AI infrastructure requires a shift toward first principles thinking to overcome the inefficiencies of current, unoptimized AI factories. While training remains a significant cost, doubling the utilization of these clusters through advanced networking directly scales inference revenue. Historically, technological discontinuities—such as the evolution of GPUs and the structural design of electric vehicles—have rewarded those who re-engineered systems from the ground up. Networking now represents the most critical bottleneck in large-scale AI clusters, where superior backplane performance enables greater coherence across hundreds of thousands of accelerators. Investors and cloud providers must prioritize these networking advancements to gain a competitive edge as the industry moves toward token-based pricing models. By adopting purpose-built networking solutions, organizations can transform their infrastructure into high-revenue assets, mirroring the transformative impact seen in previous networking shifts like the rise of Arista.
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