Episode 16: Building AI for Life Sciences

ℹ️ EPISODE INFO

Released

April 16, 2026

Duration

44m

Channel

OpenAI

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

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?

🎤 SPEAKERS

• Joy Jiao

  guest

  Research Lead for OpenAI Life Sciences with a PhD in systems biology from Harvard.

• Yunyun Wang

  guest

  Product Lead for OpenAI Life Sciences focused on responsible deployment and biosecurity safeguards.

🧾 EPISODE SUMMARY

In this episode of OpenAI, featuring Joy Jiao and Yunyun Wang, Episode 16: Building AI for Life Sciences explores openAI’s Life Sciences models: accelerating labs, discovery, and safety safeguards OpenAI is launching a Life Sciences model series focused on biochemistry workflows, starting with genomics and protein understanding for early discovery use cases.

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