Industry-Grade Deep Learning
Today’s AI is arming humans with superpowers — from aiding doctors to make better diagnoses to helping the public move around safely. Entire industries are being redefined, and new ones are emerging as well. AI, today mostly powered by Deep Learning, is a powerful tool, but one that is not trivial to master and integrate into existing industry workflows. NVIDIA has enabled the current AI boom by providing critical compute power necessary for scientists to solve a wide range of AI problems, specifically challenging perception problems. Today NVIDIA is investing in higher-level abstractions to solve even more complex innovations, like self-driving cars, and help other industries leverage Deep Learning. In this talk, you’ll learn how Deep Learning has evolved over the past 10 years, how we enabled this field, and continue to do so; what we are doing to get to fully autonomous cars; and how we are building platforms to enable anyone to create value with Deep Learning. I will also talk about research at NVIDIA and how we operate a fast-moving R&D team to rapidly transfer research into products.
Clement Farabet is VP of AI Infrastructure at NVIDIA. His team is responsible for building NVIDIA’s next-generation AI platform, to enable a broad range of applications, from autonomous cars to healthcare. Clement received a PhD from Université Paris-Est in 2013, while at NYU, co-advised by Laurent Najman and Yann LeCun. His thesis focused on real-time image understanding, introducing multi-scale convolutional neural networks and a custom hardware arch for deep learning. He cofounded Madbits, a startup focused on web-scale image understanding, sold to Twitter in 2014. He cofounded Twitter Cortex, a team focused on building Twitter’s deep learning platform for recommendations/search/spam/nsfw/ads.