This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
This Website Uses Cookies By closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
Danny Shapiro, Senior Director of Automotive, Nvidia, believes that simulation is a vital part of the development and deployment process, enabling robust testing and validation of AV systems.
Autonomous vehicles (AVs) hold tremendous promise to make our roads safer. Testing and training these self-driving systems, however, demands a sizable test fleet driving potentially billions of miles.
Nvidia Jetson AGX Xavier, the newest product of the series, features a small form factor and has more than 20x the performance and 10x the energy efficiency of its predecessor.
In the Wild, Wild West of the current AV (autonomous vehicle) industry, many claims are made by the industry’s OEMs, suppliers, and technology providers regarding vehicle and system performance capabilities.
Said to be the most complex system on a chip ever created, it represents the work of more than 2000 Nvidia engineers over a four-year period and an investment of $2 billion.
Developed jointly with Nvidia, ZF’s production-ready ProAI control box enables vehicles to better understand their environment by using deep learning to process sensor and camera data, with the first application for Baidu.