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Summary form only given. In this talk we discuss the latest developments in the art and science of autonomous driving. Deep Learning Networks have become indispensable in design and implementation of such systems. We will present the latest software and hardware tools for development and deployment of ever more computationally demanding DLNs used in self-driving cars. From DGX-1 supercomputer for training DLNs, to Drive PX 2, a scalable AI car computer platform for inference, and looking into the future, to the recently announced Xavier, an AI supercomputer on a chip for future autonomous vehicles, tools are now available for every part of a DLN lifecycle. We illustrate how the tools are being used already by showing some of the most recent results of Nvidia's own, end-to-end DLN for autonomous driving.
Branislav Kisačanin (Mon,) studied this question.