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Introduction:
NVIDIA is redefining how we build, test, and optimize AI factories by expanding its Omniverse Blueprint—a powerful framework for creating digital twins of AI infrastructure. With this preview release, NVIDIA brings new integrations with global tech giants like Siemens, Delta Electronics, Jacobs, Cadence, and others, enabling engineering teams to model and simulate entire AI factory environments with unprecedented accuracy. This expansion is set to revolutionize industrial AI development, energy efficiency, and operational reliability.
Summary:
NVIDIA has announced a major expansion of its Omniverse Blueprint for AI factory digital twins. Now available as a preview, this blueprint provides engineering teams with tools to design, simulate, and optimize AI factory infrastructure in highly accurate virtual environments. The updated platform includes integrations with top industry players like Siemens, Delta Electronics, and Jacobs, adding to existing collaborations with Cadence, Schneider Electric, ETAP, and Vertiv.
The blueprint is built on NVIDIA’s GB200 NVL72 reference architecture and uses OpenUSD (Universal Scene Description) to create unified 3D models of every component in an AI factory. This approach helps engineers identify issues early, optimize performance, and design more efficient facilities. By connecting with platforms like the Cadence Reality Digital Twin and ETAP, engineers can test thermal, power, and network configurations before any physical construction begins.
One standout feature is the SimReady standardization—a workflow designed to ensure all models within the blueprint are physics-based and simulation-ready. This enables accurate modeling of power systems, cooling infrastructure, building automation, and even agentic AI systems. With this development, the digital twin ecosystem can scale efficiently to meet the demands of AI factories worldwide.
NVIDIA and its partners aim to push boundaries by turning traditional data centers into intelligent, AI-driven environments. Through the Omniverse Blueprint, companies can now simulate entire AI workloads, optimize energy consumption, and reduce the risks of costly delays. As AI factories become increasingly vital in our digital landscape, NVIDIA’s solution emerges as a crucial tool in building smarter, more resilient infrastructure.
What Undercode Say:
NVIDIA’s expansion of its Omniverse Blueprint marks a bold step toward digital transformation in industrial AI. This isn’t just about graphics or simulations—it’s a strategic shift in how we engineer physical infrastructure in a world driven by AI demands.
From an industry analysis perspective, digital twins are evolving from nice-to-have visualizations to essential tools for predictive design and operations. The inclusion of OpenUSD ensures interoperability, while the SimReady framework guarantees that simulations are grounded in real-world physics—critical for managing power, cooling, and networking loads that AI training demands.
Companies like Siemens and Delta Electronics bring in physical hardware expertise, allowing for richer, real-world aligned models. Cadence and ETAP’s involvement connects software design and energy optimization, a combo that’s increasingly vital as energy consumption becomes the new bottleneck for data centers.
This expansion also illustrates a bigger trend in enterprise AI: vertical integration of software and infrastructure. NVIDIA isn’t just selling GPUs—it’s architecting the ecosystem where those GPUs live and work. The Omniverse Blueprint is a foundational layer that turns isolated systems into connected, intelligent environments.
Moreover, the SimReady asset standard sets a precedent. It could become the HTML of infrastructure modeling, where AI developers and infrastructure engineers work on a common, modular foundation. This opens doors for faster time-to-market, fewer errors, and better sustainability metrics.
For companies looking to adopt industrial AI, this blueprint could significantly lower the barrier of entry. With plug-and-play models and pre-validated simulation assets, organizations no longer need massive in-house teams to manage every layer of AI infrastructure. It’s a move toward democratizing access to AI-scale infrastructure.
NVIDIA’s broader vision of the “AI factory” as a digitally simulated, pre-optimized machine has strong implications for cloud, edge computing, and smart cities. It’s not just about building data centers—it’s about turning them into intelligent agents in a distributed AI network.
🕵️ Fact Checker Results:
✅ The blueprint is based on NVIDIA’s GB200 NVL72 architecture and uses OpenUSD.
✅ Siemens, Delta Electronics, and Jacobs are officially confirmed new partners.
✅ SimReady assets are now publicly available and standardized for wider industry use.
🔮 Prediction:
As AI workload demands skyrocket, the Omniverse Blueprint will become a core planning tool for future data centers. Expect to see widespread adoption by telecoms, hyperscalers, and industrial AI developers. Within the next two years, SimReady standards could emerge as an industry baseline for infrastructure modeling, influencing everything from robotics deployment to autonomous facility operations.
References:
Reported By: blogs.nvidia.com
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