AI is dividing the math world in two

October 20, 2026

AI Summary

5 min read

AI is dividing the math world in two

Over the last few months, OpenAI has started releasing what it calls answers to some of the biggest problems in mathematics—problems that professional mathematicians have been working on for decades, even a century. Some are famous problems with large prizes attached. Others are just things researchers have been noodling on forever. The math community has been shocked. People are worried about whether OpenAI is taking credit from them. People are worried about what this means for the existence of the life of a mathematician going forward. The Verge's Robert Hart has been covering all of this, talking to professors around the world, and what he's found is a story that extends far beyond mathematics.

From terrible to terrifyingly good, practically overnight

Math has been a focus for AI labs for a very long time. As Hart puts it, mathematics is viewed as "a kind of pinnacle of knowledge," and it's easy for AI companies to "try and sort of show off in that area." For years, the results were terrible. Then, in the last few months, they suddenly became very good—on par with the best human mathematicians. It was a lot like what happened with coding about nine months earlier: the technology went from "maybe someday" to "oh my God, this actually works" almost overnight.

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What you'll learn

1 (04:06) **OpenAI's Math Breakthroughs and the Shock to the Field** - David introduces the core story: OpenAI has been releasing solutions to major unsolved math problems, some worked on for decades, causing upheaval in the mathematics community.
2 (05:41) **The Sudden Shift: From Terrible to World-Class** - Robert explains how AI's math ability has rapidly improved, going from poor to on par with the best human mathematicians in just a few months.
3 (09:18) **The Human Story: Despair, Sleeplessness, and the "Eye of Sauron"** - Mathematicians are reacting with deep anxiety, feeling that a massively resourced AI lab has turned its attention to their specific field.
4 (11:31) **Why the Approach Feels Bad: Silicon Valley vs. Academia** - The frustration isn't just about job displacement; it's about OpenAI's "move fast, break things" culture clashing with the deliberative norms of mathematics.
5 (14:27) **The "Dump and Run" Problem: 400 Unverified Results** - OpenAI dropped hundreds of unverified, AI-written preprints on the math community, creating a massive verification burden and misunderstanding the field's values.
6 (20:55) **The Core Mismatch: Answer vs. Understanding** - The fundamental conflict is that OpenAI values the final answer, while mathematicians value the process of discovery, which creates new methods and understanding for future problems.
7 (25:01) **Efforts at Harmony: A Hijacked Advisory Board** - OpenAI has made some efforts to collaborate, but they have been clumsy and have undermined their own credibility with the math community.

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Show Notes

Over the last several months, the AI industry has set its sights on some of the problems that have stymied mathematicians for years. In some cases, AI models have made huge progress — though exactly how much isn't always obvious. The Verge's Robert Hart explains what OpenAI and others have actually accomplished, the disastrously bad ways the companies have interacted with researchers, and whether there's a future left for human mathematics.