Nvidia · AI Safety · NVIDIA Blog
Why Deploying Physical AI at Scale Demands Safety at Every Layer
Compiled by KHAO Editorial — aggregated from 1 source. See llms.txt for citation guidance.
★ Tier-1 Source
Physical AI is moving rapidly from research to large-scale deployment.
Key facts
- For AVs, TÜV SÜD certified NVIDIA’s Automotive Product Lifecycle software process and DriveOS 6.0 to ISO 26262 ASIL D, as well as NVIDIA’s automotive engineering processes to ISO/SAE 21434
- By 2035, ABI Research projects an installed base of 49 million level 3-5 autonomous vehicles (AVs), while Omdia estimates that roughly 60 million industrial robots will be deployed between 2026
- For robotics, TÜV Rheinland is inspecting NVIDIA IGX Thor, Halos OS and Holoscan Sensor Bridge for functional-safety certification readiness, building on TÜV SÜD’s inspection of the Thor SoC
- Across physical AI, ANAB has accredited the NVIDIA Halos AI Systems Inspection Lab as an ISO/IEC 17020 inspection body
Summary
Physical AI safety means proving that AI-driven machines, AVs, humanoid robots, industrial robots and more, behave safely when their decisions turn into physical action. After years of testing and benchmarking, AVs continue to expand commercially. Robotics is approaching a similar inflection point as autonomous machines move into factories, warehouses and other environments shared with people. Across physical AI, manufacturers, regulators, insurers and workplace safety teams need evidence that hardware, software, AI behavior and operating environments can work together safely without human intervention.