Nvidia Expands AI Factory Digital Twins Blueprint

By Netvora Tech News

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Nvidia has announced a significant expansion of its Omniverse Blueprint for AI factory digital twins, now available as a preview. The blueprint features new integrations across the AI factory power, cooling, and networking ecosystems with industry leaders Delta Electronics, Jacobs, and Siemens joining existing partners Cadence, Schneider Electric with ETAP and Vertiv.

This growing ecosystem unifies the design and simulation of billions of components required to build digital twins of AI factories. The expanded blueprint will equip engineering teams to design, simulate, and optimize entire AI factories in physically accurate virtual environments, enabling early issue detection and the development of smarter, more reliable facilities.

Built on reference architectures for Nvidia GB200 NVL72-powered AI factories, the blueprint taps into Universal Scene Description (OpenUSD) asset libraries. This allows developers to aggregate detailed 3D and simulation data representing all aspects of the data center into a single, unified model, enabling them to design and simulate advanced AI infrastructure optimized for efficiency, throughput, and resiliency.

Partners Join Forces with Nvidia

Nvidia's Omniverse Blueprint for AI factory digital twins brings together diverse partners and tools to optimize the design, simulation, deployment, and operations of AI factories. Today, the company announced that new partners are contributing to the framework, including:

• Delta Electronics, a global leader in power and thermal management solutions
• Jacobs, a global provider of technical, professional, and construction services
• Siemens, a global technology powerhouse in the fields of industry, energy, and healthcare

Building SimReady Assets for AI Factories

The Omniverse Blueprint for AI factory digital twins enables companies to design and simulate advanced AI infrastructure optimized for efficiency, throughput, and resiliency. With digital twins, these companies can prepare for building AI factories in real life, ensuring early issue detection and the development of smarter, more reliable facilities.