At its first Horizon customer and partner event this week, Equinix Inc. argued that the architecture of enterprise artificial intelligence is being reshaped by a simple yet hard-to-answer question: Where should inference run?
For the past several years, much of the AI infrastructure conversation has centered on the supply and cost of accelerated computing. The focus has been on graphics processing units, AI factories, training clusters and the unprecedented capital buildout required to support them. Those remain crucial. But as enterprise AI shifts from experiments to real applications, the more immediate operational challenge is distribution.
Data resides across multiple clouds and enterprise systems. Users, sensors and business processes are dispersed across regions. Models may be proprietary, open source, fine-tuned or delivered as services. AI agents will call other agents, tools and application programming interfaces across organizational and infrastructure boundaries. In this environment, compute is only one component of a system that must be connected, governed and continuously optimized.
That is the premise behind the two announcements Equinix made at Horizon: Equinix Fabric One, an intent-driven, managed any-to-any connectivity service, and Equinix Inference Exchange, a distributed inference offering built with Nvidia Corp. and Together AI Inc.
