Comment by croniev

What confuses me about this analogy is that it seems to imply this is a matter of a knowledge-base and logical inferences. But the whole reason why LLMs are so successful is that the logical approach was abandoned in favor of a statistical one (and huge amounts of data, compute, and weights). The argument is precisely, that what is not in the training does not find its way into the probability distribution. To claim that LLMs reason is a very far stretch that I don't feel comfortable to let pass.