Autonomous Vehicle Data Factory

Train Smarter, Safer Autonomous Driving Models

    Overview

    Physical AI Data Factory for Autonomous Driving

    Developing safe and scalable autonomous vehicles (AVs) requires reasoning models that handle the full complexity of real-world driving. NVIDIA brings together open foundation models for fine-tuning and distillation, scalable data curation and post-training pipelines, and purpose-built compute to train and deploy production-ready driving models from cloud to car.

    NVIDIA Unveils Alpamayo Super and Expands Open AV Ecosystem

    Alpamayo 2 Super is a 32 billion-parameter reasoning VLA model, built for Level 4 robotaxi-ready autonomous vehicles.

    Read the Press Release

    The World Is Building Robotaxis on NVIDIA DRIVE Hyperion

    Global automakers, software partners, and mobility leaders are bringing level 4-ready fleets to market on DRIVE Hyperion—NVIDIA's robotaxi-ready platform.

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    Benefits

    Why Data Factory Matters for Autonomous Vehicles

    The AV Data Factory bridges the gap between a capable prototype and a production-ready AV through models that reason, data that covers the long tail, and continuous iteration on edge cases.

    High-Throughput Data Processing

    AVs generate terabytes of multimodal data from cameras, lidar, radar, and sensors. This data has to be ingested, reconstructed, curated, and labeled at scale before it can be used to train AI models.

    Continuous Improvement

    AV systems need to improve continuously, learning from new data, rare events, and edge cases to refine perception, prediction, and planning.

    Synthetic Data Generation at Scale

    Optimize for high‑throughput synthetic data generation of real‑world drives and scalable scene reconstruction. This enables efficient validation of changes and broad scenario coverage from fleet data.

    Safety-Grade Data Curation

    Ensure the right data, not just more data, is used to train and validate safety-critical systems.

    Technology

    Dataset Preparation and AV Data Factory for Autonomous Vehicles

    NVIDIA DGX™

    • Unified AI training platform combining software, infrastructure, and expertise for enterprise-scale model development
    • High-performance model training and fine-tuning at data center scale
    Learn More About DGX

    NVIDIA Alpamayo

    • Open family of VLA models, simulation frameworks, and datasets for reasoning-based AVs
    • Human-like reasoning to interpret complex driving scenes and explain decisions
    • Causal reasoning label generation for driving clips at scale
    • Available in 10 B and 32 B parameters
    Learn More About Alpamayo

    NVIDIA Cosmos™ for Data Factory

    • Open platform for physical AI with WFMs, video data processing libraries, video evaluation, and post-training frameworks
    • Large-scale dataset processing and metadata generation
    • Petabyte-scale data search and curation
    • Synthetic data generation, video quality scoring and evaluation at scale
    Learn More About Cosmos

    NVIDIA AI Enterprise

    • Essential tools for streamlining the development and deployment of AV software
    • Includes everything from data preparation and training to optimizing for inference and deploying at scale
    • Direct access to NVIDIA AV experts for NVAIE subscribers—the deepest level of technical guidance available to optimize your NVIDIA software deployments
    Learn More NVIDIA AI Enterprise Software Suite

    NVIDIA Automotive NIM

    NVIDIA Inference Microservices Turbocharge the Future of Autonomous Vehicles

    Use advanced AI models to streamline automotive software development and optimize cloud deployment.

    cosmos-nemotron-34b

    Multi-modal vision-language model that understands text/img/video and creates informative responses.

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    cosmos-1.0-diffusion-7b

    Generates physics-aware video world states from text and image prompts for physical AI development.

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    cosmos-1.0-autoregressive-5b

    Generates future frames of a physics-aware world state based on simply an image or short video prompt for physical AI development.

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    View all NVIDIA Automotive NIMS

    Accelerate Your Development

    Unblock data bottlenecks with the NVIDIA Physical AI Dataset, an open-source dataset for autonomous vehicle, robot, and smart space development. The unified collection is composed of validated data used to build NVIDIA physical AI—now available to developers on Hugging Face.

    Start Building

    Customer Stories

    AI Training Across the Automotive Industry

    Hyundai

    Hyundai Motor Group will tap into NVIDIA’s data-center-level computing and infrastructure to efficiently manage the massive data volumes essential for training its advanced AI models and building a robust AV software stack.

    Read the Blog

    Wayve

    Wayve’s partnership with NVIDIA enables seamless deployment of autonomous driving, AI training, and fleet learning. This collaboration accelerates scalable, high-performance adoption of AI-driven automotive systems.

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    Volvo Cars and Zenseact

    Volvo Cars and its software subsidiary, Zenseact, are investing in NVIDIA DGX systems for model training in the cloud. This will help ensure that future fleets are equipped with the most advanced and well-tested AI-powered safety features.

    Read the Blog

    Waabi

    Waabi trusts NVIDIA hardware to run complex simulations and trains its AI models. They'll also use NVIDIA Cosmos for data curation for software development and simulation.

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    NIO

    NIO, a smart electric vehicle manufacturer, is using the NVIDIA DGX AI platform to improve training efficiency and GPU utilization of perception models for autonomous vehicles.

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    Resources

    Breakthroughs in AI, Accelerated Computing, and Simulation

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    Next Steps

    Get in Touch

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