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OpenAI has published more than 700 AI-generated mathematics manuscripts, covering over 370 mathematical problems, with each taking an average of three hours to produce, including work related to the Riemann Hypothesis. According to a report by t3n, OpenAI said these manuscripts were completed with the help of an as-yet-unreleased AI model and were published in October. Institutions including the German Mathematical Society criticized the approach as a results-oriented "power display," arguing that the value of mathematical research lies in the paths of proof and new methods rather than in the answers themselves, and expressing concern about the use of unverified knowledge and issues of academic norms. Stuttgart professor Christian Hesse, on the one hand, called OpenAI's demonstration "stunning," while on the other hand arguing that doctoral training and the definition of mathematical understanding need to be readjusted.
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Nov 4
Sina Technology
OpenAI takes on the mathematics world with Lean: How formal verification becomes the key to AI self-evolution
Starting from the Millennium Prize Problems, OpenAI has released more than 700 manuscripts and challenged the ETH hypothesis and the P=NP conjecture, carrying the flames of AI competition into the mathematics world. The core tool is the Lean formal proof system and its Mathlib library, which contains more than two million lines of content; it can automatically provide scalable verification feedback, allowing AI to self-evolve through trial and error in mathematics like AlphaGo. In 2024, Google already used Lean to build AlphaProof, reaching the level of a silver medal at the Mathematical Olympiad.
Nov 3
t3n
OpenAI claims AI solved nearly 400 math problems; mathematicians criticize it for prioritizing results over process
OpenAI claims that with the help of an as-yet-unreleased AI model, it published more than 700 manuscripts in October, covering more than 370 math problems, with each taking an average of three hours, including work related to the Riemann Hypothesis. Institutions such as the German Mathematicians Association criticized this approach as a results-oriented "power display," arguing that the value of mathematical research lies in the proof path and new methods rather than the answers themselves, and expressing concern about the use of unverified knowledge and issues of academic norms. Stuttgart professor Christian Hesse, on the one hand, called OpenAI's demonstration "stunning," and on the other hand, believes that doctoral training and the definition of mathematical understanding need to be readjusted.