Seminar

Abstract: Recent progress in AI can be attributed to the emergence of large models trained on large datasets. However, teaching AI agents to reliably interact with our physical world has proven challenging, which is in part due to a lack of large and sufficiently diverse robot datasets. In this talk, I will cover ongoing efforts of the Open X-Embodiment project–a collaboration between 279 researchers across 20+ institutions–to build a large, open dataset for real-world robotics, and discuss how this new paradigm is rapidly changing the field. Concretely, I will discuss why we need large datasets in robotics, what such datasets may look like, and how large models can be trained and evaluated effectively in a cross-embodiment cross-environment setting. Finally, I will conclude the talk by sharing my perspective on the limitations of current embodied AI agents, as well as how to move forward as a community.

Speaker: Sarah H. Cen Abstract: We have begun grappling with difficult questions related to the rise of AI, including: What rights do individuals have in the age of AI? When should we […]

Abstract: Although influenza is one of the best-studied viruses, vaccine effectiveness remains around 20-50%. A sizable fraction of people exhibit a weak or short-lived antibody response following vaccination, yet we cannot […]

When Monday July 22nd 2:00pm Where: HDSI MPR 123 Zoom Info: http://bit.ly/HDSI-Seminars Title: "Tackling Acute Respiratory Distress Syndrome (ARDS) : Integrated and Holistic Approaches" Abstract: ARDS is a complex heterogenous disorder which forms a […]

When Wednesday July 24th 10:00am *Updated Where: HDSI 123 * Updated Zoom Info: https://ucsd.zoom.us/j/99334315002 *Updated Title: What Kinds of Functions do Neural Networks Learn?  Theory and Practical Applications Abstract:  This talk presents a theory characterizing […]

Beyond their use in traditional data analytics problems, AI and Machine Learning techniques are changing the way real-world complex systems (like vehicles, airplanes, and even industrial production lines) are designed, […]

ABSTRACT The advent of deep learning has completely revolutionized how we perceive data to obtain superhuman performance across all fields of modern science. However, despite the remarkable empirical successes of […]

Talk Information: When Wednesday Oct 30th 1:00pm Where: HDSI MPR 123 Zoom Info: http://bit.ly/HDSI-Seminars Title: Modeling and Inference of Complementarity Mechanisms in Networks. Abstract: "In many networks, including networks of protein-protein interactions, […]