Daphne Koller — Digital Biology and the Next Epoch of Science

Gradient Dissent: Conversations on AI - Un pódcast de Lukas Biewald

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From teaching at Stanford to co-founding Coursera, insitro, and Engageli, Daphne Koller reflects on the importance of education, giving back, and cross-functional research. Daphne Koller is the founder and CEO of insitro, a company using machine learning to rethink drug discovery and development. She is a MacArthur Fellowship recipient, member of the National Academy of Engineering, member of the American Academy of Arts and Science, and has been a Professor in the Department of Computer Science at Stanford University. In 2012, Daphne co-founded Coursera, one of the world's largest online education platforms. She is also a co-founder of Engageli, a digital platform designed to optimize student success. https://www.insitro.com/ https://www.insitro.com/jobs https://www.engageli.com/ https://www.coursera.org/ Follow Daphne on Twitter: https://twitter.com/DaphneKoller https://www.linkedin.com/in/daphne-koller-4053a820/ Topics covered: 0:00​ Giving back and intro 2:10​ insitro's mission statement and Eroom's Law 3:21​ The drug discovery process and how ML helps 10:05​ Protein folding 15:48​ From 2004 to now, what's changed? 22:09​ On the availability of biology and vision datasets 26:17​ Cross-functional collaboration at insitro 28:18​ On teaching and founding Coursera 31:56​ The origins of Engageli 36:38​ Probabilistic graphic models 39:33​ Most underrated topic in ML 43:43​ Biggest day-to-day challenges Get our podcast on these other platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/google-podcasts YouTube: http://wandb.me/youtube Soundcloud: http://wandb.me/soundcloud Tune in to our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research: http://wandb.me/salon Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices: https://wandb.ai/gallery

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