As of: 2026-10-30 13:42 CET.
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# “Recently, OpenAI showed that matrix multiplication algorithms with exponent near 2.25…”

Sergey Gusev (@13SergeyGusev), X, 2026-10-20.
Source: https://x.com/13SergeyGusev/status/2112373928802799741

## Archived text

> Recently, OpenAI showed that matrix multiplication algorithms with exponent near 2.25 exist, but not what they actually are. We then shared an AI-written paper that builds them explicitly. That first version was really bad: even at exponent 2.67, it needed matrices with about 10^(2.3×10^11) rows.
> 
> So we pushed the AI agents further, and they improved it a lot. At the same exponent, the size dropped to about 10^4,650 rows. That's a huge improvement, but the observable universe has only about 10^80 atoms, so even at one number per atom it couldn't hold a single row of such a matrix.
> 
> For anyone wondering what this new exponent of 2.25 means: so far, it's a theoretical result only. The algorithms constructed so far are "galactic," and making such algorithms practical would require another major breakthrough. Still, there's real new interesting math here: a step-by-step version of OpenAI's construction that shrinks the sizes dramatically, and proofs of how far these specific constructions can and can't go.
> 
> New paper produced by AI: https://github.com/SECQUOIA/finite-extraction-matrix-multiplication/blob/main/shifted-chains.pdf

Archived 2026-10-29 via fxtwitter (unofficial).
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## Cited in

- 2026-10-06: [OpenAI proves ω ≤ 9/4 for matrix multiplication](https://postcutoff.com/e/2026-10-06-openai-matrix-multiplication-omega-9-4/)