Even Google can't get enough compute. Bloomberg reports Google's own AI researchers are competing internally for access to the company's computing resources.

Let that sink in. Google has a cloud business that rents compute to the world. Google makes its own chips (TPUs). Google has struck compute-sharing deals with Anthropic and Meta. Google still can't satisfy its own internal AI research teams.

This is the compute scarcity problem from the inside. When even the company with arguably the most compute infrastructure on Earth can't satisfy internal demand, you know the AI compute crunch is real.

The Star, citing Bloomberg sources, reports Google researchers "jockey for access" to computing resources. Internal prioritization battles. Resource allocation politics. Queue management for GPU clusters. Sound familiar? It's the same compute hunger that drives external customers to Google Cloud, except now Google's own people are feeling it.

This pairs perfectly with other compute shortage stories we've tracked. Remember Anthropic needing to partner with SpaceX for Colossus access? Remember Uber burning through its entire AI budget faster than expected? Add Google internal competition to the list.

At Google I/O 2026, the company announced new TPU 8t and 8i chips, Gemini 3.5 Flash models, and claimed 900 million Gemini users. All that success requires massive compute infrastructure. And apparently, even Google's own infrastructure isn't enough to meet internal demand.

The broader pattern: AI companies are hitting compute walls faster than they can build new data centers. Training larger models requires exponentially more compute. Running inference at scale requires persistent compute. Building AGI systems will require unprecedented compute.

Google's internal compute competition is a canary in the coal mine. If the company that builds the infrastructure can't feed its own researchers enough computing power, what does that say about the compute requirements for the AI systems we're building?

The AI compute crunch isn't theoretical anymore. It's happening inside Google.