Building AI for Life Sciences - Episode 16

About this episode

Joy Jiao and Yunyun Wang discuss the development of AI systems for life sciences and their implications for research and biosecurity.

What does it take to build AI systems that can actually help scientists? Research lead Joy Jiao and product lead Yunyun Wang discuss how OpenAI is developing models for life sciences and what responsible deployment means in a field with real biosecurity stakes. They explore how AI is already improving research workflows and where it could lead in drug discovery and more autonomous labs — including why a future with less pipetting sounds pretty good to most scientists. Chapters 0:39 Introducing the Life Sciences model series 3:47 Joy’s path into life sciences 5:00 Autonomous lab with Ginkgo Bioworks 7:27 Yunyun’s path into life sciences 8:12 OpenAI’s life sciences work 9:48 Biorisk, access, and safeguards 15:43 What models can do in the lab 17:51 Building scientific infrastructure 20:14 Why compute matters for science 24:54 Where are we in 6-12 months? 29:51 Scientific adoption and skepticism 33:17 Advice for students and researchers 40:27 Where are we in 10 years? Hosted on Acast. See acast.com/privacy for more information.

People in this episode

Guests: Joy Jiao, Yunyun Wang

Topics covered

• AI in life sciences
• biosecurity
• drug discovery
• autonomous labs
• scientific infrastructure

Keywords

• AI
• life sciences
• biosecurity
• drug discovery
• autonomous labs
• research workflows
• scientific infrastructure

Mentioned in this episode

Organizations: OpenAI, Ginkgo Bioworks

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