Why the Next AI Breakthrough May Come from Physics with Max Welling

**Sam Charrington** (0:00)
Max, it's so great to be on the line with you again. It's been a while.

**Max Welling** (0:03)
It's great to be back, Sam. I'm looking forward to our discussion.

**Sam Charrington** (0:07)
I am as well.
Our audience can look up our conversations from, I think, 2019 and 2020, where we covered what you were working on at the time, and I think still echoes into your work today, geometric neural networks, gauge, aqua variance, neural networks and the like. But I'd love to have you catch us up on what you've been up to since. It's been quite a while. Yeah.

**Max Welling** (0:36)
Actually, the aqua variance theme has definitely continued. So in fact, I found out that aqua variance was used very fruitfully in chemistry and material science. So in chemistry and material science, people train neural network models to predict the forces on atoms because people want to evolve atoms forward in time in order to compute their properties, which is called molecular dynamics. And typically, you need to use quantum mechanics to compute these forces because a large contribution comes from the electrons, and electrons are very light.
And so you need to treat them with quantum mechanics. But if you get 10 electrons or more, it becomes completely unfeasible to solve the so-called Schrodinger equation. So people have come up with approximations like density functional theory, known as DFT, and the inventors of that got the Nobel Prize for that. But what now people do is they train surrogates. So they provide data using this expensive approximation to quantum mechanics.
And then they use neural networks to short cut the computation, so to predict the outcome of that computation, but at a much more accelerated pace. So in other words, three orders or four orders of magnitude acceleration, more efficiently relative to these quantum mechanical approximations. And in those models, because the world is three-dimensional symmetric, so if I rotate a molecule, all the forces will rotate with it. And so we could now put the same ideas that we use for images, we could put them in these molecules, these models that predict the forces, and we could use aquivariants. And so that's why I kind of, also because my background is in science, I did my PhD in theoretical physics, I thought, okay, this is a perfect unification of my old sort of passion and my new passion, I can put it together and that's when I started to be interested in AI for science.

**Sam Charrington** (2:47)
So that led to pretty directly to the founding of CuspAI.

**Max Welling** (2:51)
Actually, first I spent two years at Microsoft Research as a VP because they were building their AFS science lab in Amsterdam, and so I helped that along. But after two years, I wanted to start a startup. I already did a startup a while ago, but this was actually the startup I got acquired by Qualcomm, and then I spent some time at Qualcomm.
I really like startups, the dynamical environment and the impact you can make. I wanted to do it the Silicon Valley way together with my co-founder, Chad Edwards, and so we started CuspAI in 2024

**Sam Charrington** (3:29)
Talk a little bit about the progress that you've made since then. What is the shape of the company today?

**Max Welling** (3:36)
There's been a huge ride actually. It's a roller coaster. So we started, I think, about two years ago, so May, spring 24
Yeah, we started with a good initial investment of about 30 million from which we could hire an excellent team. The team has grown to about 50 people right now across different geographies. So there's a headquarter both in Amsterdam and in Cambridge. Actually, the headquarter officially is in Cambridge, so the two initial labs were Amsterdam and Cambridge, because Chad is from Cambridge and I'm from Amsterdam. We now also have labs in London and Berlin, and we're also expanding into Asia and North America.

**Sam Charrington** (4:26)
Got it. And no surprise, your list of advisors is a bit of a who's who with Jeff Hinton and Jan LeCun at the top of the list.

**Max Welling** (4:35)
Yes. Yeah, the advisors are actually fantastic. So we have Jeff Hinton and Jan LeCun.
We added to that also Martin Van Dambrink and Lord Brown. So Lord Brown is the former CEO of BP. And Martin Van Dambrink is the former president and CTO of ASML. They're both retired and they like to spend their time with new startups and help them along. And then there's Verity Harding. She's working for the UK government and also DeepMind. And then, or maybe Formonia DeepMind. And then Kristen Person, who has sort of initiated the Materials Project.