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AI-driven platform for life sciences research and discovery

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Build, customize, and deploy multimodal generative AI

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Integrate advanced simulation and AI into complex 3D workflows

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Harness the power of large-scale, physically-based OpenUSD simulation

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Innovative solutions to take on your robotics, edge, and vision AI challenges

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AI-defined vehicles are transforming the future of mobility

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Transform workflows with immersive, scalable interactions in virtual environments

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Explore high-fidelity sensor simulation for safe autonomous vehicle development

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State-of-the-art system for AV safety, from the cloud to the car

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  • AI Trust Center
    Autonomous Vehicle Safety

    Autonomous Vehicle Safety

    Ensure vehicle safety across the full AV stack with NVIDIA Halos.

    Read the Safety Report
    • Overview
    • Highlights
    • Technology
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    • Use Cases
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    • Overview
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    Overview

    Autonomous Vehicle Safety, From the Cloud to the Car

    NVIDIA Halos is a full-stack, comprehensive safety system that unifies vehicle architecture, AI models, chips, software, tools, and services to ensure the safe development and deployment of autonomous vehicles (AVs) from cloud to car.

    The system covers the full development lifecycle with design-time, deployment-time, and validation-time guardrails that collectively build safety and explainability into AI-based AV stacks. These guardrails are implemented using three powerful computers—NVIDIA DGX™ for AI training, NVIDIA Omniverse™ and Cosmos™ for simulation, and NVIDIA AGX™ for deployment.

    NVIDIA Halos complements existing industry-standard safety practices, while introducing unique elements for autonomous vehicles. This ensures regulatory compliance and advances safe and reliable AV stacks, together with NVIDIA’s Halos AI Systems Inspection Lab.

    Halos is also extending its comprehensive safety framework beyond AVs to robotics, further enhancing the reliability and safety of intelligent systems.

    NVIDIA Releases New AI Models and Developer Tools to Advance Autonomous Vehicle Ecosystem

    To accelerate the development of next-generation AV architectures, NVIDIA released NVIDIA Cosmos Predict-2 — a new world foundation model with improved future world state prediction capabilities for high-quality synthetic data generation — as well as new developers tools.

    Read the Blog

    NVIDIA Launches Halos, a Full-Stack, Comprehensive Safety System for Autonomous Vehicles

    NVIDIA unifies vehicle architecture to AI models; chips, software, and tools to services for safely developing AVs from cloud to car.

    Read the Blog

    Highlights

    Autonomous Vehicle Safety Leadership

    NVIDIA Halos is the result of continuous investment in autonomous vehicle safety—from research to engineering to active engagement with international safety standards—validated by independent third-party assessments.

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    15,000+

    Engineering years invested in vehicle safety to date

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    21 Billion+

    Safety transistors safety assessed

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    7,000,000

    Lines of safety-assessed code

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    2,000,000

    Daily end-to-end integration tests for validation

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    22,000+

    Platform safety monitors

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    20,000+

    Hours of safety test data

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    1,000+

    Patents filed

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    240+

    Research papers published on AV safety

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    30+

    Certificates and assessment reports issued

    Technology

    Engineered for Safety, Designed for Trust

    As AV companies transition to AI-based, end-to-end architectures, NVIDIA Halos provides the critical safety foundation to ensure system-level reliability and iterative improvement for automated driving systems. This includes integration of third party-assessed hardware, software, and processes with a diverse algorithmic architecture and validation pipelines.

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    NVIDIA DGX

    Design-time safety guardrails for built-in hardware/software safety and trustworthy development processes.

    Learn More
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    NVIDIA Omniverse With Cosmos

    Validation-time guardrails for data generation, simulation, evaluation, and lifelong safety assurances.

    Learn More
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    NVIDIA DRIVE AGX™

    Deployment-time guardrails for run-time monitoring and real-time introspection.

    Learn More

    Benefits

    A Comprehensive System for Autonomous Vehicle Safety

    NVIDIA Halos helps to ensure AI-driven AV systems are safe and secure. Partners can tap into NVIDIA’s investments in AI safety to accelerate development and enhance AV reliability. NVIDIA Halos is also open to developers, enabling adoption or customization of safety elements to drive the shared mission to create safe and reliable autonomous vehicle technology.

    Design-time, deployment-time, and validation-time guardrails collectively build safety and explainability into several layers of technologies spanning platform safety, AI algorithmic safety, and ecosystem safety. 

