NVIDIA and Aurora today announced that they are working together to create a new Level 4 and Level 5 self-driving hardwa...
GE Healthcare and NVIDIA today announced they will deepen their 10-year partnership to bring the most sophisticated artificial intelligence (AI) to GE Healthcare’s 500...
The partnership will enable the production of AI computer systems that scale from automated Level 2 features through full Level 5 self-driving capabilities, where the vehicle has no steering wheel or pedals.
Dedicated engineering teams from each company will work together to develop self-driving solutions based on the NVIDIA DRIVE platform — which includes NVIDIA DRIVE Xavier, the world’s highest performance system-on-a-chip, as well as the NVIDIA DRIVE OS (operating system) and DRIVE AV (autonomous vehicle) software stacks.
The solutions will utilize Continental’s experience in system and software engineering for ASIL-D rated safety — the highest rating level — and integrate a range of Continental sensor technologies, including radar, camera and high-resolution 3D lidar.
“The vehicle of the future will be a sensing, planning and acting computer on wheels. The complexity of autonomous driving requires nothing less than the full computational horsepower of an AI supercomputer,” said Dr. Elmar Degenhart, CEO of Continental. “Together with the performance and flexibility of NVIDIA’s AI self-driving solution, from the cloud to the car we will achieve new levels of safety, comfort and personalization for future vehicles.”
“We now have all the key elements in place to take AI self-driving cars from development to mass production,” said Jensen Huang, founder and CEO of NVIDIA. “Our newly arrived DRIVE Xavier processor, extensive NVIDIA DRIVE software, and cloud-to-car approach for testing, validation and functional safety, combined with Continental’s expertise and global reach, will bring autonomous cars to the world.”
As the brain of the Continental system, NVIDIA DRIVE Xavier can deliver 30 TOPS (trillion operations per second) for deep learning, while consuming only 30 watts of energy. This unprecedented level of performance is necessary to handle the massive amount of data processing that self-driving vehicles must perform. These include running deep neural networks to sense surroundings, understand the environment, localize the vehicle on an HD map, predict the behavior and position of other objects, compute vehicle dynamics, and plan a safe path forward.
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