Jonathan Gorard: The Physicist Revolutionizing Physics With AI

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Jonathan Gorard (0:30)

The timelines were completely wrong. I was scared on a very personal level. We're not putting the genie back in the bottle.

Curt Jaimungal (0:35)

This is Jonathan Gorard, an applied mathematician, co-founder of the Wolfram Physics Project and CEO of the newly founded Lanyon AI. He's one of the physicists revolutionizing how AI can make scientific progress, which is distinct from just mathematical or code-based progress, which is what everyone else is focusing on.

Jonathan Gorard (0:54)

We want to make physics executable in the same way that software is executable and that now increasingly mathematics is executable.

Curt Jaimungal (1:01)

Just like the recent interview with Fields Medalist Jacob Simmerman, we focused today on how AI will impact mathematicians and physicists.

Jonathan Gorard (1:08)

Do I grieve a particular subset of physics? Yes, we are not prepared for this. I'm in a continual process of grief.

Curt Jaimungal (1:16)

On this channel, I, Curt Jaimungal, interview researchers regarding their theories of reality with rigor and technical depth. Today, we discuss what our place will be once we can ostensibly solve any problem with a single prompt, and how Jonathan's new company is fixing the foundational problem with traditional AI approaches, regarding that distinction between math and science. We start with the moment that changed everything about physics for Jonathan Gorard.

Jonathan Gorard (1:41)

Yeah, so that came probably, well, definitely a lot later than arguably it should have done, and certainly a lot later than it did for many people. So that moment was a very well-defined moment in the beginning of March, 2026

So I had been, I think, like the rest of the world, following kind of the progressive march of AI capabilities from, I guess, late 2021 onwards, and getting increasingly excited and increasingly concerned about figuring out, okay, what is the direction this is going in, et cetera. But I was still, right up to the start of this year, I was still viewing it as just, this is an interesting thing that's happening in the world. Let's try and think about it. Let's try and analyze it in the kind of normal ways that I have tended to think about and analyze technologies and developments.

And then in March 2026, there was this big auto-formalized proof dropped by this startup, Math Inc, of the Marina Wierzowska 1824 dimensional sphere packing problem that she won the Fields Medal for, completely done autonomously end-to-end using effectively an AI harness. And, you know, it was, so, you know, for context, like I had spent a decade or so working about and thinking, working on and thinking about, you know, automated theory-improving techniques and proof assistance. In fact, that was originally, about 10 years ago, that was originally what I was recruited to, to Wolfram Research to work on, was to develop kind of automated theory-improving capabilities. So I thought I had a pretty good sense of how difficult a problem like this was going to be, you know, the problem of doing an automated proof of correctness for a Fields Medal winning result. I had some intuition for how difficult this was, so I thought. And I thought by tracking kind of the progress of AI capabilities, I thought that I had some sense of when this was going to be on. It was clear that, you know, AI would eventually reach the point where it could do that. But I was, if you'd asked me in January 2026, I was very confident that this wouldn't happen until, you know, late 2027 at the latest, sorry, at the earliest and maybe 2028 as a kind of more reasonable timeframe. So the fact that on, you know, at the beginning of March, there is this like multi-hundred thousand line, fully autonomously generated lean proof of this result. That just gets dropped. That, you know, that for me was the oh shit moment. That was the moment where I realized I was thinking about this completely wrong. The timelines were completely wrong. And that, you know, on a more kind of personal level, that my way of life and my plans for the future of how I thought my life was going to go, just were not, you know, they were not going to survive in any reasonable sense. And that this was not something I could ignore for very much longer. That was very much the moment.