Uber Aims for 100,000 Nvidia-Powered Autonomous Taxis by 2027, Stellantis to Supply Vehicles

Uber Technologies Inc. is setting an ambitious goal to have a fleet of 100,000 autonomous vehicles by eventually utilizing technology from Nvidia Corp. This initiative aims to reduce the costs associated with offering ride-hailing robotaxis. The expansion is slated to begin in 2027, building on an existing partnership where Uber shares driving data to enhance Nvidia’s artificial intelligence models and chip technology for autonomous vehicle development. Nvidia unveiled its new platform, Nvidia Drive AGX Hyperion 10, at its GTC conference, which equips car manufacturers with necessary hardware and sensors for autonomous driving software. Stellantis NV will be among the first automakers to provide at least 5,000 Nvidia-powered robotaxis for Uber's global operations, starting in the US. Uber will manage all aspects of fleet operations. Stellantis will collaborate with Foxconn on hardware and systems integration, targeting production start in 2028. This move contrasts with Uber's current limited autonomous ride offerings with Alphabet Inc.'s Waymo and China’s WeRide Inc., which involve much smaller fleets. The partnership also involves building a "robotaxi data factory," where Uber will contribute millions of hours of driving data to train and validate driverless models, supported by Nvidia's processors and AI tools. Impact: This collaboration is set to accelerate the development and deployment of autonomous vehicle technology, potentially transforming the ride-sharing industry and automotive manufacturing. It will drive innovation in AI, sensor technology, and fleet management, leading to more efficient and possibly cheaper robotaxi services. The impact on the automotive and tech sectors is high, promising significant disruption and growth opportunities. Rating: 8/10. Difficult terms: Autonomous vehicles: Vehicles capable of driving themselves without human intervention. Robotaxis: Autonomous vehicles used as taxis for ride-hailing services. AI models: Computer programs designed to mimic human intelligence for tasks like learning and decision-making. Chips: Small electronic components that process information, often referred to as semiconductors. Sensors: Devices that detect and respond to physical stimuli like light, heat, or motion, crucial for autonomous driving. Fleet operations: The management of a group of vehicles, including maintenance, charging, cleaning, and dispatch. Data factory: A system designed for collecting, processing, and managing large volumes of data, here specifically for training AI. Synthetic data generation: Creating artificial data that mimics real-world data to train AI models, especially useful when real-world data is scarce or sensitive.