@samir I'm generally against hyper-large-model based generative algorithms for at least 3 reasons 1. the ethics of training resources and getting training data 2. new class of bugs and security risks, as well as the poor maintainability of generated code 3. deskilling as people rely on these auto-parrots, and no longer learn the actual skill these machines are bad at mimicking I was surprised to see a famous mathematician, world famous, invest a lot of time in AI-aided proofs. I guess the difference between AI-generated code or human-language content - and AI-generated proofs is that the proofs can be checked with proof checkers (which are not AI). I'm still thinking about whether this "idea generation" is a good thing or a bad thing.