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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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