Episode 16: Building AI for Life Sciences
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?
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Chapters (13)
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?
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