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.

In the race for AI dominance, Meta pivoted from its world-class, energy-efficient data center designs to rapidly deployable "tents." This strategic shift demonstrates that speed of deployment for new GPU clusters is now more critical to winning than long-term operational cost efficiency.

Unlike traditional software, OpenAI's growth is limited by a zero-sum resource: GPUs. This physical constraint creates a constant, painful trade-off between serving existing users, launching new features, and funding research, making GPU allocation a central strategic challenge.

Instead of bearing the full cost and risk of building new AI data centers, large cloud providers like Microsoft use CoreWeave for 'overflow' compute. This allows them to meet surges in customer demand without committing capital to assets that depreciate quickly and may become competitors' infrastructure in the long run.

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.

Instead of managing compute as a scarce resource, Sam Altman's primary focus has become expanding the total supply. His goal is to create compute abundance, moving from a mindset of internal trade-offs to one where the main challenge is finding new ways to use more power.

The limiting factor for large-scale AI compute is no longer physical space but the availability of electrical power. As a result, the industry now sizes and discusses data center capacity and deals in terms of megawatts, reflecting the primary constraint on growth.

After its initial joint venture stalled, OpenAI explored building its own data centers but found securing project financing as a non-investment grade tenant too difficult. This financial reality pushed them back to the partnership table with Oracle for a massive 4.5 gigawatt deal.

The exponential growth of AI is fundamentally constrained by Earth's land, water, and power. By moving data centers to space, companies can access near-limitless solar energy and physical area, making off-planet compute a necessary step to overcome terrestrial bottlenecks and continue scaling.