# AI for the Industrial Sector Enabling new levels of automation, efficiency, and precision. **Introduction** ## Powering Industrial Digitalization Leading industrial companies around the world are implementing NVIDIA technologies for large-scale AI initiatives. NVIDIA accelerated computing, AI models, and libraries make it possible to deploy AI at industrial scale, letting you take advantage of vast amounts of sensor and operational data to optimize operations, improve time to insight, maximize yield, and reduce costs. ### NVIDIA Releases Major Collection of Open Source Agent Tools and Skills for Physical AI Physical AI skills and tools help developers turn complex robotics, autonomous vehicle, vision AI, and industrial digital twin workflows into agent-executable tasks. [Read the Press Release](https://nvidianews.nvidia.com/news/nvidia-releases-major-collection-of-open-source-agent-tools-and-skills-for-physical-ai) ### Enterprise Software Leaders Build AI Agents With NVIDIA Design and simulation leaders are building autonomous AI engineers with NVIDIA®  NemoClaw™. [Read the Press Release](https://nvidianews.nvidia.com/news/enterprise-software-leaders-build-ai-agents-with-nvidia) ## Sectors ## Discover How the Industrial Sector Is Using AI #### Manufacturing Reinventing manufacturing—from design to delivery. Designers, engineers, and analysts need to process massive models so they can innovate, iterate, and solve problems—all at the speed of light. Meanwhile, manufacturers need insights from vast amounts of sensor and operational data to optimize operations, improve time to insight, and reduce costs. NVIDIA accelerated computing, AI models, and libraries make it all possible, at scale, from anywhere. [Learn More About AI in Manufacturing](https://www.nvidia.com/en-gb/industries/manufacturing.md) BMW Group #### Semiconductor Enabling advances at sub-nanometer scale. With the move to smaller technology nodes, the demand for compute cycles in electronic design automation (EDA) and semiconductor manufacturing is rapidly and exponentially increasing. Advanced chip manufacturing requires over 1,000 steps, producing features the size of a biomolecule. Each step must be nearly perfect to yield functional output. To meet this need, accelerated computing and AI have become critical to the semiconductor industry, addressing compute-intensive workloads like logic simulation and verification, physical design, computational lithography, and other mask shop and wafer fab workloads, including inspection and metrology. [Learn More About AI for the Semiconductor Industry](https://www.nvidia.com/en-gb/industries/semiconductor.md) TSMC #### Aerospace Powering next-gen performance, manufacturability, and efficiency. The commercial success of today’s aerospace industry is driven by product innovation, quality, reliability, and operational efficiency. NVIDIA is speeding up design cycle times with accelerated computing, CUDA-X™, AI physics, agent engineering, and interactive digital twins tools for engineering design and simulation. #### Agriculture Revolutionizing agriculture with AI. By using NVIDIA technologies, farmers can analyze data from diverse sources—such as soil moisture sensors, weather forecasts, and satellite imagery—to make better decisions about crop management, irrigation, and pest control. NVIDIA's AI-powered solutions can also help farmers automate repetitive tasks, including monitoring crops, detecting plant diseases, and analyzing soil conditions. By improving efficiency and productivity, these resources ultimately help farmers increase crop yields and reduce waste, contributing to a more sustainable and profitable agriculture industry. Monarch Tractor #### Automotive Driving end-to-end innovation. NVIDIA’s automotive solutions offer the performance and scalability needed to design, simulate, and visualize the future of driving. Designers and engineers can create virtual vehicle design, showrooms, and car configurators; can develop real-time digital twins, in-vehicle AI assistants, and simulation AI agents; and can validate autonomous driving technology—all with NVIDIA CUDA-X, AI physics, autonomous AI agent engineers, Omniverse™ libraries, and accelerated computing platforms. [Learn More About AI in the Automotive Industry](https://www.nvidia.com/en-gb/industries/automotive.md) BMW Group, Koenigsegg, Rimac Automobili #### Chemicals, Materials, and Industrial Biotech Accelerating discovery. AI and accelerated computing have transformed innovations in chemicals, materials, and industrial biotech. These technologies enabled the discovery of novel molecules, formulation optimization, identification of new biotech traits, and more applications. By accelerating such innovations, NVIDIA enables partners and customers to explore a much larger solution space, save computing costs, and automate innovation workflows. [Learn More About AI for Chemical, Materials, and Industrial