Modern progress in AI systems has been driven and enabled mainly by acquiring more computational resources. AI systems rely on computation-intensive training runs — they require massive amounts of compute.

Learning about the compute requirements for training existing AI systems and their capabilities allows us to get a more nuanced understanding and take appropriate action within the technical and governance domain to enable a safe development of potential transformative AI systems.

To understand the role of compute, I decided to (a) do a literature review, (b) update existing work with new data, (c) investigate the role of compute for timelines, and lastly, (d) explore concepts to enhance our analysis and forecasting efforts.

In this sequence, I present a brief analysis of AI systems’ compute requirements and capabilities, explore compute’s role for transformative AI timelines, and lastly, discuss the compute governance domain.