Autonomous vehicles are one of the most complex AI challenges of our time. For AVs to operate safely in the real world, the networks running within them must come together as an intricate symphony, which requires intensive training, testing and validation on massive amounts of data.
Clément Farabet, vice president of AI infrastructure at NVIDIA, is a proverbial maestro behind the AV development orchestra. He’s applying nearly 15 years of experience in deep learning — including building Twitter’s AI machine — to teach neural networks how to perceive and react to the world around them.
Farabet sat down with NVIDIA’s Katie Burke Washabaugh on the latest episode of the AI Podcast to discuss how the early days of deep learning led to today’s flourishing AV industry, and how he’s approaching deep neural network development.
Tapping into the NVIDIA SaturnV supercomputer, Farabet is designing a highly scalable data factory to deliver intelligent transportation in the near term, while looking ahead to the next frontiers in AI.
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