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OpenAI claims it solved an 80-year-old math problem -- for real this time | TechCrunch
OpenAI claims its new reasoning model has produced an original mathematical proof disproving a famous unsolved conjecture in geometry, which was first posed by Paul Erdős in 1946. If this sounds familiar to you, it's because this isn't the first time OpenAI has made such a bold claim. Seven months ago, the AI giant's former VP Kevil Weil posted on X: "GPT-5 found solutions to 10 (!) previously unsolved Erdős problems and made progress on 11 others." It turns out, GPT-5 didn't actually solve those problems; it just found existing solutions that already existed in the literature. Taunts from rivals like Yann LeCun and Google DeepMind CEO Demis Hassabis followed, and Weil promptly took down his premature post. Today, at least, it seems OpenAI didn't make the same mistake twice. Alongside the announcement, OpenAI published companion remarks in support of the disproof from mathematicians like Noga Alon, Melanie Wood, and Thomas Bloom, who maintains the Erdos Problems website, and previously called Weil's post "a dramatic misrepresentation." "For nearly 80 years, mathematicians believed the best possible solutions looked roughly like square grids," OpenAI posted on X. "An OpenAI model has now disproved that belief, discovering an entirely new family of constructions that performs better." The company said this marks "the first time AI has autonomously solved a prominent open problem central to a field of mathematics." The proof, per OpenAI, came from a new general-purpose reasoning model, not a system specifically designed to solve math problems or even this problem in particular. OpenAI says this is significant because it means AI systems are now more capable of holding together long, difficult chains of reasoning and connecting ideas across fields in ways researchers may not have previously explored. That has implications for biology, physics, engineering, and medicine. "AI is helping us to more fully explore the cathedral of mathematics we have built over the centuries," Bloom said in a statement. "What other unseen wonders are waiting in the wings?"
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ChatGPT solves 80 year old math problem that puzzled researchers for years
This announcement is interesting because OpenAI faced criticism last year after making a similar claim. OpenAI has once again made a big claim in the world of AI and mathematics. The company says that one of its latest AI reasoning models has successfully solved a famous geometry problem that remained unsolved for nearly 80 years. The problem was originally proposed by legendary mathematician Paul Erdos in 1946. This announcement is especially interesting because OpenAI faced criticism last year after making a similar claim. About seven months ago, former OpenAI VP Kevin Weil posted on X that GPT-5 had solved several unsolved Erdos problems. However, it was later found that the AI had only rediscovered solutions that already existed in mathematical research papers. That earlier claim led to criticism from well-known AI researchers like Yann LeCun and Demis Hassabis. Weil later deleted his post. This time, OpenAI appears to have taken extra care before making the announcement public. The company also shared supporting comments from respected mathematicians, including Noga Alon, Melanie Wood and Thomas Bloom. Also read: OpenAI introduces Guaranteed Capacity offering: What is it and what it promises 'For nearly 80 years, mathematicians believed the best possible solutions looked roughly like square grids,' OpenAI posted on X. 'An OpenAI model has now disproved that belief, discovering an entirely new family of constructions that performs better.' OpenAI says this is 'the first time AI has autonomously solved a prominent open problem central to a field of mathematics.' Also read: Google unveils new AI Ultra subscription with 20TB of cloud storage: What it offers and how much it costs The company also explained that the proof was generated by a general-purpose reasoning model rather than a system specially built for solving maths problems. According to OpenAI, this shows how modern AI systems are becoming better at handling long and difficult chains of reasoning. 'AI is helping us to more fully explore the cathedral of mathematics we have built over the centuries,' Bloom was quoted as saying in OpenAI's blogspot. 'What other unseen wonders are waiting in the wings?'
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OpenAI announced its new reasoning model has produced an original mathematical proof disproving a famous geometry problem posed by Paul Erdős in 1946. This comes after the company faced criticism seven months ago when GPT-5 allegedly solved Erdős problems but had only rediscovered existing solutions. This time, OpenAI backed its claim with support from respected mathematicians.
OpenAI has announced that its latest AI reasoning models successfully disproved an unsolved mathematical conjecture that has puzzled researchers since 1946. The 80-year-old math problem, originally posed by legendary mathematician Paul Erdős, centered on a geometry problem where mathematicians believed the best solutions resembled square grid patterns
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. The company's general-purpose reasoning model discovered an entirely new family of constructions that performs better, marking what OpenAI calls "the first time AI has autonomously solved a prominent open problem central to a field of mathematics"2
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Source: Digit
This achievement demonstrates a significant leap in complex reasoning capabilities, as the AI solves math problem through autonomous discovery rather than pattern matching from existing literature. The proof came from a model not specifically designed to tackle mathematical challenges, suggesting broader implications for how AI systems handle difficult chains of reasoning across multiple scientific fields
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.The announcement carries extra weight given OpenAI's previous misstep in this arena. Seven months ago, former OpenAI VP Kevin Weil posted on X that GPT-5 had found solutions to 10 previously unsolved Erdős problems and made progress on 11 others. However, it turned out GPT-5 didn't actually solve those problems—it merely rediscovered existing solutions already present in mathematical literature
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.That premature claim drew sharp criticism from AI luminaries including Yann LeCun and Google DeepMind CEO Demis Hassabis, prompting Weil to delete his post. Thomas Bloom, who maintains the Erdos Problems website, called Weil's earlier post "a dramatic misrepresentation"
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. This time, OpenAI appears to have taken a more cautious approach before going public.To support its claim, OpenAI published companion remarks from respected mathematicians including Noga Alon, Melanie Wood, and Thomas Bloom
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. Their endorsements lend credibility to what could represent a watershed moment for AI in mathematics. Bloom, who previously criticized OpenAI's earlier claims, now offers a more optimistic perspective: "AI is helping us to more fully explore the cathedral of mathematics we have built over the centuries. What other unseen wonders are waiting in the wings?"1
.The geometry problem disproved a long-held belief that had persisted for nearly 80 years among mathematicians. By discovering constructions that outperform the traditional square grid approach, the AI demonstrated an ability to think beyond established patterns and explore novel solution spaces that human researchers may not have previously considered
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Source: TechCrunch
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OpenAI emphasizes that this breakthrough matters because it shows AI systems can now hold together long, difficult chains of reasoning and connect ideas across fields in ways researchers may not have explored. The company suggests this capability extends far beyond mathematics, with potential applications in biology, physics, engineering, and medicine
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. If AI can autonomously discover solutions to problems that have stumped experts for decades, it could accelerate scientific discovery across multiple domains.The use of a general-purpose reasoning model rather than a specialized mathematical system is particularly noteworthy. This suggests the underlying reasoning capabilities are transferable, potentially enabling breakthroughs in other scientific fields where complex problem-solving and novel approaches are needed. For researchers watching this space, the key question becomes: what other long-standing problems might yield to AI's ability to explore solution spaces without human preconceptions?
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