| ▲ | agentultra 5 hours ago | ||||||||||||||||
> A human reviewer only needs to read 93 lines of formal specification and run the Lean checker to certify the correctness of the kernel, skipping the intricate 1000+ lines of AI-written implementation. To prove correctness, AI autonomously wrote over 60,000 lines of Lean proofs, which also never have to be inspected by a human. I am curious about the approach as I find claims like this hard to believe. There is a theory behind proof kernels that they must be small because they have to be trusted and verifiable by a human. Otherwise the whole system breaks. How does one trust an LLM generated kernel is proving the right things? | |||||||||||||||||
| ▲ | permute 5 hours ago | parent | next [-] | ||||||||||||||||
Maybe what you mean is that kernels of proof assistants must be small. Here I am referring to a geometry processing kernel (that is formally verified by a proof assistant). The implementation of the algorithm can be very long, the proof that it conforms to the spec can be very long. But lean checks the proof. And so you only have to trust the spec and that the lean proof assistant is correct. In the 93 lines I assumed a reviewer already trusts that the kernel of the Lean proof assistants is correct. We have to trust somethings. | |||||||||||||||||
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| ▲ | UltraSane 3 hours ago | parent | prev [-] | ||||||||||||||||
Think of Lean proofs as a kind of inductive proof where if you trust the kernel then you trust every proof the kernel says is true. | |||||||||||||||||
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