Iván Hernández Dalas: NVIDIA partners with Uber to deploy AVs starting in 2027

An render of a vehicle with a phone next to it.

NVIDIA DRIVE AGX Hyperion 10 is a reference computer and sensor architecture that enables automakers to build level 4-ready, software-defined vehicles on a validated, scalable foundation. | Source: NVIDIA

NVIDIA today announced it is partnering with Uber to scale a level 4-ready mobility network. The network will be built on:

  • Uber’s robotaxi and autonomous delivery fleets
  • The new NVIDIA DRIVE AGX Hyperion 10 autonomous vehicle (AV) development platform
  • NVIDIA DRIVE AV software, purpose-built for L4 autonomy

“Robotaxis mark the beginning of a global transformation in mobility — making transportation safer, cleaner, and more efficient,” said Jensen Huang, founder and CEO, NVIDIA. “Together with Uber, we’re creating a framework for the entire industry to deploy autonomous fleets at scale, powered by NVIDIA AI infrastructure. What was once science fiction is fast becoming an everyday reality.”

NVIDIA said it can support Uber in scaling its global autonomous fleet to 100,000 vehicles over time, starting in 2027. These vehicles will be developed in collaboration with NVIDIA and other Uber ecosystem partners, using NVIDIA DRIVE.

NVIDIA and Uber are also working together to develop a data factory accelerated by the Cosmos world foundation model (WFM) development platform. This data factory will help it curate and process data needed for autonomous vehicle development.

“NVIDIA is the backbone of the AI era, and is now fully harnessing that innovation to unleash L4 autonomy at enormous scale, while making it easier for NVIDIA-empowered AVs to be deployed on Uber,” said Dara Khosrowshahi, CEO of Uber. “Autonomous mobility will transform our cities for the better, and we’re thrilled to partner with NVIDIA to help make that vision a reality.”

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NVIDIA products lay the foundation for an AV network

NVIDIA DRIVE AGX Hyperion 10 is a reference production computer and sensor set architecture that makes any vehicle L4-ready, the company said. It enables automakers to build cars, trucks, and vans equipped with validated hardware and sensors. These vehicles can host any compatible autonomous-driving software, providing a unified foundation for safe, scalable, and software-defined mobility.

The NVIDIA DRIVE AGX Hyperion 10 production platform features:

  • The NVIDIA DRIVE AGX Thor system-on-a-chip
  • The safety-certified NVIDIA DriveOS operating system
  • A fully qualified multimodal sensor suite including 14 high-definition cameras
  • Nine radars, one lidar, and 12 ultrasonics
  • A qualified board design

DRIVE AGX Hyperion 10 is modular and customizable. This allows manufacturers and AV developers to tailor it to their unique requirements. By offering a prequalified sensor suite architecture, NVIDIA said the platform also accelerates development and lowers costs.

The developer aims to give customers a running start with access to NVIDIA’s rigorous development expertise and investments in automotive engineering and safety.

At the core of DRIVE AGX Hyperion 10 are two performance-packed DRIVE AGX Thor in-vehicle platforms based on NVIDIA Blackwell architecture. Each delivers more than 2,000 FP4 teraflops (1,000 TOPS of INT8) of real-time compute. DRIVE AGX Thor fuses diverse, 360-degree sensor inputs and is optimized for transformer, vision language action (VLA) models, and generative AI workloads.

This, NVIDIA said, enables safe, level 4 autonomous driving backed by industry-leading safety certifications and cybersecurity standards.

In addition, DRIVE AGX’s scalability and compatibility with existing AV software let companies integrate and deploy future upgrades from the platform. NVIDIA said this works across robotaxi and autonomous mobility fleets via over-the-air updates.

Generative AI and foundation models enable AVs to solve complex problems, NVIDIA said

NVIDIA’s autonomous driving approach taps into foundation AI models, large language models, and generative AI. Its AI is trained on trillions of real and synthetic driving miles. These advanced models allow self-driving systems to solve highly complex urban driving situations with reasoning and adaptability, the company claimed.

