SAN FRANCISCO / LONDON (IT BOLTWISE) – Uber plans to establish one of the world’s largest networks of autonomous vehicles, powered by NVIDIA’s AI architecture. This collaboration aims to accelerate the next generation of robotaxi and autonomous delivery fleets and expand globally.
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Uber has announced a significant partnership with NVIDIA to accelerate the development and deployment of autonomous vehicle fleets. This collaboration is powered by NVIDIA’s advanced AI architecture, enabling Uber to significantly expand its global autonomous fleets. Stellantis will be one of the first OEMs to deliver at least 5,000 Level 4 vehicles equipped with NVIDIA DRIVE AGX Hyperion to support robotaxis operations in the US and internationally.
The vehicles are developed in collaboration with NVIDIA and other partners in the Uber ecosystem and leverage the latest upgrades to the NVIDIA DRIVE AGX Hyperion platform. This platform offers a modular computing and sensor architecture designed for fully autonomous driving. Uber will oversee end-to-end fleet operations, including remote assistance, charging, cleaning, maintenance and customer support.
The partnership between Uber and NVIDIA marks an important step in the development of autonomous mobility to make cities safer, cleaner and more efficient. According to Uber CEO Dara Khosrowshahi, autonomous mobility will transform cities for the better, and working with NVIDIA is a critical step in making that vision a reality. Antonio Filosa, CEO of Stellantis, emphasizes that autonomous mobility opens up new, more affordable transportation options for customers.
Another aspect of this collaboration is the development of a Robotaxi data factory powered by the NVIDIA Cosmos physical AI platform. Uber will collect over 3 million hours of specific ride data to support training and validation of L4 models. NVIDIA will provide GPUs, Cosmos and related tools for data curation, simulation and continuous improvement of the autonomy stacks. These capabilities form a powerful data engine aimed at shortening the path from pilot projects to profitable autonomy deployment.
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