Yunyun Wang

Yunyun Wang, product lead on OpenAI’s life sciences models focusing on bio-risk mitigation. Joy Jiao, research lead linking AI to wet labs and systems biology. They discuss building biology-focused models, safeguards and differentiated access, AI-driven lab automation and autonomous labs, and near-term impacts like drug repurposing and assay-driven evaluation.

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.Chapters0:39 Introducing the Life Sciences model series3:47 Joy’s path into life sciences5:00 Autonomous lab with Ginkgo Bioworks7:27 Yunyun’s path into life sciences8:12 OpenAI’s life sciences work9:48 Biorisk, access, and safeguards15:43 What models can do in the lab17:51 Building scientific infrastructure20:14 Why compute matters for science24:54 Where are we in 6-12 months?29:51 Scientific adoption and skepticism33:17 Advice for students and researchers40:27 Where are we in 10 years? Hosted on Acast. See acast.com/privacy for more information.