DeepMind researcher explains why AI hasn't transformed physics yet
DaniloJRezende · x · 2026-09-27
Responding to a question about why the theoretical physics community has been slow to react to AI advances, DeepMind researcher DaniloJRezende offered a four-point explanation:
- Practical physics isn't that math-dependent: most work applies equations derived a century ago to novel problems, so AI's math prowess translates poorly.
- Advanced mathematical physics remains too hard for AI, while numerical methods have sufficed for decades for most real physics problems.
- Much of what passes for "advanced theoretical physics" is math disconnected from reality, so AI progress there would barely matter.
- The truly hard breakthroughs require deep insights outside the "convex hull" of current human knowledge — largely invisible to today's AI.
He agrees physics will eventually have to rethink how it trains students.
Related event: Why theoretical physics lags in responding to AI progress(2 posts)→
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