Autonomous automobiles are probably the most advanced AI challenges of our time. For AVs to function safely in the actual world, the networks operating inside them should come collectively as an intricate symphony, which requires intensive coaching, testing and validation on huge quantities of knowledge.
Clément Farabet, vice chairman of AI infrastructure at NVIDIA, is a proverbial maestro behind the AV improvement orchestra. He’s making use of almost 15 years of expertise in deep studying — together with constructing Twitter’s AI machine — to show neural networks the best way to understand and react to the world round them.
Farabet sat down with NVIDIA’s Katie Burke Washabaugh on the most recent episode of the AI Podcast to debate how the early days of deep studying led to at this time’s flourishing AV {industry}, and the way he’s approaching deep neural community improvement.
Tapping into the NVIDIA SaturnV supercomputer, Farabet is designing a extremely scalable information manufacturing facility to ship clever transportation within the close to time period, whereas looking forward to the subsequent frontiers in AI.
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