Data centers are increasingly central to the burgeoning AI landscape. The infrastructure required to train and execute AI models demands significant resources, demanding high power, cooling solutions, ample floor space, high-speed networking, and specialized computing capabilities.
At major data center events, such as Metro Connect in Florida, discussions surrounding power, cooling, and real estate finances take precedence. Omdia predicts that the global IT power capacity will soar to 314 GW by 2030, a staggering 2.9-fold increase, largely fueled by AI needs. Ensuring reliable power is essential for effective AI operations.
Networking capabilities are equally crucial. While the current discourse often segregates networking and computing into distinct forums like Nvidia’s GTC or OFC, this division risks neglecting their interdependencies. Data center operators must find a comprehensive understanding of how connectivity complements their AI deployments.
Scaling Across: A New Connectivity Model
The notion of "scale across," introduced by Nvidia’s CEO Jensen Huang in 2025, captures the necessity for high-bandwidth connectivity between data centers dedicated to AI functions, including both training and inference. This new design is pivotal for facilitating interconnected GPU clusters that operate across various facilities.
The escalating power needs mean that traditional single-facility infrastructures are inadequate. Hyperscale clusters may require up to a gigawatt of power, often necessitating a multi-site approach spanning different electrical grids. To function cohesively, these setups require ultra-fast, low-latency, and high-availability optical connectivity among buildings.
The Impact of Power on Data Center Development
The demand for power is prompting a shift in location preferences for data centers. Regions like Northern Virginia and Dallas are traditionally favored, but power shortages in these areas lead to increased costs and prolonged wait times, sometimes extending to five years. Consequently, new expansive data center projects are emerging in locations like Lancaster, Pennsylvania, and Memphis, designed for robust power access.
These sites frequently lack the necessary fiber-optic infrastructure, resulting in isolated facilities that struggle with data connectivity, as distances to metropolitan hubs can stretch hundreds of kilometers. Without adequate optical links, these mega data centers risk becoming operationally stranded.
The primary motivator behind current data center developments is the substantial power needs of AI. Whether for multi-site AI training clusters or large power campuses, the trend is clear: power access is paramount. However, integrating optical fiber connectivity into these plans is increasingly critical for ensuring streamlined operations. The revised perspective acknowledges that both power and robust networking capabilities are essential for facilitating effective AI functions in data centers.
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