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Is there an associated machine-checked proof of this?

We're in full vibe-code mode at work, so I understand both how powerful frontier models can be and how often they can over-confidently state subtly (or not so subtly) wrong things, even when you're taking great efforts to try to keep that from happening.

So without a Lean development or extensive human verification, I guess I'm a little bit skeptical, and even sort of hoping this is wrong - not just because of my not so positive feelings about AI, but by my disposition towards beauty in math. n log n is an awful lot nicer than what we have here.



Agree 100% on wanting machinr verification of AI generated math.

But in regards to beauty, i feel like multiplication already has a lot of non beautiful exponents. Best known matrix multiply is O(n^2.371). For integer factorization, the inverse of this problem, general number field sieve is a crazy subexponential.

If factorization is just barely subexponential, is it really that surprising that multiplication is just barely sub n lg n ?


Matrix multiplication is <=O(n^2.25) actually... [1]

1. https://github.com/openai/math/blob/main/preprints/Matrix-Mu...


Amazing, but...

this is not an algorithm in O(n^2.25), rather it is a proof that such an algorithm exists, but the proof doesn't provide the algorithm, it is a non constructive proof.


Beauty? Please, there are messy things all over math, this appeal to beauty sounds like over-romanticized pearl clutching.

Ever seen the Chudnovsky algorithm for Pi? People are plenty capable of creating very important ugly math on their own. Not at all unique to LLMs, nor a valid critique. Do you understand the significance of proving that integer multiplication is simpler than O(n log n), even by a little bit? This is exciting! Who knows where this might go or what'll be learned from this


We can just wait for whomever they stole THIS proof from to come forward with threatening emails sent by OpenAI.




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