Physical AI is becoming the foundation of smart cities, facilities and industrial processes across the globe.
NVIDIA is working with companies including Accenture, Avathon, Belden, DeepHow, Milestone Systems and Telit Cinterion to enhance operations across the globe with physical AI-based perception and reasoning.
The continuous loop of simulating, training and deploying physical AI offers sophisticated industrial automation capabilities, making cities and infrastructure safer, smarter and more efficient.
For example, physical AI applications can automate potentially dangerous tasks for workers, such as working with heavy machinery. Physical AI can also improve transportation services and public safety, detect defective products in factories and more.
The need for this is greater than ever. The numbers tell the story:
Infrastructure that can perceive, reason and act relies on video sensors and the latest vision AI capabilities. Using the NVIDIA Metropolis platform — which simplifies the development, deployment and scaling of video analytics AI agents and services from the edge to the cloud — developers can build visual perception into their facilities faster to enhance productivity and improve safety across environments.
Below are five leading companies advancing physical AI — and five key NVIDIA Metropolis updates, announced today at the SIGGRAPH computer graphics conference, making such advancements possible.
Five Companies Advancing Physical AI
Global professional services company Accenture is collaborating with Belden, a leading provider of complete connection solutions, to enhance worker safety by creating smart virtual fences that factories can place around large robots to prevent accidents with human operators.
The smart virtual fence is a physical AI safety system that uses an OpenUSD-based digital twin and physics-grounded simulation to model complex industrial environments. Using computer vision-based mapping and 3D spatial intelligence, the system is adaptive to increased variability in the dynamic human-robot interactions that occur in a modern shopfloor environment.
Accenture taps into the NVIDIA Omniverse platform and Metropolis to build and simulate these smart fences. With Omniverse, Accenture created a digital twin of a robot arm and workers moving in a space. And with Metropolis, the company trained its AI models and deployed them at the edge with video ingestion and the NVIDIA DeepStream software development kit (SDK)’s real-time inference capabilities.
Avathon, an industrial automation platform provider, uses the NVIDIA Blueprint for video search and summarization (VSS), part of NVIDIA Metropolis, to provide manufacturing and energy facilities with real-time insights that improve operational efficiency and worker safety.
Reliance British Petroleum Mobility Limited, a leader in India’s fuel and mobility sector, used the Avathon video intelligence product during the construction of its gas stations to achieve higher standards of safety compliance, a reduction in safety noncompliance incidents and higher productivity by saving thousands of work hours.
DeepHow has developed a “Smart Know-How Companion” for employees in manufacturing and other industries. The companion uses the Metropolis VSS blueprint to transform key workflows into bite-sized, multilingual videos and digital instructions, improving onboarding, safety and floor operator efficiency.
Facing upskilling needs and retiring skilled workers, beverage company Anheuser-Busch InBev turned to the DeepHow platform to convert standard operating procedures into easy-to-understand visual guides. This has slashed onboarding time by 80%, boosted training consistency and improved long-term knowledge retention for employees.
Milestone Systems, which offers one of the world’s largest platforms for managing IP video sensor data in complex industrial and city deployments, is creating the world’s largest real-world computer vision data library through its platform, Project Hafnia. Among its capabilities, the platform provides physical AI developers with access to customized vision language models (VLMs).
Tapping NVIDIA NeMo Curator, Milestone Systems built a VLM fine-tuned for intelligent transportation systems for use within the VSS blueprint to help develop AI agents that better manage city roadways. Milestone Systems is also looking to use the new open, customizable NVIDIA Cosmos Reason VLM for physical AI.
Internet-of-things company Telit Cinterion has integrated NVIDIA TAO Toolkit 6 into its AI-powered visual inspection platform, which uses vision foundation models like FoundationPose, alongside other NVIDIA models, to support multimodal AI and deliver high-performance inferencing. TAO brings low-code AI capabilities to the Telit platform, enabling manufacturers to quickly develop and deploy accurate, custom AI models for defect detection and quality control.
Five NVIDIA Metropolis Updates for Physical AI
Key updates to NVIDIA Metropolis are enhancing developers’ capabilities to build physical AI applications more quickly and easily:
Cosmos Reason VLM
The latest version of Cosmos Reason — NVIDIA’s advanced open, customizable, 7-billion-parameter reasoning VLM for physical AI — enables contextual video understanding, temporal event reasoning for Metropolis use cases. Its compact size makes it easy to deploy from edge to cloud and ideal for automating traffic monitoring, public safety, visual inspection and intelligent decision-making.
VSS Blueprint 2.4
VSS 2.4 makes it easy to quickly augment existing vision AI applications with Cosmos Reason and deliver powerful new features to smart infrastructure. An expanded set of application programming interfaces in the blueprint offers users direct more flexibility in choosing specific VSS components and capabilities to augment computer vision pipelines with generative AI.
New Vision Foundation Models
The NVIDIA TAO Toolkit includes a new suite of vision foundation models, along with advanced fine-tuning methods, self-supervised learning and knowledge distillation capabilities, to optimize deployment of physical AI solutions across edge and cloud environments. The NVIDIA DeepStream SDK includes a new Inference Builder to enable seamless deployment of TAO 6 models.
Companies around the world — including Advex AI, Instrumental AI and Spingence — are experimenting with these new models and NVIDIA TAO to build intelligent solutions that optimize industrial operations and drive efficiency.
NVIDIA Isaac Sim Extensions
New extensions in the NVIDIA Isaac Sim reference application help solve common challenges in vision AI development — such as limited labeled data and rare edge-case scenarios. These tools simulate human and robot interactions, generate rich object-detection datasets, and create incident-based scenes and image-caption pairs to train VLMs, accelerating development and improving AI performance in real-world conditions.
Expanded Hardware Support
All of these Metropolis components can now run on NVIDIA RTX PRO 6000 Blackwell GPUs, the NVIDIA DGX Spark desktop supercomputer and the NVIDIA Jetson Thor platform for physical AI and humanoid robotics — so users can develop and deploy from the edge to the cloud.
Cosmos Reason 1 and NVIDIA TAO 6.0 are now available for download. Sign up to be alerted when VSS 2.4, the Cosmos Reason VLM fine-tuning update and NVIDIA DeepStream 8.0 become available.
Watch the NVIDIA Research special address at SIGGRAPH and learn more about how graphics and simulation innovations come together to drive industrial digitalization by joining NVIDIA at the conference, running through Thursday, Aug. 14.
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