Growing pains: how distributed AI training changes the network between datacenters

Large-scale AI training has already escaped the confines of a single datacenter. Google said Gemini was trained synchronously across clusters in multiple locations; Microsoft has connected AI data centres in Wisconsin and Georgia into what it describes as one distributed AI supercomputer; AWS has connected AI compute clusters across wide areas to allow Anthropic to build Claude models; Meta has built high-capacity datacenter interconnects to support model training; and CoreWeave and Google Cloud