The IBM Think article examines concerns raised by Fields Medalist Terence Tao about the rapidly increasing ability of AI to solve difficult mathematical problems. The discussion follows OpenAI’s claim that an internal AI system produced a solution to the Navier–Stokes existence and smoothness problem, one of the seven Millennium Prize Problems. According to OpenAI, thousands of AI agents worked concurrently, generating enormous amounts of mathematical exploration before another model formalized and checked the resulting proof in Lean. The article places this development alongside other recent AI-generated mathematical results from OpenAI and Google DeepMind, suggesting that AI is moving from solving established benchmarks toward conducting genuinely new mathematical research.
Tao’s main concern is not simply whether AI can solve mathematics, but what might be lost if it solves problems too quickly. Human mathematicians often gain valuable techniques, failed approaches, related problems and deeper understanding during the years spent attacking a difficult question.
If AI jumps directly from problem to finished proof, researchers may receive the answer without understanding the mathematical journey that produced it. Tao therefore argues that mathematical progress should be measured not only by whether a theorem is proved, but by whether the process produces ideas that allow mathematicians to understand and think about mathematics more effectively.
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Tao’s main concern is not simply whether AI can solve mathematics, but what might be lost if it solves problems too quickly. Human mathematicians often gain valuable techniques, failed approaches, related problems and deeper understanding during the years spent attacking a difficult question.
If AI jumps directly from problem to finished proof, researchers may receive the answer without understanding the mathematical journey that produced it. Tao therefore argues that mathematical progress should be measured not only by whether a theorem is proved, but by whether the process produces ideas that allow mathematicians to understand and think about mathematics more effectively.
ARTICLE
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