🔬Doing Vibe Physics — Alex Lupsasca, OpenAI

May 5, 2026

AI Summary

5 min read

Alex Lupsasca, a Vanderbilt physics professor, OpenAI fellow, and 2024 Breakthrough Prize winner, discusses how AI models like GPT-4o and o1-pro have shifted from email assistants to tools solving frontier theoretical physics problems. In recent papers co-authored with experts like Andrew Strominger, AI rapidly derived simple formulas for scattering amplitudes previously stumping researchers for a year, marking a threshold where AI outperforms humans on specific tasks.

Core Physics Concepts

Quantum field theory (QFT) reconciles relativity—no faster-than-light information—and quantum uncertainty by predicting probabilities via scattering amplitudes. These complex-valued functions describe particles smashing together (e.g., at LHC), with inputs like energy, momentum, and helicity (polarization handedness, like light's twist visible through polarized sunglasses). Amplitudes square to probabilities; knowing all n-point amplitudes (for n particles) encodes a theory's content.

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What you'll learn

1 (00:00) **AI Surpasses Human Physicists** - Alex introduces AI solving year-long physics puzzles quickly, marking a superhuman threshold.
2 (00:40) **Guest Introduction and Background** - Hosts introduce Alex Lupsasca, Vanderbilt professor, OpenAI fellow, Breakthrough Prize winner.
3 (01:38) **Alex's AI Awakening Timeline** - Details progression from GPT-3.5 saving time to GPT-4o reproducing his best paper in 30 minutes.
4 (04:07) **Model Capability Jumps** - Discusses GPT-4o's science leaps vs. lukewarm public reception; examples like Codex simulating SYK model.
5 (06:46) **Core Physics Principles** - Explains relativity (no faster-than-light info) vs. quantum uncertainty tension.
6 (08:20) **Quantum Amplitudes in QFT** - Defines amplitudes as complex objects squaring to probabilities for particle interactions.
7 (11:16) **Particle Polarizations and Helicity** - Describes helicity (right/left-handed spin) via photon polarization example.

+ Full timestamped outline available in the app

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 Physics

GPT-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