AI in Materials Discovery
Ekin discusses the ongoing need for experimental validation in materials science, emphasizing that while AI can aid in predictions, it cannot fully replace lab work. The conversation highlights the importance of creating large datasets for training machine learning models, particularly in the context of startups focusing on innovative materials for climate solutions, such as metal-organic frameworks for carbon capture.In this clip
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Catalyst with Shayle Kann
Can AI revolutionize materials discovery?
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