Many enterprise leaders have spent the past few years laser-focused on their AI strategies. They’ve obsessed over every detail of which hardware they should acquire and which models they should run. But now, they’re realizing that where they run AI workloads is just as important as what they run. In particular, inference workloads can be highly sensitive to latency, so it’s important to place infrastructure in proximity to the data sources needed for useful results. Enterprises that don’t account for this could end up with AI applications that look great on paper, but ultimately fail to meet expectations. The emergence of…

The post How Close Is Your AI Infrastructure to the Agents That Depend on It? appeared first on Interconnections - The Equinix Blog.