https://github.com/openai/math/blob/7ef5c0cc5ca4b0e072b7a050... looks like the real proof is in this file
How do you gain confidence that your theorem actually applies to your code?
What is this meant to do? You're just showing that OpenAI didnt post a Lean proof that Lean/nanoda doesn't really accept?
I don't think this is a reasonable take at all. Most work on maths has no real benefit other than to further human understanding of maths - it's more like an art. Nothing is gained from OpenAI solving all these problems…
There's a project called lean4lean that implements lean in lean. I guess ideally, if you had a kernel optimisation idea you could do a copy of the Lean model lean4lean has created, add the optimisation, then prove your…
yes and it has for a very long time. Stockfish took the neural net approach after AlphaZero showed it was a good idea as all modern chess engines have
https://github.com/openai/math/blob/7ef5c0cc5ca4b0e072b7a050... looks like the real proof is in this file
How do you gain confidence that your theorem actually applies to your code?
What is this meant to do? You're just showing that OpenAI didnt post a Lean proof that Lean/nanoda doesn't really accept?
I don't think this is a reasonable take at all. Most work on maths has no real benefit other than to further human understanding of maths - it's more like an art. Nothing is gained from OpenAI solving all these problems…
There's a project called lean4lean that implements lean in lean. I guess ideally, if you had a kernel optimisation idea you could do a copy of the Lean model lean4lean has created, add the optimisation, then prove your…
yes and it has for a very long time. Stockfish took the neural net approach after AlphaZero showed it was a good idea as all modern chess engines have