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.

While focus is on massive supercomputers for training next-gen models, the real supply chain constraint will be 'inference' chips—the GPUs needed to run models for billions of users. As adoption goes mainstream, demand for everyday AI use will far outstrip the supply of available hardware.

Anthropic is throttling user access during peak hours due to GPU shortages. This confirms that the AI industry remains severely compute-constrained and validates the multi-billion dollar infrastructure investments by giants like OpenAI and Meta, which once seemed excessive.

Despite massive infrastructure investments, Greg Brockman believes demand for AI will consistently outstrip supply, leading to a long-term state of "compute scarcity." As AI tackles bigger problems like curing diseases, the appetite for computation will prove effectively infinite, making it a chronically scarce resource.

The focus in AI has evolved from rapid software capability gains to the physical constraints of its adoption. The demand for compute power is expected to significantly outstrip supply, making infrastructure—not algorithms—the defining bottleneck for future growth.

Escalating compute requirements for frontier models are creating a new market dynamic where access to the best AI becomes restricted and expensive. This shifts power to the labs that control these models, creating a "seller's market" where they act as "kingmakers," granting massive competitive advantages to the highest corporate bidders.

The comparison of the AI hardware buildout to the dot-com "dark fiber" bubble is flawed because there are no "dark GPUs"—all compute is being used. As hardware efficiency improves and token costs fall (Jevons paradox), it will unlock countless new AI applications, ensuring that demand continues to absorb all available supply.

The value unlocked by frontier AI models is expanding so rapidly that there isn't enough hardware to meet demand. This scarcity ensures that not just the top lab (like OpenAI), but also second and third-tier competitors, will operate at full capacity with strong margins.

Contrary to expectations of easing supply, the GPU shortage has intensified since 2023. With clearer AI business models, mega-customers like OpenAI and Anthropic are spending even more aggressively, creating a fierce bidding war that pushes startups out.