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>and test for correctness by checking the numerical equality of the two outputs over many random inputs. This is fundamentally different to how any human would
by constantcrying 1y ago
>and test for correctness by checking the numerical equality of the two outputs over many random inputs.
This is fundamentally different to how any human would approach this problem. And also different to how some recent advances in this area were made, where AI actually came up with superior and correct algorithms.
This approach also seems quite unfortunate and makes many of theses results somewhat doubtful.
- gotoeleven 1y agoHow else would you do the verification?
- constantcrying 1y agoSee: https://www.nature.com/articles/s41586-022-05172-4 https://www.nature.com/articles/s41586-022-05172-4 IIRC there was another paper recently, with similar methodology about computing xAx. These papers produce algorithms which aren't empirically correct, but provably correct. They do this by operating on a graph data structure, which describes the algorithm and then verifying the algebraic equality to the correct result. There is a substantial difference here. And I think utilizing algorithms which only are empirically correct can be dangerous.