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Explore how foundation models trained on vast, diverse datasets can revolutionize autonomous vehicle development in this seminar from New York University's ECE AI series. Discover recent research efforts that rethink key elements of autonomous vehicle programs, both in vehicles and data centers, with particular focus on three critical areas: composing ingredients for universal and controllable end-to-end simulation systems, architecting autonomy stacks that leverage foundation models to handle long-tail events and edge cases, and ensuring safety protocols when foundation models are integrated into autonomous driving systems. Learn how the principles and lessons from foundation model construction can be applied to develop transformative autonomous vehicle technology, drawing parallels between the AI revolution in general computing and its potential impact on transportation systems.
