Daphne Koller | How machine learning could save millions of lives

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Previously titled “How machine learning could save millions of lives | Daphne Koller” — renamed by the publisher on Aug 6, 2026

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Recorded26 Jun 2025

Publisheranchor.fm ↗

Handlerec:568160

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This episode is part of our “Summer Selects” series—curated archival episodes that shifted our perspective and are worth revisiting.Daphne Koller—AI pioneer, founder of Coursera, and CEO of Insitro—sits down with Sana founder and CEO Joel Hellermark to explore the groundbreaking intersection of digital technology, scientific discovery, and human health.In this episode of Strange Loop, Daphne shares her inspiring journey from a prodigious student to leading some of the most important advances in AI, education, and biotech. She reveals how machine learning is unlocking the secrets of biology, enabling new treatments, and offering hope for solving some of humanity’s toughest medical challenges.Daphne also discusses the ethical challenges, the importance of collaboration across fields, and her vision for a future where AI and biology together unlock new possibilities for patients worldwide.What's in this episodeFrom early academic prodigy to founding Coursera and InsitroHow AI and massive datasets are transforming drug discovery and biologyWhy data quality and removing human bias are key to scientific breakthroughsThe exponential growth curves in AI and genomics—and why we’re at an inflection pointChallenges and opportunities in building high-impact, interdisciplinary teamsThe future of healthcare: personalized medicine, early detection, and longer, healthier livesReflections on culture, leadership, and inspiring the next generation of scientists and engineers—Transcript: https://sanalabs.com/strange-loop/daphne-koller—About Strange LoopStrange Loop is a podcast about how artificial intelligence is reshaping the systems we live and work in. Each episode features deep, unscripted conversations with thinkers and builders reimagining intelligence, leadership, and the architectures of progress. The goal is not just to follow AI’s trajectory, but to question the assumptions guiding it.Subscribe for more conversations at the edge of AI and human knowledge.—Timestamps(00:00:00) Early days of AI(00:04:12) Intersecting biology & AI(00:06:22) Predicting biology(00:10:12) insitro’s vision(00:12:30) Harmonizing datasets(00:13:53) Finding patterns(00:15:39) Addressing biases(00:17:02) Importance of finetuning(00:19:35) Layers of multimodality(00:21:34) Actionable insights(00:23:57) Bilingual colleagues(00:26:14) Biologists’ future(00:29:25) Eroom’s Law(00:34:57) Lack of data(00:39:51) Incentivizing scientists(00:43:56) Daphne’s motivation(00:46:40) Future of medicine—Where to find DaphneLinkedIn: https://www.linkedin.com/in/daphne-koller-4053a820/X: https://x.com/daphnekoller—Where to find JoelLinkedIn: https://www.linkedin.com/in/joel-hellermark/X: https://x.com/joelhellermark

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