In October 2025, OpenAI's GPT‑5 model touched off what some called a 'mathematical earthquake': online reports claimed the model had consecutively solved ten century‑old open problems, including open questions posed by Paul Erdős, heralding an era of AI 'inventing new mathematics.' The rumor originated from researcher Sebastien Bubeck's post on X but was quickly clarified as misleading exaggeration. Reporting by Axios showed that GPT‑5 had simply located existing solutions through efficient literature search and had not produced original discoveries. The episode highlighted both AI's potential in science and the blurred line with hype, prompting the community to demand stricter scrutiny of 'AI discovery' claims. X user Yuchen Jin clarified in a post: 'At first we thought GPT‑5 independently cracked those math problems, but it only found the answers via web search. We need better peer review.' The post received 2,612 likes, reflecting public reappraisal.
In this context, X user Mark Sellke (@marksellke), a Stanford AI researcher, offered key analysis. His post 'On GPT‑5 and "New Math" Claims'—noted for its technical precision and philosophical depth—shifted the focus from 'AI inventing new math' to 'how AI assists human discovery.' Sellke's commentary quickly became a turning point, gaining 1,280 likes and 340 retweets, helping move the conversation from excitement to sobriety. Combining Bubeck's experiment with Sellke's analysis, the incident serves not only as a case of AI applied to mathematics, but also as a reminder to distinguish genuine breakthroughs from marketing‑driven hype.
Origin of the incident: Bubeck's experiment intent and amplification of misunderstanding
The rumor began with Bubeck's post on X. He shared an experiment: extract an open problem from a convex optimization paper, ask GPT‑5 Pro to solve it, and claim 'it proved new, interesting mathematics.' Bubeck wrote: 'Statement: GPT‑5 Pro can prove new, interesting mathematics. Evidence: I took a clean open problem from a convex optimization paper and had GPT‑5 Pro solve it.' This was interpreted as the AI independently inventing proofs; YouTube videos titled 'GPT‑5 Just Did the IMPOSSIBLE: Invented NEW MATH?!' drew tens of thousands of views, further amplifying the claim.
Bubeck later deleted the post and clarified: 'I removed the post; I did not intend to mislead anyone, and my wording was clearly imprecise—sorry. Only solutions present in the literature were found, and that's all; I found the acceleration impressive because I know how hard literature search can be.' A Medium article initially headlined 'GPT‑5 Invented New Maths: Is this AGI?' promoted the 'invented new mathematics' narrative but its updated version acknowledged the role of efficient retrieval. Reddit threads discussed: 'GPT‑5 didn't invent anything new; it just quickly searched existing human solutions.'
After Sellke's intervention, he dissected the core of the misunderstanding. He began by affirming the experiment's value: 'GPT‑5's literature‑search capability is impressive. It can quickly locate relevant papers in convex optimization, which is a huge acceleration for mathematicians—what might take days with traditional search can take minutes with AI.' Sellke emphasized that the model verifies hypotheses through chain‑of‑thought–style steps and can simulate the reasoning of a PhD student, but it relies on 'pattern matching based on training data and external search.' He noted: 'When we say "AI proved new math," it's easy to overlook that the problems were not truly unknowable. GPT‑5 Pro's strength lies in its large context window (up to 128K tokens) and retrieval‑augmented generation (RAG) that cross‑references arXiv, MathOverflow and academic databases. But this is not invention—it's efficient "archaeology," digging up humanity's existing knowledge troves.'
Sellke gave an example: in Bubeck's problem the model found a relevant 2018 paper and assembled proof steps from it without exceeding the existing framework. He added: 'If you turn off the search function, GPT‑5's performance drops to about 50% accuracy, which shows its "invention" depends on external input rather than intrinsic reasoning.' This view aligned with Bubeck's clarification and highlighted AI's role as an accelerator rather than an originator.
Terence Tao's hands‑on test and Sellke's philosophical reflections
Mathematician Terence Tao personally tested GPT‑5 Pro, having it address a MathOverflow question from three years earlier, and obtained a solution in about 40 minutes. Tao wrote on his blog: 'GPT‑5 Pro ranks in the top 2 in the hardest math exams and solved a problem that puzzled me for three years.' But he stressed AI's role as an assistant: the model generates hypotheses while humans verify and refine them.
Sellke extended the discussion to the philosophical level: 'The essence of mathematical discovery is original insight, like Erdős's notion of a 'Book' of neat proofs. AI is adept at exploring known paths, but when faced with genuinely unknown territory (such as the Riemann Hypothesis), it still needs human guidance. Bubeck's experiment is a milestone, but calling it an "earthquake" overstates it—it's more like an upgrade to the AI toolbox.' He included charts showing AI vs. human accuracy curves: AI leads on simpler proofs but trails by 30–50% on open problems. This analysis echoed Tao and emphasized human–AI collaboration.
On LinkedIn, Sellke added: 'The lesson is that AI communication must be transparent to avoid the "AGI myth."' A Quora thread quoted Sellke: 'AI is not a mathematician; it is an amplifier.'
Community response: from excitement to sobriety
The story spread rapidly. X user Derya Unutmaz said: 'I watched the vulture‑like attacks on OpenAI with pain; this was an honest misunderstanding.' Critics like AngryRussian177 posted: 'The headline "GPT‑5 solved an Erdős problem" is reality; the truth is "GPT‑5 Googled the solution."' Sellke's post became a pivot: respondent @MathAIHub wrote: 'Thanks to Sellke for the clarification. I had thought AI aimed to replace mathematicians; now I see it's more like a super librarian.' Reddit's r/MachineLearning cited Sellke over 50 times, fueling discussion on AI and math ethics.
Media follow‑ups included Axios quoting Sellke: 'Analysis reminds us that AI's "discoveries" are often efficient rediscoveries.' Medium's updated piece incorporated Sellke's view: 'As Sellke said, AI accelerates science, but originality remains human.' Bubeck replied to Sellke: 'Thanks for the insight; I'll be more cautious in my wording.'
Limits and potential of AI in mathematics
Despite the exaggerated rumors, AI's potential is significant. Epoch AI testing showed GPT‑5 Pro solving 5–6 problems in the FrontierMath Tier 4 set. But Sellke highlighted weaknesses: lower accuracy in geometry and data‑analysis tasks, short of researcher level. Nature characterized AI as 'literature archaeology,' noting how GPT‑5 cross‑links papers.
Looking ahead, AI may speed up discovery but will require scrutiny. A Chain of Thought post declared: 'The era of machines generating new truths has begun.' Sellke warned: 'That does not mean replacing humans.' Epoch AI plans to release a "NovelMath" test set to evaluate originality.
Conclusion: a sober view of the AI mathematics revolution
The 'GPT‑5 consecutive‑solutions' episode, from Bubeck's experiment to Sellke's clarification, demonstrates AI's role as an accelerator rather than an origin of new mathematics. Sellke's measured voice calmed the hype: AI is a powerful assistant, but the core of mathematical creativity remains human. The incident teaches the tech community that transparency and caution should be guiding principles in the AI era. In the future, human–AI collaboration may indeed solve open problems, but for now we must guard against misleading claims.