Generative AI is unlocking new research tools for bold scientific discoveries. We sort through the hype and take a deep dive into some practical examples of groundbreaking research enabled by generative AI such as small molecular inhibitors for treating infectious disease and the discovery of new materials for energy storage. As researchers reduce the discovery time from years to months, how are they ensuring that safe and responsible practices are used to instill public trust in the process?
0:00 Introduction
0:23 Scientific discovery is the most important use of AI
1:23 What Large Language Models bring to science
2:06 What makes scientific discovery different?
3:40 Prior knowledge
6:19 "No-free-lunch theorem"
9:16 Generative AI model MatterGen
9:55 Drug discovery and deep learning
14:12 Large Language Models v other training models
15:40 The evolution of generative AI models
16:37 How generative AI models can assist scientists
19:08 The role of AI in drug development
22:35 How Large Language Models can work with science-based models
26:00 Looking ahead for AI in science
MIT Technology Review's EmTech Digital: [ Ссылка ]
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