New reasoning VLA models combine visual understanding, natural language reasoning, and action generation. By running reasoning VLAs in the vehicle, the AV can interpret nuanced and unpredictable real-world conditions in real time. These conditions can include sudden changes in traffic flow, unstructured intersections, and unpredictable human behavior.

AV toolchain developer Foretellix is collaborating with NVIDIA to integrate its Foretify Physical AI toolchain with NVIDIA DRIVE for testing and validating these models. To enable the industry to develop and evaluate these large models for autonomous driving, NVIDIA is also releasing its largest multimodal AV dataset.

The dataset is made up of 1,700 hours of real-world camera, radar, and lidar data across 25 countries. NVIDIA designed it to bolster development, post-training, and validation of foundation models for autonomous driving.

NVIDIA grows partnerships with AV developers

Two vehicles developed by Stellantis for autonomy.

Stellantis is working with NVIDIA, Uber, and Foxconn to explore the joint development and future deployment of robotaxi services. | Source: Stellantis

Global automakers, robotaxi companies, and tier 1 suppliers are already working with NVIDIA and Uber to launch level 4 fleets with NVIDIA AI behind the wheel.

Stellantis is developing AV-Ready Platforms, specifically optimized to support level 4 capabilities and meet robotaxi requirements. These platforms will integrate NVIDIA’s full-stack AI technology, further expanding connectivity with Uber’s global mobility ecosystem. Stellantis is also collaborating with Foxconn on hardware and systems integration.

Lucid is advancing level 4 autonomous capabilities for its next-generation passenger vehicles. It’s doing this by using full-stack NVIDIA AV software on the DRIVE Hyperion platform for its upcoming U.S. models. Additionally, Lucid aims to deploy a unified AI factory to build smart factories with NVIDIA Omniverse and NVIDIA AI Enterprise software libraries.

Mercedes-Benz is testing future collaboration with industry-leading partners powered by its proprietary operation system MB.OS and DRIVE AGX Hyperion. Building on its legacy of innovation, the new S-Class offers an exceptional chauffeured Level 4 experience combining luxury, safety, and cutting-edge autonomy.

Meanwhile, NVIDIA and Uber will continue to support and accelerate shared partners across the worldwide level 4 ecosystem, developing their software stacks on the NVIDIA DRIVE level 4 platform. These include Avride, May Mobility, Momenta, Nuro, Pony.ai, Wayve, and WeRide.

In trucking, Aurora, Volvo Autonomous Solutions, and Waabi are developing level 4 autonomous trucks powered by the NVIDIA DRIVE platform. Their next-generation systems, built on NVIDIA DRIVE AGX Thor, will accelerate Volvo’s upcoming L4 fleet, extending the reach of end-to-end NVIDIA AI infrastructure from passenger mobility to long-haul freight.

Additionally, International Motors LLC and PlusAI Inc. are working together to develop factory-built autonomous trucks powered by NVIDIA DRIVE AGX Thor.

A self-driving truck. International, PlusAI, and NVIDIA are teaming to produce factory-built autonomous trucks.

A self-driving truck. International, PlusAI, and NVIDIA are teaming up to produce factory-built autonomous trucks.

New Halos system to ensure safety while scaling

The NVIDIA Halos system delivers state-of-the-art safety guardrails from cloud to car. NVIDIA said this establishes a holistic framework to enable safe, scalable autonomous mobility.

The Halos AI Systems Inspection Lab, dedicated to AI safety and cybersecurity across automotive and robotics, performs independent evaluations and oversees the new Halos Certified Program. It can help ensure products and systems meet rigorous criteria for trusted physical AI deployments.

Companies such as AUMOVIO, Bosch, Nuro, and Wayve are among the inaugural members of the NVIDIA Halos AI System Inspection Lab — the industry’s first to be accredited by the ANSI Accreditation Board. This lab aims to accelerate the safe, large-scale deployment of level 4 automated driving.

The post NVIDIA partners with Uber to deploy AVs starting in 2027 appeared first on The Robot Report.



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