Biotech](https://resources.nvidia.com/l/en-us-chemicals-materials-and-industrial-biotech) ### Use Cases ## How Developers Are Using NVIDIA AI 1. Design and Engineering 2. Synthetic Data Generation 3. Reinforcement Learning 4. Industrial Facility Digital Twins ## Design and Engineering Computer-aided engineering (CAE) simulation tools offer the ability to quickly assess physical performance. Leading software providers such as Cadence, Siemens, Synopsys, and Dassault are using [NVIDIA CUDA-X libraries](https://developer.nvidia.com/gpu-accelerated-libraries), [AI physics models](https://developer.nvidia.com/physicsnemo), [autonomous AI agents](https://build.nvidia.com/nemoclaw), the [CUDA-X Python](https://developer.nvidia.com/warp-python) framework, and the latest [NVIDIA Blackwell GPUs](https://www.nvidia.com/en-gb/data-center/technologies/blackwell-architecture.md) to accelerate their solvers by orders of magnitude, reducing simulation times from days to hours and enabling higher-fidelity simulations. [Explore the Computational Fluid Dynamics Use Case](https://www.nvidia.com/en-gb/use-cases/computational-fluid-dynamics-simulation.md) McLaren ## Synthetic Data Generation Developers can save a significant amount of training time and greatly reduce costs by using [synthetic data](https://www.nvidia.com/en-gb/glossary/synthetic-data-generation.md) in conjunction with real-world data to create carefully labeled datasets for training multimodal physical AI models. And now, with [NVIDIA Cosmos](https://www.nvidia.com/en-gb/ai/cosmos.md)™, developers can generate even larger datasets with 3D-to-real workflows. [Explore the Synthetic Data Generation Use Case](https://www.nvidia.com/en-us/use-cases/synthetic-data.md) ## Reinforcement Learning With reinforcement learning in simulation, robots can train in any virtual environment through trial and error. This allows robots to develop sophisticated gross and fine motor skills needed for real-world automation tasks, such as grasping novel objects, quadrupedal walking, and learning complex manipulation skills. [Explore the Reinforcement Learning Use Case](https://www.nvidia.com/en-gb/use-cases/reinforcement-learning.md) Agility, Apptronik, Fourier Intelligence, Unitree ## Industrial Facility Digital Twins Leverage Omniverse SDKs and APIs to develop advanced industrial facility digital twins solutions and bring data interoperability, physically based visualization, generative AI, and real-time collaboration to your software. [Explore the Industrial Facility Digital Twins Use Case](https://www.nvidia.com/en-gb/use-cases/ai-for-virtual-factory-solutions.md) Delta Electronics Explore and Build ## Accelerate Your Workflows With NVIDIA Technology Explore pre-built Omniverse Blueprints and workflows to quickly develop or enhance your OpenUSD-based applications and services. ### Build Autonomous AI Agent Engineers Use the NVIDIA® NemoClaw™ reference architecture to build long-running AI agents that autonomously execute engineering simulation workflows. [Try Now](https://build.nvidia.com/nemoclaw) Accenture, KION Group ### Test Multi-Robot Fleets for Industrial Automation Simulate and test physical AI and robotic fleets at scale in industrial digital twins before real-world deployment. [Try Now](https://build.nvidia.com/nvidia/mega-multi-robot-fleets-for-industrial-automation) Luminary Cloud ### Build a Digital Twin for Interactive Fluid Simulation Integrate real-time visualization and analysis into your 3D workflow to enable real-time computer-aided engineering of your product. [Try Now](https://build.nvidia.com/nvidia/digital-twins-for-fluid-simulation) ### Build Digital Twins for AI Factory Design and Operations Design, test, and optimize a new generation of intelligence manufacturing data centers using digital twins. [Try Now](https://build.nvidia.com/nvidia/digital-twins-for-ai-factories) Foxconn ### Spatial Streaming for Omniverse Digital Twins Stream immersive OpenUSD-based Omniverse digital twins to the Apple Vision Pro with this reference workflow. [Explore Workflow](https://developer.nvidia.com/blog/experience-digital-twins-in-xr-with-nvidia-omniverse-spatial-streaming/) Microsoft Azure ### Build Digital Twins for Remote Monitoring Enable remote monitoring of industrial operations with accurate digital twins integrated with real-time IoT data. [Explore Workflow](https://developer.nvidia.com/blog/connect-real-time-iot-data-to-digital-twins-for-3d-remote-monitoring/) Previous Next 1. Build Autonomous AI Agent Engineers 2. Test Multi-Robot Fleets for Industrial Automation 3. Build a Digital Twin for Interactive Fluid Simulation 4. Build Digital Twins for AI Factory Design and Operations 5. Spatial Streaming for Omniverse Digital Twins 6. Build Digital Twins for Remote Monitoring Success Stories ## See the Real-World Impact Learn from ‌industrial leaders using AI to optimize processes, reduce risk, and trim costs. [More Success