Relativity Networks raises $22 million to bring a faster kind of fiber to data centers
Relativity Networks deals in hollow-core fiber, a rarely deployed technology that allows data to be transmitted 30% faster than conventional fiber.
Data center developers anticipate spending up to $4 trillion by the end of the decade, but their location choices are often constrained by political factors and power-grid limitations. Relativity Networks, however, believes that faster fiber could change the geographical dynamics of data center construction. The company recently raised $22 million in SAFE notes from venture capital firms such as Rhapsody Venture Partners, Bell Ventures Inc., and Faster Than Glass LLC.
In addition, a leading hyperscaler agreed to a $40 million follow-on investment, though the firm's name was not disclosed.
Relativity Networks specializes in hollow-core fiber, a technology that transmits data 30% faster than traditional fiber-optic glass. While regular fiber carries light through glass, hollow-core fiber utilizes a vacuum chamber in the center of the line, bringing the light closer to the theoretical speed limit of light. This difference manifests in microseconds.
CEO Jason Eisenholz estimates that a signal travels approximately five microseconds to travel one kilometer in conventional fiber, but that figure can be reduced to just three and a half microseconds when using hollow-core fiber.
As AI computing scales across multiple racks of GPUs, the physical distance between these components has grown significantly. Data center campuses now stretch across hundreds of acres and multiple buildings, making latency a crucial consideration. By deploying hollow-core fiber, Relativity Networks offers a potential solution to the spatial limitations that have hindered data center buildouts.
The technology could enable developers to span 30% larger distances before latency becomes a concern, effectively expanding the geographical reach of data centers.
Eisenholz believes that this innovation could represent a major shift in the industry, marking the third era of AI optimization. The first era focused solely on compute, while the second era concentrated on improving networking within data centers to harness the power of GPUs. The third era, according to Eisenholz, is centered on optimizing geographical placement to maximize efficiency.
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