🔬Doing Vibe Physics — Alex Lupsasca, OpenAI

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What is the breakthrough in AI that sparked the discussion on theoretical physics?

Alex Lupsasca 0:00

Okay, so I think we're at this special time now where at least in some directions, AI has become superhuman, at least on certain tasks. And that's what led to these recent papers that resolved a problem that was puzzling physicists, experts in the field for over a year, and they weren't able to resolve it and AI was able to do it very quickly. So I think that's A certain milestone that we've passed. But you guys are bringing attention to this because I I think maybe for the average person on the street who doesn't care about theoretical physics, this is not very noticeable. But I think it's a very profound change and we've really passed some kind of a

Brandon Anderson 0:40

Threshold. Welcome to the AA for Science podcast, uh part of Lean Space Network. Um, I'm Brandon. I uh develop RNA therapeutics using AI at Atomic AI. Um, I'm joined by my co-host, RJ Honicke, uh CTO and founder of Mirror Omics. Um yeah, it's a pleasure to introduce Alex Lupchowska, professor at Vanderbilt University and fellow at OpenAI. He has uh uh for a young researcher he has quite a story background amongst other things he's the uh winner of the 2024 New Verizons Breakthrough Prize. It's the uh call it the Oscars for Science. I uh asked ChatGBT is this the most prestigious award someone of his um career could win and it it recommended a second one called the IUPAP Award, which turns out to be it also won.

Brandon Anderson 1:28

Anyway, right now he uh having fun at OpenAI, uh doing some really cool research or pushing the foundation of theoretical physics using uh G3T models.

Alex Lupsasca 1:38

A pleasure to be here. The one message I wanted to convey is that I think we're on this trajectory, which I personally find very surprising and kind of surreal, but also amazing. Where I would say a little over a year ago AI was very useful for email, but not the kind of work that I do that I consider you know important theoretical physics calculations. I thought, oh, that's special and much harder than email and AI is not gonna be able to do that. And then there were a series of developments that came in rapid succession that completely changed my mind. And I can walk you through some of these examples specifically. Um, in particular, Chad GPT 03 was the first really strong reasoning model that could do actual math that was usable for my research and could save me a lot of time.

Alex Lupsasca 2:24

That's when I started to really pay attention and use it a lot more. And I thought, wow, this is a great tool. I gotta get ahead of this and learn how to integrate it into my workflow. Then when GPT-5 came out, it was able to reproduce. one of my best papers that took me a very long time to come up with. In like thirty minutes. And that's When I really became AI Pill, I thought, oh my God, I this changes everything. It's the most important discovery in my lifetime. It's gonna affect everything about how we do research. And frankly, a lot of my colleagues, I would go around telling them this currently thinking happy attention. And it Yeah, I was getting lots of different reactions, but uh I think people weren't quite getting it.

Alex Lupsasca 3:06

But I talked to OpenAI, they were also really excited. And I thought, I have I don't know that much about AI, but I have to get in on this. And to understand that this is happening and not be a part of it is a huge mistake. So I have to go to OpenAI. So I I I was on sabbatical. It was very easy to to come here and and join the company. And Then it just kept ramping up even beyond that. Um and you know, to the point where now I think most of my senior colleagues in physics are are aware of where things are are headed and they're all getting on board. So

Brandon Anderson 3:40

Yeah. I think that's an awesome story. Sorry, I was just saying like I I find it really funny that you that story because it almost reminis it reminds me of a lot of different um if you people who had the same realization with codex starting sometime last fall, especially. Uh it just took off. And a bunch of people are like, even like Andre Carfathy went from, oh man, this is you know, 20% of my work, it's kind of a nice, you know, assistant to Okra.

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Chapters

8 chapters

1 What is the breakthrough in AI that sparked the discussion on theoretical physics? 0:00–11:38 2 How did Alex Lupsasca first discover AI’s potential for solving physics calculations? 11:38–22:42 3 What was the “Move 37” moment when GPT‑5 solved a year‑long problem for Alex’s advisor? 22:42–33:29 4 Why are single‑minus gluon tree amplitudes actually non‑zero, and how did AI help prove it? 33:29–43:02 5 How did the team extend the gluon result to gravitons and generate a new paper in days? 43:02–51:49 6 What new insights about quantum gravity and scattering amplitudes emerged from the AI‑generated work? 51:49–1:04:52 7 How is AI changing the way physicists do research, teach students, and verify results? 1:04:52–1:15:53 8 What does Alex see as the future impact of AI on scientific discovery and publishing? 1:15:53–1:31:43

Speakers

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Brandon Anderson 8 min RJ Haneke 6 min

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Topics in this episode

AI 1 OpenAI 7 David 1 Harvard 1 Andy 1 Brandon 1 University of Cambridge 1 GPT-5 1 Vanderbilt University 1 Alfredo 1 Mark Chen 1 O3 1

