In this episode, we dive into the fascinating world of AI-driven scientific discovery with our guest Prof. Jilles Vreeken. We explore how machine learning is revolutionizing materials science, from predicting crystallization structures to uncovering hidden patterns in data. Discover the surprising challenges of AI in medical diagnostics, including why some COVID-detection models failed in real-world applications. We also break down the classic "shark attacks vs. ice cream sales" paradox to highlight the importance of distinguishing correlation from causation. Plus, our guest shares their favorite material—one that powers nearly all modern technology. Join us for an engaging conversation on the future of AI, scientific breakthroughs, and the tools that will shape tomorrow’s discoveries.To learn more about Jilles , check out this webpage - https://cispa.de/de/people/jilles.vreekenTo get to know what our host, Shrikrishnan Sankaran, does, check out his group's webpage - https://www.leibniz-inm.de/en/research/research-groups/bioprogrammable-materials/You can also find him on Bluesky ( https://bsky.app/profile/shrikrishnans.bsky.social ), LinkedIN ( https://www.linkedin.com/in/shrikrishnans/ ), and Instagram ( https://www.instagram.com/shirish.sankaran/ ) To get to know more about the Leibniz Institute for New Materials, visit us at https://www.leibniz-inm.de/en/ or find us on Bluesky ( https://twitter.com/Leibniz_INM ), LinkedIN ( https://www.linkedin.com/company/inm-leibniz-institute-for-new-materials/ ), and Instagram ( https://www.instagram.com/leibniz_inm/ )Recording and editing by INM's communication designer, Lars Knaack - https://www.leibniz-inm.de/en/staff/b-a-knaack-lars/

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