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That's because between the two approaches "explain me this thing" or "write code to demonstrate this thing" the LLMs are much more useful on the second path. I can ask it to calculate some third derivatives, or I can ask it to write Mathematica notebook to calculate the same derivatives, and the latter is generally correct and extremely useful as is - the former requires me to scrutinize each line of logic and calculation very carefully.

It's like https://www.youtube.com/watch?v=zZr54G7ec7A where Prof. Tao uses claude to generate Lean4 proofs (which are then verifiable by machine). Great progress, very useful. While the LLM only approachs are still lacking utility for the top minds: https://mathstodon.xyz/@tao/113132502735585408






You have a narrow imagination. I'm talking about using GenAI for non-CS related applications, like it was advertised a year or so ago.

Lacking a rigorous way to verify truth, I would be pretty wary of using it for truly important things without a human to validate.

And math research is a non-CS application, for the pedants :)




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