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The Machine Learns Medicine: Daphne Koller’s Vision for AI in Biotech

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Manage episode 493286047 series 2728623
Content provided by Fortune. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fortune or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Daphne Koller, CEO of insitro and cofounder of Coursera, joins Leadership Next to unpack a bold idea: Just as calculus revolutionized our understanding of physics, AI could do the same for biology. In this episode, Koller explains how insitro is blending biology and machine learning to unlock new treatments for diseases like ALS and fatty liver. She also opens up about her leap from academia to entrepreneurship, the ethical challenges of data collection, and why the future of medicine lies in personalized, AI-driven care. Plus, her take on why humans and machines must work in tandem to drive meaningful innovation.

  continue reading

237 episodes

Artwork
iconShare
 
Manage episode 493286047 series 2728623
Content provided by Fortune. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fortune or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Daphne Koller, CEO of insitro and cofounder of Coursera, joins Leadership Next to unpack a bold idea: Just as calculus revolutionized our understanding of physics, AI could do the same for biology. In this episode, Koller explains how insitro is blending biology and machine learning to unlock new treatments for diseases like ALS and fatty liver. She also opens up about her leap from academia to entrepreneurship, the ethical challenges of data collection, and why the future of medicine lies in personalized, AI-driven care. Plus, her take on why humans and machines must work in tandem to drive meaningful innovation.

  continue reading

237 episodes

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