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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 October 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.
Open to Stanford community members! We are hosting an interactive orientation featuring faculty insights, networking, and opportunities to explore AI and data science research, programs, and resources across Stanford.
Open to Stanford community members! We are hosting an interactive orientation featuring faculty insights, networking, and opportunities to explore AI and data science research, programs, and resources across Stanford.
As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.
As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.
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.
The report documents what it calls the scaling era — the five years in which generative AI moved from research preview to a technology used daily by a substantial share of the world's population. The talk traces its findings across twelve standing questions and two deep dives, covering advances in reasoning models and agentic systems, the geopolitics of compute and data, and the contested evidence on AI's effects on work. It closes by revisiting the 2021 panel's predictions, asking why the field's own insiders underestimated how far scaling the transformer would go — and what that suggests about forecasting what comes next.
The One Hundred Year Study on Artificial Intelligence (AI100) is a longitudinal effort administered out of Stanford HAI and managed by a standing committee of AI experts from around the world, chaired by Sheila McIlraith, Professor of Computer Science at the University of Toronto. Its mission is to assess AI not as a snapshot, but as an evolving force across technical, ethical, economic, and societal domains. Every five years, we return to the same standing questions and answer them anew in a changed world.
