In the realm of AI computing, a new breed of cloud providers, known as “neoclouds,” has emerged, driven by billion-dollar deals and a soaring demand for generative AI. These neoclouds are distinguished by their specialized infrastructure tailored for large-scale model training and high-throughput inference, setting them apart from traditional cloud providers.
Leading players in the neocloud space, such as CoreWeave, Crusoe, Lambda Labs, and Nebius, are rapidly expanding their operations, leveraging their roots in crypto-mining and high-performance computing. These providers offer purpose-built architectures that converge on GPUs equipped with high-bandwidth memory, intranode links like NVLink/NVSwitch, and cluster-scale networks such as InfiniBand or RDMA-enabled Ethernet.
Despite their rapid growth, neocloud providers face challenges related to supply chain constraints and the escalating power demands of AI workloads. The industry is grappling with shortages of critical components like memory, high-speed networking equipment, cooling systems, and power infrastructure, posing obstacles to seamless operational scalability. As the neocloud landscape evolves, providers must refine their offerings to remain competitive in a dynamic market characterized by technical complexity and persistent supply chain disruptions.
