Advancements in Hardware and Their Impact on Autonomous Driving Efficiency

This chapter explores the efficiencies achieved in hardware for autonomous driving technology, emphasizing advancements in GPU computing power. It discusses the shift towards data center applications for training large neural networks, contrasting it with the limitations faced by edge computing models.

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