NVIDIA is expanding its Deep Learning Institute initiative in China by partnering with Tencent and Leadtek to provide hands-on AI training to developers...
Whether it’s helping neural networks learn how to learn or getting them to work with pseudo-labeled data, most of the ...
The new system, codenamed Pegasus, extends the NVIDIA DRIVE PX AI computing platform to handle Level 5 driverless vehicles. NVIDIA DRIVE PX Pegasus delivers over 320 trillion operations per second -- more than 10x the performance of its predecessor, NVIDIA DRIVE PX 2.
The computational requirements of robotaxis are enormous -- perceiving the world through high-resolution, 360-degree surround cameras and lidars, localizing the vehicle within centimeter accuracy, tracking vehicles and people around the car, and planning a safe and comfortable path to the destination. All this processing must be done with multiple levels of redundancy to ensure the highest level of safety. The computing demands of driverless vehicles are easily 50 to 100 times more intensive than the most advanced cars today.
"Creating a fully self-driving car is one of society's most important endeavors -- and one of the most challenging to deliver," said Jensen Huang, NVIDIA founder and CEO. "The breakthrough AI computing performance and efficiency of Pegasus is crucial for the industry to realize this vision.
"Driverless cars will enable new ride- and car-sharing services. New types of cars will be invented, resembling offices, living rooms or hotel rooms on wheels. Travelers will simply order up the type of vehicle they want based on their destination and activities planned along the way. The future of society will be reshaped," he said.
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