Compute access is the ability of an individual, organization, or country to obtain enough computational resources for artificial intelligence (AI) workloads. It has become a basic condition for building, training, fine-tuning, and deploying competitive AI systems. section 11.5
High-end graphics processing units (GPUs) are scarce, while training-scale models, multilingual datasets, and inference application programming interfaces (APIs) are concentrated among a small number of companies and countries. This scarcity raises costs and favors corporations or governments with substantial financial resources. section 11.5 section 11.7
Governments and institutions are responding to limited compute access through several approaches:
- Building national supercomputers and large GPU clusters. section 11.5
- Subsidizing public cloud access and forming international partnerships. section 11.5
- Developing domestic chips and alternative supply routes in response to export controls. section 11.5
- Combining chips, compute, models, data pipelines, and policy frameworks into a national sovereignty stack. section 11.5
Investment does not automatically produce broad access. Infrastructure remains unevenly distributed, and the labor supporting data annotation, content moderation, and data-center maintenance is often overlooked. Unequal compute access may allow a small group of companies and countries to determine who builds and benefits from AI. section 11.5 section 11.7
