OpenAI Cracks Navier-Stokes, Tech Trailers, AI Jobs Apocalypse on Hold | Diet TBPN

**John Coogan** (0:01)
Does math matter? That's the big question. I was debating this with Tyler today.
Lots of tension on the timeline over Navier-Stokes, the Millennium Prize math problem. There has been a Millennium Prize math problem that was solved before the Poincare Conjecture in the pre-AI era. These are very, very difficult math problems that all PhD mathematicians, all sorts of elite, the upper echelon of math has been grappling with for years, and AI is starting to knock these down. Remember, last year was the year of the IMO gold medals from both Google DeepMind and OpenAI. We talked to Scott Wu about this, who's coming on the show later today, huge raise for cognition.
Scott made the prediction on TBPN early in 2025, that he believed that artificial intelligence would be able to achieve gold at the IMO, the International Math Olympiad in 2025, and he was right.
He nailed it.
Progress continued. But debate remained around, cool calculator, bro, basically, is the critique. I mean, people just, they don't feel empowered by a system that's really good at math.
Already, a TI-83 can do more complex math than most people can do, and so when you say, oh, there's another level of math that you don't know about and you don't care about, and computers are good at it, a lot of people, their eyes glaze over. And so the bigger question here for me is all about the public perception. What actually matters here? I think they're cool benchmarks. I think they're interesting stories. Obviously, there's a lot of drama over this race. It feels like it was neck and neck. Now there's a bunch of debates going back and forth with a mathematician who works at Google and a mathematician who's independent, who worked alongside an anthropic researcher who were both working on it. And they were apparently texting back and forth and going back and forth on did they steal the data? Did they copy each other? Do they have different approaches? And so lots of different back and forth. And I think someone summed it up well by saying that these math models have discovered the hardest problem of advanced mathematics, which is authorship contribution. Who actually did the work? Who gets lead left on the paper? But yeah, there was a drama last year, 2025, during the IMO. OpenAI and Google DeepMind, and I believe Harmonic, the math AI lab that we had on the show last week, were all working on solving the International Math Olympiad. Remember, there's six questions. Question six, no AI model could solve. It was more complex. But both teams got a 35 out of 42 There was a bunch of back and forth because OpenAI validated with former IMO gold medalists, while Google's result was graded by the official rubric that year, which is internal to the organization. We called it at the time, it's like they ran the fastest 100 meter sprint in the parking lot while the actual Olympics is going on in the stadium. And so a lot of these are just, you know, vibe wars, races, who does what, does it even matter? The interesting thing about Navier-Stokes is, does it matter, Tyler? You think it does? I'll debate you on this a little bit. It seems like it doesn't because the equations themselves are known. They're just not fully proven. Engineers and physicists already solve them numerically all the time for a particular situation. So airflow around a wing, you might have to use some of these equations, weather models, water through a pipe. These are critical things. They are boring, but you can imagine that there would be cause for optimism. Better weather models save lives during hurricane season. Increased airflow across an airplane wing, that could lead to more efficiency, longer ranges, cheaper flights, lower carbon emissions. There's a bunch of reasons why you could solve all that and be excited. But that's not actually what happened.

**Jordi Hays** (4:07)
One of the reasons I'm excited, I believe we agreed last week that if anyone solves Navier-Stokes, Tyler would shave his head.

**John Coogan** (4:13)
Oh, that's right. Didn't we do that? We said something.

**SPEAKER_3** (4:17)
No, no, that was about the Tesla.

**SPEAKER_4** (4:19)
Oh, that was the Tesla. The details are kind of positive. Get ready to shave your head, buddy.

**Jordi Hays** (4:23)
But yeah, this is a big moment.

**John Coogan** (4:24)
Yeah, I think it was actually more, it was if any AI progress happens at all, Tyler shaves his head.

**Jordi Hays** (4:30)
Yeah.

**John Coogan** (4:31)
But do you have a steel man for why this matters?

**SPEAKER_3** (4:33)
So I think I agree that like, I don't think the breakthrough, this new stuff that's going on is practically super useful. It's not like you're going to feel it when you're on an airplane. You're not going to feel like less turbulence now. But I think these are like the most important open math problems. I think like these are more close to like, you know, a beautiful painting or something than like some like practical engineering breakthrough.