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OpenAI made a breakthrough on 80 year old maths problem

General-purpose AI reasoning is starting to crack real research problems, hinting at a new tool for science.

Key takeaways

  • Over the past year Artificial Intelligence (AI) has been getting much better at maths and even won some Maths Olympiads.
  • The company behind ChatGPT said it had with a challenge first posed by Hungarian mathematician Paul Erdős in 1946: the planar unit distance problem.
  • OpenAI’s model concluded otherwise by drawing on different branches of mathematics to uncover a family of arrangements that break the limit in Erdős’s conjecture.
Cite or link to this article

Griffin, M. (2026) 'OpenAI made a breakthrough on 80 year old maths problem', 311 Institute, 9 May. Available at: https://www.311institute.com/openai-made-a-breakthrough-on-80-year-old-maths-problem/ (Accessed: 1 October 2026).

Over the past year Artificial Intelligence (AI) has been getting much better at maths and even won some Maths Olympiads. Now OpenAI has claimed a further advance in AI reasoning after its technology successfully tackled an 80-year-old maths problem.

The company behind ChatGPT said it had with a challenge first posed by Hungarian mathematician Paul Erdős in 1946: the planar unit distance problem.

The question posed by Erdős is simple to explain. If you take a sheet of paper and add some dots, how many pairs can be the same distance apart? Erdős proposed the number would rise only slightly faster than the number of dots themselves.

OpenAI’s model concluded otherwise by drawing on different branches of mathematics to uncover a family of arrangements that break the limit in Erdős’s conjecture.

“For nearly 80 years, mathematicians believed the best possible solutions looked roughly like square grids,” OpenAI wrote on X. “An OpenAI model has now disproved that belief, discovering an entirely new family of constructions that performs better.”

While the work has excited mathematicians, the broader problem remains unsolved because the AI did not come up with a new answer for how fast the pairs of dots rise, but merely showed that the limit Erdős proposed was too low.

OpenAI, which is preparing to float on the US stock market, said the calculations had been made by a general-purpose reasoning model, which breaks down problems into smaller steps, rather than a system trained specifically for mathematics.

The startup has been tripped up before by its attempts to solve Erdős’s problems, having hailed a supposed breakthrough last year that was in fact based on already existing literature absorbed by the model. This time, OpenAI’s work has been validated by mathematicians, including Thomas Bloom, a mathematician who maintains the website and criticised OpenAI’s prior Erdős claims.

Bloom co-authored a companion paper to OpenAI’s blog post flagging the Erdős achievement. Bloom wrote that the AI system had attained its results by “persevering down paths that a human may have dismissed as not worth their time to explore.”

However, he added that humans had been involved in the AI’s work.

“While the original proof produced by AI was completely valid, it was significantly improved by the human researchers at OpenAI and the many other mathematicians involved in the present paper. The human still plays a vital role in discussing, digesting and improving this proof, and exploring its consequences,” he wrote.

Mathematician Tim Gowers, also writing in the companion paper, described the result as “a milestone in AI mathematics.”

Andrew Rogoyski, of the Institute for People-Centred AI at the University of Surrey, said the announcement showed AIs were giving humans new ways to look at problems.

“It’s becoming clear that AI is impacting the world of creative thought and will become a fundamental tool of future scientific research,” he said.


311 Intelligence

What this means for your organisation

Broad reasoning tools reach research.

OpenAI says a general-purpose system that breaks problems into smaller steps beat a limit proposed by Erdős in 1946. It was not built only for maths. Leaders should expect broad tools, not narrow ones, to start contributing to hard research questions.

People still shape the outcome.

Thomas Bloom wrote that the original proof was valid but was significantly improved by human researchers. Humans still discuss, digest and improve what the machine finds. Plan research teams around that working pairing.

Verify every claim before relying on it.

OpenAI hailed a supposed breakthrough last year that rested on existing literature. This time mathematicians, including Bloom, validated the work. The wider problem also remains unsolved, so build independent checking into any research process.

Three questions for your next leadership meeting

  1. Which of our hardest problems could a reasoning system help explore?
  2. Who independently checks results before we act on them?
  3. How are our researchers trained to work alongside these tools?

The trends and technologies behind this story

From the 311 Starburst, the 311 Strategic Intelligence Unit’s map of the technologies and trends shaping the next 50 years.

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Analysis by the 311 Strategic Intelligence Unit, from Matthew Griffin’s article and 311 data. First published on Fanatical Futurist.

FAQ

Does this mean AI can now do original mathematics?

Partly, the model found a genuinely new construction, but human researchers refined the proof, and mathematicians stress people still drive the understanding and judgment behind such results.

Matthew Griffin

About the author

Matthew Griffin Founder, President and Futurist, 311 Institute

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."

Read full bio

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 17-time best selling author of the "Codex of the Future" series, Matthew is the Founder, President and Futurist of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.

An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity programme, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.

As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.

Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.

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Source: first published by the 311 Institute on 9 May 2026. Cite as: Griffin, M. (2026). OpenAI made a breakthrough on 80 year old maths problem. 311 Institute. https://www.311institute.com/openai-made-a-breakthrough-on-80-year-old-maths-problem/

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