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A Center for Neural Data Science Seminar Series
A Center for Neural Data Science Seminar Series
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
Hear from speakers and attendees at recent Stanford HAI events across research, policy, and education.
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
The past decade’s series of dramatic AI successes has brought us closer to realizing the dream of the autonomous agent—an artificial system that can learn about its world, make decisions, and set and achieve goals, all with minimal human intervention.
The past decade’s series of dramatic AI successes has brought us closer to realizing the dream of the autonomous agent—an artificial system that can learn about its world, make decisions, and set and achieve goals, all with minimal human intervention.