AI Summer Charles Yang on AI and Science
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Apr 7, 2025 In this engaging conversation, Charles Yang, a former Department of Energy staffer and the mind behind the Rough Drafts newsletter, discusses AI's transformative potential in science. He dives into how AI can revolutionize materials science and biology, emphasizing the development of self-driving labs that automate experiments. The talk also highlights the complexities of integrating AI with quantum computing and the need for robust experimental databases. Yang shares insights on the challenges of making scientific research more efficient and reproducible.
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Two Routes for AI in Science
- AI can advance science by being smart thinkers in data centers or by processing data to find new insights.
- Scientific texts are not always information-dense and can be difficult to reproduce, while surrogate models using data are more efficient.
Google's Co-Scientist Project
- Google's co-scientist paper demonstrates a multi-agent AI system producing new scientific knowledge, a significant threshold.
- While the discoveries themselves were routine advancements, the fact that an AI system achieved them is a breakthrough.
AI in Drug Discovery
- Google's AI model has been applied to drug repurposing, drug activity for liver fibrosis, and antimicrobial resistance.
- Experimental validation remains crucial but is often bottlenecked by the need to translate findings to the real world.