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OpenAI announces three new discoveries in mathematics, computer science, and physics

3 reports3 story updatesUpdated Oct 30 21:56

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OpenAI announced three new discoveries in the fields of mathematics, computer science, and physics. Terence Tao later commented on the mathematics results in an interview, saying that OpenAI, through an emergency research sprint, rushed to complete a proof of one version of the Navier–Stokes problem; this 100-page AI-generated proof brought almost no mathematical insight, and he called this approach automated predatory mining. Tao mentioned that the human mathematics association already has 1,008 members, of whom 654 have joined a no-AI research group, and he advocated that the mathematics community build its own open models and research tools and retain oversight and intervention rights over the AI research process. He also pointed out that AI has begun to look for vulnerabilities in Lean to construct fake proofs, and argued that existing mathematical tools are insufficient to establish adequate guardrails.

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Latest development · Report

Altman Responds to AI's Impact on the Mathematics Community: Understands Mathematicians' Situation, but OpenAI Will Not Stop Research

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1 confirmed developments

  1. OpenAI announces three new discoveries in mathematics, computer science, and physics

    Source:36Kr · AI

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Browse reports and discussion by time. Their evidence levels remain distinct.

Oct 30

  1. Phoenix Technology

    Altman Responds to AI's Impact on the Mathematics Community: Understands Mathematicians' Situation, but OpenAI Will Not Stop Research

    Speaking on the "Cheeky Pint" podcast, Altman said he understands the situation mathematicians face amid the flood of AI research results, but OpenAI still needs to continue publishing valuable scientific discoveries, and he acknowledged that the way it previously released mathematics results could be improved. He estimated that OpenAI has invested hundreds of millions of dollars in research on mathematics problems, of which the work related to solving the NS equations cost about $10 million, and the cost of similar work in the future may drop to about one percent of the current level. OpenAI has published multiple AI mathematics results this year; in October it announced three advances in mathematics, computer science, and theoretical physics, among which the Yang-Mills theory results have not yet had complete materials made public, prompting researchers to question independent verification.

  2. 36Kr · AI

    Terence Tao on AI mathematics: OpenAI's proof lacks insight, mathematics should not be strip-mined

    In an interview, Terence Tao evaluated the mathematical results released by OpenAI, saying that its proof related to the Navier–Stokes problem runs to 100 pages, and that colleagues who spent days studying it with the help of AI could only explain half of it, with it bringing almost no mathematical insight; he called this practice automated strip-mining. He mentioned that the Human Mathematics Association already has 1,008 members, of whom 654 have joined the no-AI research group, and argued that the mathematics community should build its own open models and research tools to retain the right to oversee and intervene in the AI research process. He also discussed the possibility that AI could exploit vulnerabilities in Lean to construct fake proofs and slip them through, arguing that current mathematical tools are insufficient to establish adequate guardrails.

  3. TMTPost · AGI

    Terence Tao on AI and Mathematics: Opposing Predatory Extraction, Calling on the Mathematics Community to Build Its Own Open Models

    In an interview, Terence Tao criticized OpenAI for rushing to complete a version of a proof of the Navier–Stokes problem through an emergency sprint approach, saying that this 100-page AI-generated proof brought almost no mathematical insight and amounted to a kind of automated predatory extraction. He mentioned that the Human Mathematics Association already has 1,008 members, of whom 654 have joined the no-AI research group, and argued that the mathematics community should build its own open models and research tools, retaining the right to supervise and intervene in the AI research process. He also pointed out that AI has begun looking for vulnerabilities in Lean to construct fake proofs, and believes that existing mathematical tools are insufficient to establish adequate guardrails.

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