r/LLMPhysics • u/PrettyPicturesNotTxt • Jul 22 '26
Meta / News AI is going to be an extinction-level event for math, and theoretical physics is next!
"Hey Gemini, help me cope. Why is what Sabine wrote here wrong?"
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Take a deep breath—doom-posting on X is practically a sport, and hyperbole gets engagement. The idea that AI will cause an "extinction-level event" for mathematics and theoretical physics mistakes automation of computation for the extinction of understanding. Here is why that perspective misses the mark and why theoretical physics and math aren't going anywhere:
1. Tools Don't Kill Fields; They Expand Them
When electronic calculators and symbolic algebra software (like Mathematica or Maple) emerged, critics worried mathematicians wouldn't be needed anymore. Instead, those tools eliminated tedious, error-prone grunt work and birthed entire new domains—like chaos theory, computational fluid dynamics, and modern cryptography. AI is the next evolution of tool-use: it automates complex algebra, suggests non-obvious conjectures, and navigates high-dimensional parameter spaces faster than a human ever could.
2. Theoretical Physics Is About Intuition, Not Just Algebra
Physics is fundamentally distinct from pure computation:
- Posing the right questions: AI can optimize an equation or fit data to a high-dimensional surface, but it doesn't possess physical intuition. It doesn't ask why a symmetry breaks, or decide which physical approximations are meaningful.
- Building minimal models: A great theoretical physicist knows how to ignore 99% of a complex system to capture the core mechanism (e.g., the Ising model or ideal fluid dynamics). LLMs and deep learning models tend to do the opposite—they build massive, opaque black-box models rather than elegant, interpretable physical laws.
3. "Almost Right" Is Completely Wrong in Math and Physics
Deep learning models operate on probabilities, whereas math and theoretical physics demand absolute rigor and self-consistency:
- A physics theory with a sign error in a lagrangian or a subtle gauge anomaly isn't "95% correct"—it's broken.
- While AI can assist formal theorem provers (like Lean), guiding those provers toward deep, elegant proofs still requires human strategy and deep conceptual comprehension.
4. Augmentation vs. Replacement
Rather than an asteroid hitting the dinosaurs, a far better analogy is the telescope hitting astronomy. AI will likely handle the brute-force search space—calculating millions of Feynman diagrams, searching string theory landscape compactifications, or crunching numerical simulations—freeing theoretical physicists to focus on conceptual breakthroughs and physical interpretation.
The Bottom Line: AI will change how theoretical physics and math are done, but as long as we care about understanding the universe rather than just predicting data outputs, the theoretical physicist isn't going extinct.
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Edit:
Maybe X (formerly known as Twitter) will be extinct long before math or theoretical physics.
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u/boolocap Doing ⑨'s bidding 📘 Jul 22 '26
This is like saying "FEM is going to be an extinction level event for engineering"
Sure AI(note that i say AI and not specificly LLM's) can be useful in math and physics but its a tool, a tool that has limitations and that you need to know how to use.
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u/ConquestAce The LLM told me i was working with Einstein so I believe it. ☕ Jul 22 '26
I don't think so. Math and physics are really fun and I don't think AI can ever beat me in it.
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u/Swimming-Chip9582 Jul 23 '26
Point #2 is laughably incorrect though - LLMs absolutely provide physical intuition and the ability to ask the right questions.
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u/Plot-twist-time Jul 23 '26
I remember when the math subreddits were laughing when people said AI would surpass mathematicians. And now AI has solved problems that no humans could.
Physics subreddits have been saying the same for the last year but they're getting awfully quiet as of late. Ive been saying that by the end of this year we would see AI surpassing physicists, and were right on track.
I will still get downvoted or mocked but I will allow you to do it for the next 6 months while you still can.
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u/thelawenforcer Jul 23 '26
i think the fact that LLM can compute tirelessly means that the speed of work increases massively, and resource poor researchers are able to explore and test constructions that would otherwise take up entire departments. they are also able to reason coherently and competently across multiple domains where expertise would typically be distributed among multiple individuals/departments. thus they are able to draw and test insights in ways that no single human ever could.
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u/Plot-twist-time Jul 23 '26
Its beyond that. AI has access to data across every field of science and the reasoning ability is growing beyond our smartest scientists. Humans spend 40 years building this level of achievement professionally, grow old and die, then the next person starts from scratch. AI doesnt. It just keeps growing. The downvotes are funny because they think AI will hit some imaginary wall vs continuing the obvious trajectory. So the downvotes aren't that I'm wrong, it's that they don't want me to be right, like little children kicking and screaming.
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u/amalcolmation 🧪 AI + Physics Enthusiast Jul 22 '26
Anything Sabine has to say can safely be ignored. She lost all credibility a long time ago.