In this talk, Clément Farabet, VP of AI Infrastructure at NVIDIA discusses NVIDIA’s production-level, end-to-end infrastructure and workflows to develop AI for self-driving cars.
He explores the platform that supports continuous data ingest from multiple cars (each producing TBs of data per hour) and enables autonomous AI designers to iterate training new neural network designs across thousands of GPU systems and validate their behavior over multi PB-scale data sets. The obstacles faced by self-driving cars aren’t limited to the world of autonomous driving. Clément shares how the lessons from building this infrastructure for training and inference at scale are applicable to others deploying AI-based services.