The Power of Deep Learning with Bryan Catanzaro from NVIDIA

We are joined by Bryan Catanzaro, Vice President of Applied Deep Learning Research at NVIDIA. In his early career he built some of the original deep learning libraries and worked at Baidu in the specific field of deep speech. In 2016 he returned to NVIDIA and has been there since, exploring the ever-evolving field of deep learning at one of the industry leaders. We discuss conversational AI and the newest advancements in the field, Bryan’s thoughts on NVIDIA’s competition and what the market looks like currently. Bryan also weighs in on how far we are from a more general form of artificial intelligence and how far we can get by just scaling today’s technologies. We also cover autonomous driving, related software, hardware and frameworks and the impact of cloud computing on the field. For this informative chat be sure to listen in to the For Your Innovation podcast! Key Points From This Episode: An overview of how deep learning has changed over the last two decades. NVIDIA’s realizations around deep learning and the impact it would make. The deep learning team at NVIDIA and how it fits into the company as a whole. Connections to other companies and internal work within the NVIDIA sphere. Exciting projects at the company; conversational AI and graphics rendering! The data bottleneck and the hurdles to teaching machines to properly understand language. Scaling in large transformer networks, training and inference models for learning. Single and multi-node problems; creating solutions for different types of customers. The software and frameworks in the market right now and who is leading the race. The hardware side of machine learning and why Bryan emphasizes universal compatibility. NVIDIA’s autonomous driving efforts and what they are ultimately aiming for. How close are we to some form of general artificial intelligence?   Tweetables:  “NVIDIA is also as you might remember, a very densely connected flat organization. Teams work together across org chart boundaries every day.” — @ctnzr “We are not just training models of the past we are inventing models of the future.” — @ctnzr