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You can train a small transformers that learns an algorithm for addition and generalizes perfectly.

https://www.alignmentforum.org/posts/N6WM6hs7RQMKDhYjB/a-mec...

>But for the purpose of LLMs we have to conclude that no, it can't find logic by reducing a set of outcomes, regardless of the size of the set.

A ML model is probably not going to converge strictly on a formal logic system practically and there's also the question of if formal logic even underpins the result of the dataset you're feeding it, but that's entirely different from saying it cannot in principle.



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