Relativity Networks Raises $22M to Bring Faster Hollow-Core

Data center developers are expected to spend up to $4 trillion by the end of the decade, and their buildout locations are already heavily constrained by political factors and power-grid limitations. While most assume fiber speed is fixed, one company is betting that faster fiber could reshape the geographical calculus of data center expansion. On Tuesday, Relativity Networks announced $22 million in SAFE note funding from investors including Rhapsody Venture Partners, Bell Ventures Inc., and Faster Than Glass LLC. A SAFE note—an instrument that converts into shares upon the company's first priced round—is a standard mechanism for pre-seed and seed funding. The company also secured a $40 million follow-on order from a leading hyperscaler that declined to be named. Relativity Networks specializes in hollow-core fiber, a rarely deployed technology that transmits data 30% faster than conventional fiber. Traditional fiber sends light through glass, but hollow-core fiber routes the same light through a vacuum chamber in the center of the line, bringing it much closer to the theoretical speed of light. The difference is measured in microseconds. CEO Jason Eisenholz estimates a signal takes about five microseconds to travel one kilometer in conventional fiber, but only three and a half microseconds via hollow-core. When AI computing was confined to a single rack of GPUs, fiber latency was negligible. But as scale has grown, so has the physical distance between GPUs. Data center campuses now often span hundreds of acres and dozens of buildings. Eisenholz sees a particular opportunity in multi-campus deployments, where existing data centers are linked to operate as a single synchronized unit. “The largest systems are distributing compute across multiple campuses to reach the power that exists,” he told TechCrunch. “They’re moving to where the warm shell is, but they still need to operate as one synchronized machine.” This approach partially alleviates the spatial constraints that have limited data center buildouts. By reducing latency by 30%, developers can span 30% larger distances before latency becomes a bottleneck. As compute projects continue to scale, Eisenholz believes this could be a transformative shift for the industry. “The first era of AI optimized for compute,” he said. “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.”

via TechCrunch AI