - and more training will help. But they also said the issue above "...constitutes a more profound limitation.".

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turnip_burrito t1_jdqrxre wrote

To be fair, the model does have weaknesses. Just this particular one maybe has a workaround.

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