> Computers are exclusively theorem generators, while humans appear to be axiom generators. > However, they are limited by the fact that they cannot establish

> Computers are exclusively theorem generators, while humans appear to be axiom generators. > However, they are limited by the fact that they cannot establish axioms Maybe I'm missing subtleties, but it seems like it'd be relatively trivial to get even just current LLMs to generate a couple of original axioms? If there's going to be further stipulation ("those axioms don't count because ...") I'd be interested to know whether the author believes there's some testable distinguishing factor between human and AI axioms, or if it's going to get to the point of "its generations appear identical to human axioms, but it's not actually generating axioms - just simulating/predicting/etc." > In essence, you cannot create a computer program that will tell if another arbitrarily chosen program will ever finish For real physical computers you can, such as with Floyd's tortoise and hare algorithm, since they don't have have infinite memory. Neither humans nor computers are exempt from the central trick that you can construct an unanswerable question by in some way referencing the question's answer ("What won't your answer to this question be?").