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Recorded05 May 2026

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Show notes

Some people are going crazy over GPT 5.5. Some people. This is the story of the Jagged Frontier. People who use AI to write emails or even code implementation work find the lift moderate whereas people pushing the limits of the model are figuring out that the limits just moved outwards.Alex Lupsaska has been tracking this limit for a year and a half now. “When GPT5 came out, it was able to reproduce one of my best papers (that took a very long time to come up with) in 30 minutes.”But Alex also notes that this shift was mostly invisible.I remember when GPT-5 came out… on Twitter, the reception was lukewarm. A lot of people were like, well, we expected a lot more, and it’s not better at writing email. And I remember thinking, well, okay, GPT-3 could write email. How much better can it get at writing email? That’s not the point. But at the science frontier, the capabilities were really taking off.We walk through his paper and more with him in today’s Science pod! Watch here.The “Oscar for physics”Alex made an early splash in his career with breakthroughs in our understanding of black holes. He’s also known for Black Hole Explorer and an iPhone app that makes visualizing black holes fun and interactive to regular audiences. Alex won the 2024 New Horizons in Fundamental Physics Breakthrough Prize. Known as the “Oscar for physics” this is arguably the most prestigious prize an early stage theoretical physicist can win.Alex first saw promise for AI in theoretical physics after he asked o3 for help on his research. In the podcast, Alex recalls asking GPT for help with a calculation that would have taken days, and getting a result in eleven minutes. He immediately recognized how impactful AI would be for his work even as though his physicist colleagues and the larger community gave it a lukewarm or skeptical reception.The Move 37 Moment for AI x PhysicsGPT-5 had just been released, and Alex tried asking it to solve a problem in a just published paper. GPT-5 said no answer. But Mark Chen, CRO of OpenAI, pushed a bit harder, and had Alex prime the model with a textbook warmup problem, which it easily solved. After using this “priming” trick, GPT-5 was able to reproduce his full result in eleven minutes (yes, the paper was released after the model’s training cutoff).“This changes everything.” Alex notes that we seem to be on the edge of a massive change in theoretical physics reasoning. A year prior LLMs were just starting do correct math. Now ChatGPT could reproduce his hardest paper in the time it takes to get a coffee.Alex was on sabbatical at Vanderbilt, and he joined OpenAI to start pushing the boundary of AI’s ability to accelerate physics.“AI solved the problem before the plane landed”Alex began to put GPT through it’s paces, reaching out to colleagues for problems they were stuck on. His old PhD advisor (Prof. Andrew Storminger at Harvard) had an insidght about certain physical quantities known as “single-minus gluon tree amplitudes”. In certain cases, these amplitudes may be non-zero when previously shown to always vanish. The team pushed this intuition forward, and came up with a formula for these quantities that appeared nonzero, but which was otherwise completely intractable. Spending over a year on this problem, no real progress was made.Prof. Storminger planned to visit OpenAI to work on the problem the week after the initial conversation started. In that one week ChatGPT fully solved the problem, as Alex recalled, before Prof. Storminger’s plane even landed.What was interesting is not only that ChatGPT solved this problem, but how it solved it. The model quickly realized found a limiting case (known as the “half-collinear regime”), that in hindsight has a nice intuitive explanation. Taking this limit, the gnarly results collapsed down to a simple and intuitive formula!The last step was to prove this intuitive formula. The team started with a fresh session, gave a prompt with the context of what they previously learned, and let the model loose. Not only was ChatGPT able to reproduce the previous result, it was able to prove it using a technique unknown to the authors!The Vibe Physics momentWith a concrete success in the bag, the team asked if they could generate new physics from scratch using ChatGPT. They took on what they felt to be a harder problem, looking at the graviton, a proposed particle that should appear when one combines gravity and quantum mechanics. They wrote up a simple prompt asking ChatGPT to perform the same research as the gluon paper but instead for gravitons. And then hit go!What came next was truly “vibe physics”, with ChatGPT pushing out 110 pages of novel physics, new calculations, and novel techniques. This was over the course of a day, with most interactions the familiar following the now familiar pattern for anyone who uses a coding agent:GPT: Here's your . Would you like me to do ? Alex: Yes, please do! GPT: And for those who look deeply, this really was not just a direct 1-1 mapping between gluons and gravitons. ChatGPT imported new techniques that were necessary due to the nature of gravitons, and used them flawlessly.They spent the next three weeks verifying all the results. And voila! A new paper featuring novel results in quantum gravity, generated in less than three days total. Truly a “Feel the AGI moment”.For those interested, there’s a blog post with the full transcript from initial prompt to final paper. Even if you know no physics, it’s crazy seeing pages of correct calculations fall out of simple prompts such as “Yes calculate outside of SD first. This is the first step.”Out-of-domain = new knowledgeThe thing that is qualitatively different between Vibe Physics and Vibe Coding is that Vibe Physics means actually extending the frontier of human knowledge. Looking at the Gluon and Graviton results, they seem in retrospect, like many results in physics and math, like natural extensions of what we already know. This is in fact part of what makes them beautiful. But this was a problem that stumped experts in the domain for a year. Although it does still have a bit of a recombinant flavor, this thing has never been done before.It may be that there are still large classes of problems that AI won’t do well on, and approaches that an AI might not think to take. This is the “taste” that everyone has been talking about. Alex told us that these capabilities, however, allow him to explore many possible avenues in order to map out much more ambitious problems to tackle. With AI able to output results basically as fast as we can conceive and validate them, the scope of what one theorist can hope to achieve has just gotten a lot, lot bigger. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

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