Emerging cloud providers (“NeoClouds”) are sticking exclusively with NVIDIA, despite alternatives from AMD. The perceived performance risk is too high, as customers demand state-of-the-art inference speed and providers can't risk a multi-billion dollar investment on a non-NVIDIA stack that might offer lower throughput.

George Hotz outlines a contrarian AI infrastructure strategy. Instead of expensive enterprise hardware, Tiny Corp plans to use upcoming consumer AMD GPUs, pair them with extremely cheap power in Oregon (~$0.03/kWh), and sell compute tokens on existing platforms. This low-overhead model aims to undercut traditional cloud providers.

The primary bear case for specialized neoclouds like CoreWeave isn't just competition from AWS or Google. A more fundamental risk is a breakthrough in GPU efficiency that commoditizes deployment, diminishing the value of the neoclouds' core competency in complex, optimized racking and setup.

CoreWeave argues that large tech companies aren't just using them to de-risk massive capital outlays. Instead, they are buying a superior, purpose-built product. CoreWeave’s infrastructure is optimized from the ground up for parallelized AI workloads, a fundamental shift from traditional cloud architecture.

Specialized AI cloud providers like Nebius don't aim to push alternative chips like AMD or TPUs. Instead, they are "market catchers," responding directly to overwhelming customer demand, which is currently focused entirely on NVIDIA. This demand-driven approach dictates their hardware strategy.

For leading AI labs like Anthropic and OpenAI, the primary value from cloud partnerships isn't a sales channel but guaranteed access to scarce compute and GPUs. This turns negotiations into a complex, symbiotic bundle covering hardware access, cloud credits, and revenue sharing, where hardware is the most critical component.

The enormous scale of Meta's deal with specialized data center operator Nebius proves that "NeoClouds" are now critical infrastructure players. They are successfully competing with hyperscalers by offering specialized services and, crucially, available capacity, making them essential partners for AI giants.

A new category of cloud providers, "NeoClouds," are built specifically for high-performance GPU workloads. Unlike traditional clouds like AWS, which were retrofitted from a CPU-centric architecture, NeoClouds offer superior performance for AI tasks by design and through direct collaboration with hardware vendors like NVIDIA.

Newer AI cloud providers gain a performance advantage by building their infrastructure entirely on NVIDIA's integrated ecosystem, including specialized networking. Incumbent clouds often must patch their legacy, CPU-centric systems, creating inefficiencies that 'neo-clouds' without technical debt can avoid.