Relativity Networks Secures $22 Million in Funding to Advance Hollow-Core Fiber Technology

Data center developers are projected to invest up to $4 trillion by the decade’s end, facing significant constraints from political and power-grid challenges. In a bid to address these limitations, Relativity Networks announced $22 million in SAFE note funding on Tuesday, backed by Rhapsody Venture Partners, Bell Ventures Inc., and Faster Than Glass LLC, among others. The company has also acquired a $40 million follow-on order from an unnamed leading hyperscaler.

Relativity Networks specializes in hollow-core fiber, an innovative technology that enables data transmission to occur 30% faster than traditional fiber optics. Unlike conventional fiber that uses fiber-optic glass to transmit light, hollow-core fiber utilizes a vacuum chamber at the core, allowing it to approach the theoretical limits of light speed.

CEO Jason Eisenholz estimates that signals traverse approximately five microseconds per kilometer in conventional fiber. With hollow-core fiber, this latency is reduced to about three and a half microseconds, presenting significant advantages as data center infrastructures expand. As the deployment of AI compute grows, the physical distances between GPUs in sprawling data center campuses increase, making latency a critical concern.

Eisenholz believes that hollow-core fiber provides a unique advantage for multi-campus deployments, which can operate as interconnected units rather than isolated systems. “The largest systems are distributing the compute across multiple campuses to reach the power that exists,” he stated. “They’re moving to where the warm shell is, but they still need to operate as one synchronized machine.”

This reduction in latency could aid data center developers in expanding their geographical reach. With a 30% reduction in lag time, Eisenholz suggests that teams can now span 30% larger distances without facing latency issues. He views this development as a potential turning point for the industry, indicating the evolution of AI from focusing on compute optimization to enhancing networking and geographical strategies.

“The first era of AI optimized for compute,” Eisenholz remarked. “It was GPU, GPU, GPU. The second era optimized the networking inside the data center to take advantage of that compute. The third era that we see coming is optimizing the geography.”