    At the top of the NVIDIA Halos elements sits the NVIDIA Halos AI Systems Inspection Lab, which allows customers and ecosystem partners to verify the safe integration of their products with NVIDIA Halos elements. The lab is the first worldwide program to be accredited by ANAB for AI functional safety.

    Sensors of an Autonomous Vehicle

    Use Cases

    A Full-Stack Comprehensive Safety System

    NVIDIA Halos integrates foundational models and a diverse algorithmic stack, combining classical and AI-based, end-to-end models to drive system-level safety in the shift toward AI-driven AV architectures.

    Explore NVIDIA Halos Product Brief
    1. Platform Safety

    2. Algorithmic Safety

    3. Ecosystem Safety

    4. Halos AI Systems Inspection Lab

    Platform Safety

    The robust foundation for autonomous driving systems includes: 

    • A System-on-a-Chip (SoC) that’s designed for safety, with hundreds of built-in safety mechanisms.
    • NVIDIA DriveOS™, a safety-certified, ASIL-D operating system that extends across the CPU, ISP, GPU, I/O, and memory.
    • A safety-assessed base platform that delivers the foundational safe computer needed to enable safe systems for all types of applications
    • NVIDIA DRIVE AGX Hyperion™, a diverse hardware platform that connects the SoC, OS, and sensors in a vehicle architecture. This enables a vehicle to safely execute contingency plans if needed.
    NVIDIA DRIVE OS platform safety for autonomous vehicles

    Algorithmic Safety

    Algorithmic AI safety spans:

    • A diverse AV stack that combines a modular stack and end-to-end AI models for algorithmic AI safety.
    • Training, simulation, and validation environments that use NVIDIA Omniverse.
    • A separate safety dataset that ensures AV performance is tested against diverse, unbiased data.
    Autonomous vehicle safety testing using AI models

    Ecosystem Safety

    Building a safer AV ecosystem includes:

    • Continual improvements through a safety data flywheel, which continually learns from the road how to expand the set of operational design domains for safe deployment.
    • Seamless integration of physically based and diverse sensor simulation into existing workflows to safely train, test, and validate AVs with the NVIDIA Omniverse Blueprint for AV Simulation.
    • Open-source data, such as the NVIDIA Physical AI Dataset, to enable critical safety research throughout the industry.
    • A growing list of partners using the NVIDIA Halos system, listed here.
    NVIDIA DRIVE OS platform safety for autonomous vehicles

    Halos AI Systems Inspection Lab

    NVIDIA is the first company to establish an ANSI National Accreditation Board (ANAB)-accredited Halos AI Systems Inspection Lab, integrating functional safety, cybersecurity, AI, and regulations into a unified safety framework. The lab helps to ensure that partner system integrations meet rigorous safety and cybersecurity standards through impartial assessments. 

    By providing inspection reports and streamlining technical validations, the lab accelerates compliance with global safety standards for AV safety and cybersecurity. This empowers the automotive ecosystem to deploy safer, more reliable AI-driven technologies while advancing compliance with international standards. 

    The NVIDIA Halos AI Systems Inspection Lab has now expanded from AV to robotics.

    Learn More About the AI Systems Inspection Lab
    NVIDIA DRIVE AI Systems Inspection Lab

    “Joining NVIDIA's Halos AI Systems Inspection Lab marks our commitment to advancing driving safety. By combining Bosch's comprehensive in-house ADAS sensor expertise with NVIDIA's AI validation framework, we're setting new standards for safe and reliable ADAS solutions.”

    — Dennis Raabe, Senior Vice President ADAS Components, Bosch

    “NVIDIA’s latest evaluation with ANAB verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that developers of autonomous machines—from automotive to robotics—can meet the highest benchmarks for functional safety.”

    — R. Douglas Leonard Jr., Executive Director, ANAB

    “Aligned with our shared mission to enhance safety, efficiency and productivity, we congratulate NVIDIA on the launch of its Halos AI Systems Inspection Lab. The Lab's reports will provide valuable insights to support our certification efforts.”

    — Thomas Steffens, Head of Certification Body Functional Safety and Cybersecurity, TUV Rheinland

    “We are pleased to hear of NVIDIA's commitment to advancing autonomous vehicle safety and welcome NVIDIA's Halos Inspection Lab efforts for structured and thorough development of AI for safety-relevant applications.”

