Update: Nvidia has posted indexed video highlights of the Jen-Hsun Huang keynote. Check out full coverage of the Jen-Hsun Huang keynote over at TechEnablement.
Other GTC Keynotes on insideHPC:
- Keynote by Jeff Dean, Senior Fellow at Google. Over the past few years, Google has built large-scale computer systems for training neural networks, and then applied these systems to a wide variety of problems that have traditionally been very difficult for computers. We have made significant improvements in the state-of-the-art in many of these areas, and our software systems and algorithms have been used by dozens of different groups at Google to train state-of-the-art models for speech recognition, image recognition, various visual detection tasks, language modeling, language translation, and many other tasks. In this talk, Dean will highlight some of the distributed systems and algorithms that we use in order to train large models quickly. I’ll then discuss ways in which we have applied this work to a variety of problems in Google’s products, usually in close collaboration with other teams. This talk will also describe joint work with many people at Google.
- Keynote by Andrew NG, Chief Scientist at Baidu. Deep Learning has transformed many important tasks, including speech and image recognition. Deep Learning systems scale well by absorbing huge amounts of data to create accurate models. The computational resources afforded by GPUs have been instrumental to this scaling. However, as Deep Learning has become more mainstream, it has generated some hype, and has been linked to everything from world peace to evil killer robots. In this talk, Dr. Ng will help separate hype from reality, and discuss potential ways that Deep Learning technologies can benefit society in the short and long term.