Nvidia retreated from building its own cloud service due to the difficulty and unreliability of its 'cloud of clouds' model, which leased competitor infrastructure. It has now pivoted to a less complex marketplace model, connecting customers to smaller cloud providers instead.
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Firms like OpenAI and Meta claim a compute shortage while also exploring selling compute capacity. This isn't a contradiction but a strategic evolution. They are buying all available supply to secure their own needs and then arbitraging the excess, effectively becoming smaller-scale cloud providers for AI.
Nvidia's staggering revenue growth and 56% net profit margins are a direct cost to its largest customers (AWS, Google, OpenAI). This incentivizes them to form a defacto alliance to develop and adopt alternative chips to commoditize the accelerator market and reclaim those profits.
A fundamental shift is occurring where startups allocate limited budgets toward specialized AI models and developer tools, rather than defaulting to AWS for all infrastructure. This signals a de-bundling of the traditional cloud stack and a change in platform priorities.
With partners like Microsoft and Nvidia reaching multi-trillion-dollar valuations from AI infrastructure, OpenAI is signaling a move up the stack. By aiming to build its own "AI Cloud," OpenAI plans to transition from an API provider to a full-fledged platform, directly capturing value it currently creates for others.
OpenAI is actively diversifying its partners across the supply chain—multiple cloud providers (Microsoft, Oracle), GPU designers (Nvidia, AMD), and foundries. This classic "commoditize your compliments" strategy prevents any single supplier from gaining excessive leverage or capturing all the profit margin.
NVIDIA's financing and demand guarantees for its chips are not just to spur sales, which are already high. The strategic goal is to reduce customer concentration by helping smaller players and startups build compute capacity, ensuring NVIDIA isn't solely reliant on a few hyperscalers for revenue.
The high-speed link between AWS and GCP shows companies now prioritize access to the best AI models, regardless of provider. This forces even fierce rivals to partner, as customers build hybrid infrastructures to leverage unique AI capabilities from platforms like Google and OpenAI on Azure.
AI company Anthropic's potential multi-billion dollar compute deal with Google over AWS is a major strategic indicator. It suggests AWS's AI infrastructure is falling behind, and losing a cornerstone AI customer like Anthropic could mean its entire AI strategy is 'cooked,' signaling a shift in the cloud platform wars.
The rise of public cloud was driven by a business model innovation as much as a technological one. The core battle was between owning infrastructure (capex) and renting it (opex) with fractional consumption. This shift in how customers consume and pay for services was the key disruption.
Anthropic is making its models available on AWS, Azure, and Google Cloud. This multi-cloud approach is a deliberate business strategy to position itself as a neutral infrastructure provider. Unlike competitors who might build competing apps, this signals to customers that Anthropic aims to be a partner, not a competitor.
