Designing the Future: How AI Factories Are Transforming Data Centers

In a world increasingly powered by artificial intelligence, data centers — once seen as mere warehouses of servers — are evolving into something far more dynamic and vital: AI Factories.

At NVIDIA’s recent GTC conference, a joint session led by Kourosh Nemati, Senior Data Center Cooling and Infrastructure Engineer at NVIDIA, and Sherman Ikemoto, Sales Development Group Director at Cadence, offered deep insights into the next generation of data centers. Their discussion highlighted how simulation technology, digital twins, and ecosystem collaboration are fundamentally reshaping infrastructure for the AI era.

Let’s walk through this important transformation.

The Rise of the AI Factory

The traditional idea of a data center — a place filled with racks of servers and cooling systems — is quickly becoming outdated.

Today’s vision centers around AI Factories: highly dynamic, compute-intensive environments designed to support massive AI workloads, real-time inference, and foundational model training across industries like healthcare, autonomous vehicles, and scientific research.

However, with this transformation comes immense complexity. Building an AI Factory requires seamless coordination among power systems, cooling, networking, and compute infrastructure. The tolerances are tighter, the performance demands are higher, and traditional methods of designing and operating data centers are no longer sufficient.

This is where the concept of a Digital Twin becomes indispensable.

Simulation: The New Backbone of Data Center Design

To address the complexity of AI Factories, NVIDIA has introduced the AI Factory Digital Twin, built on its Omniverse platform and powered by the OpenUSD (Universal Scene Description) framework.

Unlike static models, this Digital Twin is a continuously updating simulation environment that integrates mechanical, electrical, and thermal data into one cohesive platform.

By leveraging this technology, engineers can:

• Evaluate "what-if" scenarios during design

• Test and refine control logic

• Identify potential failure points before physical installation

• Accelerate deployment timelines

• Reduce operational risks dramatically

Rather than waiting for issues to emerge after construction, potential problems can now be identified and addressed during the design phase. This marks a significant evolution in data center infrastructure development.

Cadence: The Simulation Powerhouse Behind It All

Following Kourosh’s presentation, Sherman Ikemoto of Cadence detailed how multiphysics simulation underpins the AI Factory Digital Twin.

Historically, teams working on electrical, thermal, and structural elements often operated in silos. In AI Factories, these disciplines must be integrated into a unified, data-driven process. Without this integration, even well-optimized individual systems can fail to work efficiently as a whole.

Cadence’s advanced simulation technology solves this challenge.

Through detailed power integrity modeling, dynamic thermal simulations, and a commitment to open standards like OpenUSD, Cadence enables teams to make early, informed decisions during the design phase. Their Reality Digital Twin Platform ensures that digital models are physically accurate, scalable, and aligned with real-world operational needs.

Cadence’s focus on interoperability is also key, helping to ensure that simulation data flows seamlessly between design tools, 3D models, and real-time telemetry systems.

Ecosystem Collaboration: The Key to Success

Another important message from the session was that building AI Factories is not a solo effort.

The complexity of these facilities requires close collaboration across the entire technology ecosystem.

Key partners such as Foxconn and Vertiv are playing critical roles:

• Foxconn is leveraging its global manufacturing capabilities to speed up the production of modular AI Factory components.

• Vertiv, a leader in power and cooling infrastructure, is collaborating with NVIDIA and Cadence to simulate and validate the behavior of critical systems like Coolant Distribution Units (CDUs), Power Distribution Units (PDUs), and Heating, Ventilation, and Air Conditioning (HVAC) systems within the digital twin.

By validating these systems under simulated peak AI workloads, teams can ensure resilience, performance, and scalability before a single piece of equipment is installed on-site.

Final Thoughts: Shaping Tomorrow’s Data Centers Today

The transformation from traditional data centers to AI Factories marks a pivotal shift in technology infrastructure.

With the integration of advanced simulation, digital twins, and ecosystem-wide collaboration, companies like NVIDIA, Cadence, Foxconn, and Vertiv are setting new standards for how next-generation data centers are designed, deployed, and operated.

As AI continues to evolve and scale, the infrastructure supporting it must evolve just as rapidly.

The future of innovation will belong to those who can simulate, design, and collaborate at a level never before imagined.

Source - Semiwiki