OpenAI Says Its AI Cracked Three Major Math Problems
Is AI revolutionizing research or is it just repackaging decades of human work without credit?
Above: Photo illustration of the OpenAI logo displayed on a smartphone screen. Image credit: Thomas Fuller/SOPA Images/LightRocket/Getty Images
The Facts
- OpenAI announced on Monday that its AI systems produced three new results in harmonic analysis, complexity theory and quantum field theory, and that it has invited independent academic experts to verify the findings and assess their implications.
- The company said its system refuted the Exponential Time Hypothesis, first proposed in 1999, by producing a deterministic algorithm that "exactly counts satisfying assignments of fixed-width CNF formulas in subexponential time and polynomial space."
- A group led by Russell Impagliazzo and Ramamohan Paturi of UC San Diego, along with MIT's Ryan Williams, will examine the computer science result, and, at the group's request, OpenAI has posted the proof and Lean formalization to GitHub.
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The Spin
Pro-industry narrative
The results demonstrate what AI can do in math, physics and computer science. Harnessing its power, OpenAI made leaps in broadening our shared understanding of these academic fields and in taking the next steps toward quantum theory. Backed by Lean formalization and open to expert scrutiny, AI-driven research could overturn assumptions held for decades.
Industry-critical narrative
These proofs are built on decades of human work, and skipping proper credit while soaking up the glory is a poor way to treat the people who made it possible. Math, fundamentally, has never been about racking up theorems; the point is understanding, and that still lives in human heads, regardless of what AI companies want us to believe.
