AI is changing math
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OpenAI says GPT-6 Astra, a new model released this week, generated new results on longstanding open math problems.
Why it matters: AI's growing ability to tackle complex math could accelerate discoveries in medicine, engineering and other math-dependent fields.
Driving the news: OpenAI says Astra resolved or made "substantial progress" in decades-old math and theoretical computer science problems.
- Astra produced results in high-dimensional geometry, coding theory, group theory, quantum complexity, lattice cryptography and combinatorics.
State of play: Anthropic and Google have also reported advances in AI-driven mathematics.
- An unreleased research version of Claude made a major improvement on decades-old work on the Riemann hypothesis, a problem that dates to 1859 and has a $1 million prize for anyone who solves it.
- Earlier systems from Google DeepMind reached medal-level performance on International Mathematical Olympiad problems.
The big picture: AI is starting to find connections that can lead mathematicians and researchers in unexpected directions.
- MIT mathematician Andrew Sutherland said Claude's work showed AI is "capable of doing interesting mathematical research, as opposed to just solving specific problems that are fed into it."
- Anthropic co-founder Tom Brown said last week at a global summit in Chapel Hill, N.C.: "Many aspects of science are a combination of engineering plus mathematics. And so my expectation is that over the next 12 months ... [models] could be once-in-a-generation scientists for key scientific fields."
Between the lines: The way researchers are using these models is surprisingly informal. Anthropic employees asked Claude to "take a real stab" at the Riemann hypothesis and "believe in yourself" after an initial run failed.
Case in point: Claude pushed the Riemann-related bound higher after spending 31 million output tokens and a day and a half coordinating about 60 subagents.
What they're saying: Mathematician Terence Tao predicts his field "will transition from an era of proof scarcity to an era of proof abundance."
