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Could an AI physicist soon out-innovate Einstein?
In this exciting interdisciplinary exploration, UC San Diego’s Rose Yu dismantles the romantic myth of genius-driven science and instead offers a thrilling look at how AI could become not just a computational tool, but a genuine partner in discovery. Rose draws from her pioneering work in traffic forecasting, pandemic modeling, and high-energy physics to show how machine learning is evolving and what it can offer to the scientific community.
She walks us through the fascinating ways AI is already helping us rethink what’s possible in science: from generating novel hypotheses to rediscovering fundamental symmetries, and even beating traditional simulations in both speed and precision. With her characteristic clarity, Rose explains how she’s built data-driven surrogates for complex phenomena like the spread of epidemics and the turbulence of fluids. We also tackle some of the more existential questions: Can an AI ever experience “happy thoughts”? How close are we to AGI? And should we be worried about AI replacing us?
If science is humanity’s greatest invention, this episode is a fascinating look at its future.
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Key Takeaways:
00:00 Intro
01:04 Can an AI physicist out-innovate Einstein?
02:07 Why are GPUs so good for AI?
12:24 Traffic modeling and AI
16:08 Is AI just imitating physics?
24:53 Epidemiology modeling and AI
30:49 Should we be worried about AGI?
34:32 The benefits and dangers of AI
39:53 AI scientists and scientific productivity
42:19 The impact of AI on academia and education
52:34 Outro
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Additional resources:
💻 Rose Yu’s website: https://roseyu.com/
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Into the Impossible with Brian Keating is a podcast dedicated to all those who want to explore the universe within and beyond the known.
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