Welcome to the AI crisis in math

**SPEAKER_1** (0:00)
Support for the show comes from ServiceNow.
AI is moving fast across the enterprise, but without visibility, it's just chaos. Different tools, different models, different teams using AI in completely different ways. ServiceNow turns that chaos into control. With the AI control tower, you see all your AI across the business in one place. What it's doing, what it's done, and what it's about to do, so you stay in control. To put AI to work for people, visit servicenow.com.

**SPEAKER_2** (0:35)
You're listening to DeepGrim Flux TTS, different voices, same model, all ready to speak.

**SPEAKER_3** (0:40)
Flux TTS is a streaming text-to-speech model built for voice agents.

**SPEAKER_2** (0:45)
Flux reads the room. It holds context across the conversation turn after turn.

**SPEAKER_4** (0:49)
With consistent tone, interruption handling, and plenty of personality.

**SPEAKER_2** (0:53)
So your agents keep it flowing and customers can just keep talking.

**SPEAKER_3** (0:57)
Try Deepgram Flux TTS free now until September 12th. Visit deepgram.com/keeptalking.

**SPEAKER_4** (1:04)
Terms apply.

**SPEAKER_5** (1:05)
We secure the world's AI future by securing the world's AI leaders. AI is being adopted faster than companies can secure it. Sensitive data is moving across AI models and attackers are using AI to strike with unprecedented speed and precision. That's why CrowdStrike built the agentic cybersecurity platform for the AI era, to secure AI and to stop breaches. So you can embrace AI with confidence, not compromise. CrowdStrike, we secure AI, we stop breaches.

**Nilay Patel** (1:37)
Hello, and welcome to Decoder. I'm Nilay Patel, Editor-in-Chief of The Verge, and Decoder is my show about big ideas and other problems. Today, I'm talking to Robert Hart, The Verge's London-based AI reporter, about what AI is doing to the field of mathematics, and the existential crisis that many leading mathematicians are having about it. The news here is that OpenAI just published a set of solutions to long-standing problems in math that went off like a bombshell in the field. It's caused a huge debate in the math community, and Rob talked to some of the most accomplished mathematicians of our time about it. It's funny that AI systems are still pretty bad at elementary school arithmetic, but they're getting increasingly good at very high-end abstract math. All of this raises some big questions for the field of advanced mathematics. If AI can do math of this caliber, does that mean AI labs can transfer those skills to other domains? What good are the academic grants and university programs designed to train new generations of human mathematicians to identify new problems as they try to solve existing ones, if the frontier models simply solve all of the outstanding questions? Perhaps most importantly, what if all this attention to math is just another marketing exercise for the frontier AI labs, who don't seem to care less about what happens to one of the oldest and most fundamental academic disciplines there is? There's a lot here, and Rob talked to a lot of people with a lot of views on all of it.
Okay, Verge AI reporter Robert Hart on what AI is doing to math. Here we go.
Robert Hart, you are a London-based AI reporter here at The Verge. Welcome to Decoder.

**Robert Hart** (3:15)
Thank you for having me.

**Nilay Patel** (3:16)
I am very excited to talk to you. There's a lot going on in particular with AI and math that you recently dove into. You spoke to a lot of leading mathematicians about the crisis in mathematics due to AI.
It feels like a lot and also like there's a lot yet to know and discover about the interaction of these two things. A full existential crisis, which is pure Decoder bait. Broadly tell us what's going on.

**Robert Hart** (3:42)
I think a lot sums it up quite well.
I mean, basically a bit of an existential crisis within what is mathematics? What are mathematicians doing? What is the role of mathematicians going forward? And a lot of that has been spurred by kind of a phrase transition in what AI is capable that has kind of exploded, would be a reasonable way of saying in the last six months to a year. And it's gone from being very terrible to seemingly genuinely quite good at a professional level in a very short space of time. And so I think it's a lot of what these other fields have been struggling to deal with for the last five years in a very compressed period of time.

**Nilay Patel** (4:24)
I would put that next to software engineering. We've been living through the AI crisis in software engineering for some amount of time. But as recently as 2024, even last year, the conventional wisdom was that AI models were particularly bad at math. The famous example is they could not count the number of Rs in the word strawberry, even just counting sort of eluded them.