
Institute for Pure & Applied Mathematics (IPAM)
The Institute for Pure and Applied Mathematics (IPAM) is a National Science Foundation Math Institute at the University of California, Los Angeles (UCLA) that fosters the interaction of mathematics with a broad range of science and technology, builds new interdisciplinary research communities, promotes mathematical innovation, and engages and transforms the world through mathematics. IPAM fulfills its mission through workshops and programs that connect mathematics and other disciplines or multiple areas of mathematics. These activities bring in thousands of visitors annually from academia, government, and industry. The NSF has encouraged IPAM to make the scientific presentations of our speakers available to a wider audience. While this YouTube channel contains many of our most popular videos, our full video archive is available at www.ipam.ucla.edu/videos.
Episodes


David Spivak - Sense-making: accounting for intelligibility - IPAM at UCLA

Fei Fang - Machine Learning and Game Theory for Social Impact - IPAM at UCLA

Jacob Foster - Institutions, innovation, and the social production of collective (un)intelligence

Pranab Das - Broadening the reach of mathematical approaches to the study of intelligences

Patrick Shafto - Cooperative communication as Belief Transport - IPAM at UCLA

Nika Haghtalab - Learning and Persuading with Anecdotes - IPAM at UCLA

Michael Muthukrishna - Paradox of diversity in the collective brain - IPAM at UCLA

Ali Jadbabaie - Persuasion, news sharing, and cascades on social networks - IPAM at UCLA

Robert Batterman - Mesoscale Models and Many-Body Systems - IPAM at UCLA

Josh Bongard - A xither of xenobots: demolishing dichotomous thinking with synthetic proto-organisms

Michael Levin - Plasticity w/out genetic change: bioelectric embryos & synthetic proto-organisms

David Ha - Collective Intelligence for Deep Learning: A Survey of Recent Developments

Orit Peleg - Physical Computation in Insect Swarms - IPAM at UCLA

Max Kleiman-Weiner - Multi-Agent Common Sense - IPAM at UCLA

Lisa Lee - Learning to Explore with Scalable Supervision - IPAM at UCLA

Elchanan Mossel - Some mathematical theorems on agreement and learning in networks - IPAM at UCLA

John Baez - Categories: the Mathematics of Connection - IPAM at UCLA

Lillian Ratliff - Learning via Conjectural Variations - IPAM at UCLA

Jessica Flack - Collective intelligence as collective computation: Future directions
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