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Please note that this event is open to Stanford affiliates only.
Please note that this event is open to Stanford affiliates only.
A Center for Neural Data Science Seminar Series
A Center for Neural Data Science Seminar Series
This in-person event is open to current Stanford faculty, students, and staff. ID will be required at check in. Other guests are invited to join the webinar.

This in-person event is open to current Stanford faculty, students, and staff. ID will be required at check in. Other guests are invited to join the webinar.

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
An AI Measurement Science (AIMS) Seminar Series
An AI Measurement Science (AIMS) Seminar Series
Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.
Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.
In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.
In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.
This talk will cover key insights from the third AI100 report, AI Goes Mainstream: The Scaling Era and the Rise of Generative AI, set for release in November 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.
This talk will cover key insights from the third AI100 report, AI Goes Mainstream: The Scaling Era and the Rise of Generative AI, set for release in November 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies.
Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies.
A Center for Neural Data Science Seminar Series
A Center for Neural Data Science Seminar Series
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced statistical and computational methods.
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced statistical and computational methods.
Hear from speakers and attendees at recent Stanford HAI events across research, policy, and education.
The rapid growth of large language models has created new challenges for the Wikimedia Foundation in managing changing traffic patterns while upholding its free knowledge mission and fostering human engagement.
The rapid growth of large language models has created new challenges for the Wikimedia Foundation in managing changing traffic patterns while upholding its free knowledge mission and fostering human engagement.
Join HAI Policy Fellow Riana Pfefferkorn for a conversation about the potential future(s) of AI and humanity with Adam Becker, author of More Everything Forever, and Jon Evans, author of Exadelic and the Gradient Ascendant newsletter.
Join HAI Policy Fellow Riana Pfefferkorn for a conversation about the potential future(s) of AI and humanity with Adam Becker, author of More Everything Forever, and Jon Evans, author of Exadelic and the Gradient Ascendant newsletter.
Join us for a fireside chat about AI's impact on the world with distinguished technology executive Craig Mundie and New York Times columnist Thomas Friedman. Former Stanford President John Hennessy will moderate the discussion. Welcome remarks will be provided by Colin Kahl, director of the Freeman Spogli Institute for International Studies.
Join us for a fireside chat about AI's impact on the world with distinguished technology executive Craig Mundie and New York Times columnist Thomas Friedman. Former Stanford President John Hennessy will moderate the discussion. Welcome remarks will be provided by Colin Kahl, director of the Freeman Spogli Institute for International Studies.
Visiting scholars share their research with the HAI community.
Visiting scholars share their research with the HAI community.
Join us online December 9-10, for Stanford's largest annual convening of AI+HEALTH experts and learners
Join us online December 9-10, for Stanford's largest annual convening of AI+HEALTH experts and learners