Uploaded April 2026 | Updated September 2026, 2 weeks ago
Trustworthy machine learning requires models that still work when real-world data changes, and Adam Klivans, Ph.D., Director of the Institute for Foundations of Machine Learning (IFML), emphasizes learning under “distribution shift” as a major barrier to relying on models to predict disease across different patient populations. IFML focuses on foundational algorithms and mathematical techniques that push generative AI forward, including better methods for training and inference in deep learning and advances in diffusion approaches. Klivans highlights robustness and safety as core priorities, asking how to trust a model trained in one setting when it is applied in another. IFML connects these foundations to use-inspired domains such as imaging, protein engineering and biologics, and AI for mathematical discovery. [Show ID: 40972]
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Science and technology continue to change our lives. University of California scientists are tackling the important questions like climate change, evolution, oceanography, neuroscience and the potential of stem cells.
UCTV is the broadcast and online media platform of the University of California, featuring programming from its ten campuses, three national labs and affiliated research institutions. UCTV explores a broad spectrum of subjects for a general audience, including science, health and medicine, public affairs, humanities, arts and music, business, education, and agriculture. Launched in January 2000, UCTV embraces the core missions of the University of California -- teaching, research, and public service – by providing quality, in-depth television far beyond the campus borders to inquisitive viewers around the world.
(https://www.uctv.tv)
Trustworthy machine learning requires models that still work when real-world data changes, and Adam Klivans, Ph.D., Director of the Institute for Foundations of Machine Learning (IFML), emphasizes learning under “distribution shift” as a major barrier to relying on models to predict disease across different patient populations. IFML focuses on foundational algorithms and mathematical techniques that push generative AI forward, including better methods for training and inference in deep learning and advances in diffusion approaches. Klivans highlights robustness and safety as core priorities, asking how to trust a model trained in one setting when it is applied in another. IFML connects these foundations to use-inspired domains such as imaging, protein engineering and biologics, and AI for mathematical discovery. [Show ID: 40972]
Donate to UCTV to support informative & inspiring programming:
uctv.tv/donate
More videos from: Science Like Me +
(uctv.tv/data-science/science-like-me-plus)
More from: Data Science Channel
(uctv.tv/data-science)
Explore More Science & Technology on UCTV
(uctv.tv/science)
Science and technology continue to change our lives. University of California scientists are tackling the important questions like climate change, evolution, oceanography, neuroscience and the potential of stem cells.
UCTV is the broadcast and online media platform of the University of California, featuring programming from its ten campuses, three national labs and affiliated research institutions. UCTV explores a broad spectrum of subjects for a general audience, including science, health and medicine, public affairs, humanities, arts and music, business, education, and agriculture. Launched in January 2000, UCTV embraces the core missions of the University of California -- teaching, research, and public service – by providing quality, in-depth television far beyond the campus borders to inquisitive viewers around the world.
(https://www.uctv.tv)
