zlacker

LLMs do not know math, at all. Not to sound like one myself, but they are stochastic parrots, and they output stuff similar to their training data, but they have no understanding of the meaning of things beyond vector encodings. This is why chatgpt plays chess in hilarious ways also.

An LLM cannot possibly have any concept of even what a proof is, much less whether it is true or not, even if we're not talking about math. The lower training data amount and the fact that math uses tokens that are largely field-specific, as well as the fact that a single-token error is fatal to truth in math means even output that resembles training data is unlikely to be close to factual.

>>themoo+(OP)
That said, they are surprisingly useful. Once I get the understanding thru whatever means, I can converse with it and solidify the understanding nicely. And to be honest people are likely to toss in extra \sqrt{2} and change signs randomly. So you have to read closely anyways.