Siemens Expands Data Center Partner Ecosystem to Scale Next-Generation AI Infrastructure

[Erkan Teskancan]

### Introduction
As the rapid growth in artificial intelligence increases the demand for data center capacity, Siemens Smart Infrastructure is expanding its data center ecosystem to meet this need with flexibility and energy efficiency.

### Siemens' Ecosystem Expansion for Next-Generation AI Infrastructure
Siemens is strategically partnering with and investing in Emerald AI, bringing together flexible computing and energy solutions for data centers. By integrating Fluence battery energy storage systems and PhysicsX for physics-based AI modeling, Siemens enables data center operators to accelerate grid connections, efficiently scale capacity, and operate reliably in energy-constrained conditions.

Ruth Gratzke, President of Siemens Smart Infrastructure USA, emphasized that the growth in AI infrastructure presents challenges not only in computing but also in energy and infrastructure dimensions. She stated that grid capacity and connection times limit data center growth, and coordinating complex digital and energy domains will accelerate this process.

### Grid Coordination with Emerald AI
Thanks to Emerald AI, AI workloads can be adjusted based on grid conditions in terms of time and location. This dynamic approach reduces demand peaks, shortens data centers' grid connection times, and alleviates pressure on energy infrastructure. Thus, Siemens provides true integration of information and operational technologies.

### Fluence Energy Storage Systems
Fluence's large-scale energy storage solutions help accelerate grid connections for high-performance AI data centers. These systems enable the shaping of electrical loads and the coordination of ramp rates, making it possible to establish data centers in energy-constrained regions and allowing energy storage systems to be commissioned within months compared to grid upgrades.
Energy storage also ensures data centers remain operational during outages or capacity reductions.

### Physics-Based AI Modeling with PhysicsX
In collaboration with PhysicsX, Siemens uses physics-based AI models in the design and operation of data center power distribution systems. These models, trained with Siemens' multi-physics simulation data, can predict thermal behavior in complex systems in real-time. This accelerates the design process, optimizes infrastructure for AI workloads, and prepares a predictive monitoring infrastructure across the facility.

### Conclusion
Against the power system challenges posed by large and dynamic AI workloads, Siemens' new ecosystem integrates the coordination of AI workloads, grid-integrated energy systems, and optimized physical infrastructure, ensuring the seamless and efficient operation of the next generation of data center infrastructure.