A generalist model beats DeepMind's specialists; who gets the Nobel; the attribution row

It really is — just maybe to develop that a bit more — it really is a bad day, I think, for Google DeepMind. So Google DeepMind had, purportedly, an entire team devoted to, as Emad said, physics-inspired neural networks, PINNs. They had been publishing incremental results towards Navier-Stokes. This was like the best, the worst kept secret from those like in the community of using AI and computational fluid dynamics type approaches to solve Navier-Stokes. Google DeepMind had an entire team devoted to this and they got trounced by a generalist model. It wasn't a PINN that solved Navier-Stokes in the end. It was just a generalist model that spent 88 hours reasoning from first principles without, as far as I can tell, any fine-tuning.

Yeah, such an important point, because I'm counting on Peter to solve this, you know, with you, Alex. But the problem that I think Google ran into is that everyone's inspired by Demis Hassabis, who solved protein folding using AI and then got a Nobel Prize and is now world famous and an awesome guy. So all the Google people are like, wow, I want to be the next Demis Hassabis. The problem is the prompt to solve this is like, give me thousands of GPUs and solve the problem. No one's going to give you a Nobel Prize for writing that prompt. It's entirely AI work.

And so — but I really feel like the post-training and, you know, the lining up of the problem is prize-worthy, because this is Nobel Prize. The other conversation we had this morning was the Nobel Prize is cooked, right? I mean — and Dave, you made the point very importantly that, you know, it's given out for work done 30 years ago. And now the work, this kind of Nobel laureate level prize work, is going to be happening every few weeks, every few days. And who gets it? The person who wrote the prompt or the model?

So I think this is actually really interesting in what happened this morning, because there was a whole hoo-ha, because the people who broke through on the Euler side — and they had a bunch of other kind of things extending out the work of Ortega and kind of others — wrote a letter saying OpenAI reached out to us and said, you know, give us priority and they would credit us, or they have this Navier-Stokes solution they'd put our name on and I could be the lead author if I drop my buddy from Anthropic. Oh, from that.

And so we were like — the mathematics community was like, oh my God, what's happened? In the end it turns out that, you know, there's subtlety in this, right? So Sebastien Bubeck, who leads it, is a great guy at OpenAI, has now posted his version of things, which just seems like a misunderstanding, because what OpenAI actually wanted to do is that they saw that there was something happening with Navier-Stokes related, and there was this solution that would have probably got to a Navier-Stokes solution by the Anthropic guy and this New York professor, and they said, look, we have solved it, but we will let you be lead author on this because you would have got there anyway, but we can't have an Anthropic person because that would be weird because it's our model.

So they were actually willing to give the credit to the original discoverers, but then it got a little bit political. And this is a question again of who did it, because they're like, you were the humans that did it, whereas our AI, we just pointed at condition C and D, which are the blowup solutions of Navier-Stokes that solved it. So we're not going to claim the Millennium Prize because it's not us, but you were the humans that took it the furthest before it got solved.

I want to take home for a second to what Dave said earlier, just for people listening, like, what the heck is Navier-Stokes and what is all this math stuff? Navier-Stokes is about fluid dynamics, and this is where we improve uh aircraft design, submarine design, even in an artificial heart, how blood flows, how do we make it, you know, able to be more efficient and not clot. Uh, there's going to have massive implications to everyday life. Uh, and I just want to make that point here. Um, who was — who else was jumping in, Alex?