{"id":622303,"date":"2026-09-12T09:32:09","date_gmt":"2026-09-12T09:32:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/ie\/622303\/"},"modified":"2026-09-12T09:32:09","modified_gmt":"2026-09-12T09:32:09","slug":"immature-playground-boasting-mathematicians-uneasy-at-openais-latest-scalp-mathematics","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ie\/622303\/","title":{"rendered":"\u2018Immature playground boasting\u2019: Mathematicians uneasy at OpenAI\u2019s latest scalp | Mathematics"},"content":{"rendered":"

It was a week that left mathematicians reeling. Hot on the heels of a flurry of cases<\/a> of artificial intelligence furthering the field<\/a>, OpenAI declared a major scalp: its latest AI model had cracked a Millennium Prize Problem, a puzzle with a $1m reward that had defied human brains for decades.<\/p>\n

The achievement bore little resemblance to how mathematical problems normally fall. A near-trillion dollar private company had unleashed 10,000 agents \u2013 AI systems that carry out tasks autonomously \u2013 on the problem. The bill was estimated at $15m.<\/p>\n

The trajectory towards AI capable of superhuman maths has long been clear, but to nail such a substantial problem<\/a> so swiftly sent shock waves through the field. Mathematicians are asking what will be left for themif works in progress are hoovered up and claimed by others, and how they should train the next generation when even fiendish assignments can be solved at the press of a button.<\/p>\n

\u201cI feel slightly shell-shocked,\u201d said Prof Colva Roney-Dougal, the head of pure mathematics at the University of St Andrews. At a recent public lecture, she said she believed that AI was unlikely to do anything remarkable soon. \u201cThree months later, I\u2019m totally wrong,\u201d she says. \u201cWe\u2019re all just waiting to see what happens. It\u2019s coming so fast.\u201d<\/p>\n

Prof David Silvester, a mathematician at the University of Manchester, said the field felt \u201cvery unstable\u201d given the pace of change. \u201cAll the open maths problems could fall with enough resources,\u201d he said. \u201cThis is irreversible. This is not going to change.\u201d<\/p>\n

Prof James Robinson, a mathematician at the University of Warwick, said hard problems were the fuel of mathematics, driving creative approaches across successive generations. \u201cIt\u2019s frustrating to see these big tech companies burning this fuel up just so that they can show off about how great their latest model is,\u201d he said. \u201cIt seems like immature playground boasting writ large, underpinned by billions of dollars and the potential for significant environmental damage in an age when climate change is probably the biggest challenge we face.\u201d<\/p>\n

One reason Silvester went into maths was the rush that comes from cracking a problem. For many mathematicians it is the weeks, months and years spent circling a problem, breaking it down, trying one approach after another, and never quitting that appeals. \u201cWithout that, the subject seems completely different to me,\u201d Silvester said.<\/p>\n

Mathematicians already devote considerable time to verifying each other\u2019s proofs. It was this kind of review that found a gap in Andrew Wiles\u2019s work on Fermat\u2019s Last Theorem<\/a> in 1993, prompting a year of further effort to fix the flaw. Silvester suspects mathematicians might find themselves poring over ever more proofs dashed out by AI. \u201cIt\u2019s more like becoming an accountant, you\u2019re auditing, you\u2019re checking,\u201d he said.<\/p>\n

There are knock-on effects throughout the field. Mathematicians are recruited on the strength of their published papers, but problems they have been working on for months might now be solved by AI in days. \u201cThere\u2019s a real sense of \u2018I could spend the next month thinking about something and somebody else does it by pushing a button\u2019,\u201d says Roney-Dougal. \u201cThat\u2019s horrible, and I think it\u2019s going to be horrible for a few years.\u201d<\/p>\n

It\u2019s also a headache for teaching undergraduates. Universities<\/a> routinely set students problems and quizzes to work through at home. That kind of coursework is now dead. \u201cThere\u2019s no point in doing it because we can\u2019t vouch for its authenticity,\u201d says Silvester. Lecturers are now having to tell students not to use AI for some problems, while ensuring they can use it for others: after all, AI-assisted maths is the future.<\/p>\n

For all the upheaval, Prof Alexander Paseau, who studies the philosophy of mathematics at the University of Oxford, believes maths will not lose much of its appeal. \u201cThe challenge still remains, even if AI is eventually better than humans at research,\u201d he said. \u201cYou\u2019ll still want to be able to understand the mathematics yourself. And we\u2019ll still enjoy it and appreciate its beauty: the sheer enjoyment and the beauty of a mathematical proof will always be there. AI is not going to take any of that away.\u201d<\/p>\n

A lot of AI maths does not solve problems from scratch, but builds on work by humans, he added. The OpenAI<\/a> breakthrough, for example, relied heavily on work by the Madrid-based mathematicians Diego C\u00f3rdoba and Luis Martinez-Zoroa.<\/p>\n

OpenAI\u2019s work described a solution to the Navier-Stokes problem<\/a> which involves equations that predict how fluids, and even the weather, behave. It is one of seven Millennium Prize Problems published by the Clay Mathematics Institute in 2000. The company\u2019s announcement on Tuesday has led to further concerns in the community. OpenAI set its latest model to work after hearing rumours that two Millennium Problems had been solved by mathematicians. Prof Tristan Buckmaster at New York University and Levent Alp\u00f6ge at Anthropic were doing related work on Navier-Stokes and had used OpenAI\u2019s products in the process. They suspected OpenAI\u2019s model had learned from their work-in-progress. After an investigation, OpenAI denied this was the case<\/a>.<\/p>\n

Some mathematicians are still wary, however. \u201cThe big story now in mathematics is that nobody wants to share anything,\u201d Buckmaster told the Guardian. \u201cMathematics is different today than it was only a few days ago. We have to decide what to do about that.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"It was a week that left mathematicians reeling. Hot on the heels of a flurry of cases of…\n","protected":false},"author":2,"featured_media":622304,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[220,218,219,61,60,80],"class_list":["post-622303","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-ie","tag-ireland","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/622303","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=622303"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/622303\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/622304"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=622303"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=622303"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=622303"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}