Stories](https://www.nvidia.com/en-gb/case-studies/?industries=Manufacturing+%2F+Product+Design%2CManufacturing) > The next era of industrial digitalization has arrived. With NVIDIA Omniverse APIs on Microsoft Azure, organizations across industries and around the world can connect, collaborate and enhance their existing tools to create the next wave of AI-enabled digital twins. — Andy Pratt, Corporate Vice President, Microsoft Emerging Technologies > Computational lithography, specifically optical proximity correction, or OPC, is pushing the boundaries of compute workloads for the most advanced chips. By collaborating with our partner NVIDIA to run Synopsys OPC software on the cuLitho platform, we massively accelerated performance from weeks to days! The team up of our two leading companies continues to force amazing advances in the industry. — Aart de Geus, Chairman and CEO, Synopsys > With Omniverse APIs, Teamcenter X lets companies like HD Hyundai unify and visualize massive engineering data sets interactively and integrate generative AI to generate 3D objects or HDRI backgrounds to see their projects in context. The result is an ultra-intuitive, photoreal, physics-based digital twin that eliminates waste and errors, delivering huge savings in cost and time. — Dr. Roland Busch, CEO, Siemens AG Previous Next 1. quote 1 2. quote 2 3. quote 3 ## News and Events Load More ## Resources ## Take a Deeper Dive Into AI for the Industrial Sector 1. Videos 2. Press Releases 3. Training 4. Community Siemens **Featured** ### What’s Next in Industrial AI? Industrial AI is driving the next era of design and manufacturing processes. Hear industry leaders from Siemens, Mercedes-Benz, and Pegatron share how agentic AI and digital twins are transforming the way we design, build, and operate industrial facilities and products. [Watch Now](https://www.youtube.com/watch?v=RLZk-Fr7wz4) Videos [See All](https://resources.nvidia.com/l/en-us-industrial-sector-resources) ### Digital Twins for Physical AI Learning Path Get started with essential foundations in developing OpenUSD-based digital twin applications and workflows for the era of physical AI. [Explore Curriculum](https://www.nvidia.com/en-gb/learn/learning-path/digital-twins.md) ### Computer Vision for Industrial Inspection Learn how to create an end-to-end hardware-accelerated industrial inspection pipeline to automate defect detection. Using NVIDIA’s own production dataset as an example, we will illustrate how the application can be easily applied to a variety of manufacturing use cases. [Industrial Inspection Workshop](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-MF-01+V2) ### NVIDIA Training Our expert-led courses and workshops provide learners with the knowledge and hands-on experience they need to unlock the full potential of NVIDIA solutions. NVIDIA Training offers customized training plans designed to bridge technical skill gaps and provide relevant, timely, and cost-effective solutions for an organization's growth and development. [Visit NVIDIA Training](https://www.nvidia.com/en-us/learn/organizations.md) ### NVIDIA Developer Program Connect with millions of like-minded developers and access hundreds of NVIDIA-accelerated containers, models, and SDKs—all the tools necessary to successfully build apps with NVIDIA technology—through the NVIDIA Developer Program. [Join the Developer Program](https://developer.nvidia.com/developer-program) ### NVIDIA Inception Program for Startups Evolve your startup with go-to-market support, technical expertise, training, and funding opportunities. Inception provides 14,000+ cutting-edge startups worldwide with resources to accelerate their business. See how program members are using NVIDIA technology to create innovative products. [Learn More and Apply](https://www.nvidia.com/en-gb/startups.md) ## NVIDIA Partners for Industrial Sector Our solutions for the industrial sector go beyond products. Our partners are here to assist your organization at every level to build and execute transformative AI strategies, products, and services. [Explore Our Partners](https://www.nvidia.com/en-gb/industries/industrial-sector/partners.md) ## Get Started ## Take the Next Steps ### Stay Up to Date on NVIDIA News for the Industrial Sector [Subscribe](#industrial-subscribe-modal) ### Request a Consultation Our experts can help your business unlock potential and unleash innovation. [Let's Talk](#schedule-meeting) ## Schedule a Meeting with Us Welcome back. Not you? Log Out Welcome back. Not you? Clear form ![YouTube Video](https://img.youtube.com/vi_webp/BRgwx12rhqg?si=enzgM7uMmLtpiZ4B/maxresdefault.webp) Consent for Optional Cookies (googleCookiePolicyLink)YouTube sets performance, advertising, and other optional cookies(/googleCookiePolicyLink) when you watch embedded videos. To watch this video, you need to turn on optional cookies for the site. 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