Revolutionizing Autonomous Vehicle Development with Foundation Models

Title: Revolutionizing Autonomous Vehicle Development with Foundation Models
 
Presentor: Boris Ivanovic

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Abstract:
Foundation models, trained on vast and diverse data encompassing a breadth of human experiences, are at the heart of the ongoing AI revolution influencing the way we create, problem solve, and work. These models, and the lessons learned from their construction, can also be applied to the way we develop a similarly transformative technology: autonomous vehicles (AVs). In this talk, I’ll highlight recent research efforts toward rethinking elements of an AV program both in the vehicle and in the data center, with an emphasis on (1) composing ingredients for universal and controllable end-to-end simulation, (2) novel end-to-end AV architectures that are built from the ground up to harness foundation models, and (3) enabling generalization to multiple geographies by leveraging video generation models and improving their consistency with techniques from neural rendering.
 
Short Bio: Boris is a Senior Research Scientist and Manager in NVIDIA's Autonomous Vehicle Research Group. His research interests include novel end-to-end AV architectures, sensor and traffic simulation, AI safety, and the thoughtful integration of foundation models in AV development. Prior to joining NVIDIA, he received his Ph.D. in Aeronautics and Astronautics under the supervision of Marco Pavone in 2021 and an M.S. in Computer Science in 2018, both from Stanford University. He received his B.A.Sc. in Engineering Science from the University of Toronto in 2016.

Welcome!
Boris Ivanovic and Lars Hammarstrand