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This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
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.
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.
This seminar co-hosted with the AI Measurement Science Center (AIMS) invites speakers to discuss academic work in AI evaluation and measurement science.
This seminar co-hosted with the AI Measurement Science Center (AIMS) invites speakers to discuss academic work in AI evaluation and measurement science.
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.
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.
Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.
Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.
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.
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.
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.
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.
Hear from speakers and attendees at recent Stanford HAI events across research, policy, and education.
Much of what we know today about global events - like Russia's invasion of Ukraine or North Korea’s advancement towards nuclear capability - has come from satellite sensors that collect optical images of the earth's surface.
Much of what we know today about global events - like Russia's invasion of Ukraine or North Korea’s advancement towards nuclear capability - has come from satellite sensors that collect optical images of the earth's surface.
Welcome to Stanford Human-Centered AI Vodcast, where we don't sweep anything under the rug; where we question everything, starting with ourselves.
Welcome to Stanford Human-Centered AI Vodcast, where we don't sweep anything under the rug; where we question everything, starting with ourselves.
In this seminar, Mark Russinovich, Azure CTO and Technical Fellow, gave an under-the-hood look at Microsoft’s AI architecture, including the large-scale supercomputers that train foundational models and the infrastructure that efficiently serves small and large pretrained and fine-tuned models.
In this seminar, Mark Russinovich, Azure CTO and Technical Fellow, gave an under-the-hood look at Microsoft’s AI architecture, including the large-scale supercomputers that train foundational models and the infrastructure that efficiently serves small and large pretrained and fine-tuned models.
In the 17th century, the Cartesian coordinate system exposed the unity between algebra and geometry, accelerating the development of the math that took humans to the moon.
In the 17th century, the Cartesian coordinate system exposed the unity between algebra and geometry, accelerating the development of the math that took humans to the moon.
When use of a healthcare AI tool harms patients, who is responsible? This session will examine how courts are grappling with the challenges of adjudicating liability for software-related injuries and how health systems and clinicians can assess and manage AI liability risk.
When use of a healthcare AI tool harms patients, who is responsible? This session will examine how courts are grappling with the challenges of adjudicating liability for software-related injuries and how health systems and clinicians can assess and manage AI liability risk.
Constitutive modeling and parameter identification are the cornerstones of realistic biomedical simulations. For decades, the gold standard in biomedical modeling has been to select a model and then fit its parameters to data. However, the scientific criteria for model selection remain poorly understood, and the success of this approach depends largely on user experience and personal preference.
Constitutive modeling and parameter identification are the cornerstones of realistic biomedical simulations. For decades, the gold standard in biomedical modeling has been to select a model and then fit its parameters to data. However, the scientific criteria for model selection remain poorly understood, and the success of this approach depends largely on user experience and personal preference.
What do we (really) want from artificial intelligence? We live in a time when advancements in AI technology is shaping our world, while critically outpacing our understanding of this technology in various humanistic contexts (cultural, social, ethical, historical).
What do we (really) want from artificial intelligence? We live in a time when advancements in AI technology is shaping our world, while critically outpacing our understanding of this technology in various humanistic contexts (cultural, social, ethical, historical).
On Monday, October 30th 2023, President Biden signed a landmark Executive Order to manage the opportunities and risks of artificial intelligence.
On Monday, October 30th 2023, President Biden signed a landmark Executive Order to manage the opportunities and risks of artificial intelligence.
AI red teaming is exploding in popularity: At DEF CON this year, more than 2,500 hackers descended to red-team AI systems. Every organization investing in AI—from Microsoft to Google to Meta to NVIDIA—has AI red teams to actively secure their AI systems
AI red teaming is exploding in popularity: At DEF CON this year, more than 2,500 hackers descended to red-team AI systems. Every organization investing in AI—from Microsoft to Google to Meta to NVIDIA—has AI red teams to actively secure their AI systems