    — Dominik Strixner, Global Lead Functional Safety Auto and Mobility, TÜV Rheinland (automotive)

    “UL Solutions is a global leader in applied safety science. We are pleased to announce our intent to collaborate with the NVIDIA Halos AI Systems Inspection Lab to harmonize testing activities and reports for companies who are pursuing safety certification with us.”

    — Alex Dadakis, EVP, Chief Business Ops and Innovation, UL Solutions

    “We are committed to fostering digital trust and delivering rigorous AI assurance at scale. By recognizing the inspection reports of the NVIDIA Halos AI Systems Inspection Lab, we’re supporting the industry’s move toward more transparent, reliable, and secure AI — while enabling developers to bring innovative systems to market faster and more safely.”

    — Vincent Sabot, CEO, CertX

    Certification

    Assessed by Experts

    Independent third-party safety and cybersecurity assessments of NVIDIA Halos elements demonstrate NVIDIA’s ongoing commitment to AV safety.

    ANSI National Accreditation Board logo

    ANSI National Accreditation Board

    ANAB accredited the NVIDIA Halos AI Systems Inspection Lab as an ISO/IEC 17020 Inspection Body. NVIDIA is the first company accredited by ANAB for an inspection plan that combines cybersecurity, AI, and functional safety.

    TÜV SÜD logo

    TÜV SÜD

    TÜV SÜD certified the NVIDIA Automotive Product Lifecycle (PLC) software process and NVIDIA DriveOS 6.0 to ISO 26262 standard for Automotive Safety Integrity Level (ASIL) D. NVIDIA also received ISO/SAE 21434 Cybersecurity Process certification for its automotive system-on-a-chip, platform, and software engineering processes.

     TÜV Rheinland logo

    TÜV Rheinland

    TÜV Rheinland performed an independent United Nations Economic Commission for Europe safety assessment of NVIDIA DRIVE AV related to safety requirements for complex electronic systems.

    Research

    NVIDIA Research for Autonomous Vehicles

    Our research and development have published 240+ research papers on autonomous vehicle safety.

    Recent Advances and Trends on Automotive Safety

    Catch up on recent automotive safety advances focusing on Automated Driving Systems (ADS) and the interplay between functional safety, SOTIF, and cybersecurity.

    Read the Paper

    NVIDIA Cosmos World Foundation Model Platform for Physical AI

    Physical AI needs to be trained digitally first. This requires a digital twin of itself, the policy model, and a digital twin of the world—the world model. Cosmos helps developers build customized world models for physical AI setups.

    Learn More About Cosmos

    Promptable Closed-Loop Traffic Simulation

    Aside from simulating realistic traffic agent interactions in a closed loop, traffic models should also generate agent motions that satisfy a complex set of user-specified prompts.

    Visit GitHub

    Surprise Potential as a Measure of Interactivity in Driving Scenarios

    Explore a novel metric that identifies interactive scenarios by measuring an AV's surprise potential on others.

    Read the Paper

    Enhancing Autonomous Driving Safety with Collision Scenario Integration

    HydraSafe is a framework that addresses the challenge of ensuring autonomous vehicle safety in hazardous scenarios by improving data availability and planner robustness.

    Visit the Project Page

    System-Level Safety Monitoring and Replanning in Autonomous Vehicles

    The safety-critical nature of autonomous vehicle (AV) operation necessitates the development of task-relevant algorithms that can reason about safety at the system level, not just the component level.

    Read the Paper

    For a list of additional AV Research papers, click here.

    Partners

    Partners Using NVIDIA Halos System

    Leading robotaxi companies, OEMs, industry safety pioneers, mapping and simulation companies, and software and sensor providers worldwide are using the system to deliver autonomous vehicle safety at all levels of automation.

    View All NVIDIA DRIVE Partner Ecosystem Members
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    Cars

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    Suppliers

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    Simulation

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    Sensors

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    Software

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    Mapping

    Resources

    The Latest in NVIDIA Halos Resources

    1. News

    2. Sessions

    (8 sessions)

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    54:20
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    AI Safety: From Autonomous Vehicles to Broader …
    NVIDIA Halos 簡介:從自動駕駛汽車到更廣泛的物理 AI 安全 Introduction to …
    Introduction to NVIDIA Halos – Strategy for AV Safety
    Guardrails for NVIDIA Halos Across the Product Life Cycle
    Safety Regulation and Standardization in the Era …
    Navigating the High-Stakes Safety Challenges of …
    Safety in the Age of AI-Based Autonomous Vehicles
    Improving Safety with Software-Defined Vehicles