As businesses contend with ever-increasing data volumes and performance-intensive applications such as AI model training, AI inferencing and high-performance computing, they need infrastructure that delivers speed, scalability and efficiency without added complexity.
By neoclouds, I'm referring to GPU-centric, purpose-built cloud services that focus primarily on AI training and inference rather than on the sprawling catalog of general-purpose services that hyperscalers offer. In many cases, these platforms deliver better price-performance for AI workloads because they're engineered for specific goals: keeping expensive accelerators highly utilized, minimizing platform overhead, and providing a clean path from model development to deployment.