Earlier quoted context omitted.
I’m generally a bit of an LLM skeptic, at least as concerns extravagant claims around “AGI” or self-improvement of any of that nonsense. But there are activities where an inherently high-temperature assistant (e.g. some Instruct-inspired tune) are a great fit, and those are almost definitionally at the boundary of “objectively faithful” and “a bit stochastic”. I’ve never done any work in novel mathematics myself, but…
The impact extends beyond mathematics. We have seen some pretty positive outcomes for LLMs as an assistant for scientists - with a lot of custom agent dev though - and not off-the-shelf models. This is already being used by a few hundred scientists in a lab. We are aiming to extend to thousands next year with a focus on CS, climate & bio.
Can you share any details?