OECD Report: “Countries count AI compute infrastructure as a strategic asset without systematically tracking its distribution, availability and access. A new OECD Working Paper presents a methodology to help fill this gap by tracking and estimating the availability and global physical distribution of public cloud compute for AI.
Compute infrastructure is a foundational input for AI development and deployment, alongside data and algorithms. “AI compute” refers to the specialised hardware and software stacks required to train and run AI models. But as AI systems become more complex, their need for AI compute grows exponentially.
The OECD collaborated with researchers from Oxford University Innovation on this new Working Paper to help operationalise a data collection framework outlined in an earlier OECD paper, A blueprint for building national compute capacity for artificial intelligence…
Housed in data centres, AI compute comprises clusters of specialised semiconductors, or chips, known as AI accelerators. For the most part, three types of providers operate these clusters: government-funded computing facilities, private compute clusters, and public cloud providers (Figure 1).
Public cloud AI compute refers to on-demand services from commercial providers, available to the general public.
Figure 1. Different types of AI compute and focus of this analysis
This paper focuses on public cloud AI compute, which is particularly relevant for policymakers because:
- It is accessible to a wide range of actors, including SMEs, academic institutions, and public agencies.
- It plays a central role in the development and deployment of the generative AI systems quickly diffusing into economies and societies.
- It is more transparent and measurable than private compute clusters or government-funded facilities, which often lack publicly available data…(More)”.
