Ben Cottier is a senior researcher at Epoch AI. He leads the AI Data Centers project. Besides data centers, Ben is interested in AI cost trends and the diffusion of AI capabilities. He previously worked as a software engineer, and has a masters degree in AI from the University of Edinburgh.
Since Colossus 1 launched in August 2024, the record for the largest AI data center has doubled every seven months. Epoch AI's breakdown of single-site compute capacity trends through 2028.
A typical one-gigawatt AI data center requires $38 billion in up-front capital expenditure (CapEx) and $0.9 billion in annual operating expenses (OpEx).
The $500 billion AI data center initiative is projected to exceed 9 gigawatts of capacity by 2029, with 0.3 gigawatts already operational in Abilene and six more US sites under active construction.
Breaking down the share of power going to different components in frontier AI data centers
AI data center campuses are massive infrastructure projects, with the largest covering thousands of acres.
Hyperscalers are planning rapid data center buildouts, with several targeting less than 2 years between the start of construction and reaching 1 gigawatt of operational power.
AI companies are planning a buildout of data centers that will rank among the largest infrastructure projects in history. We examine their power demands, what makes AI data centers special, and what all this means for AI policy and the future of AI.
Compute is not a bottleneck for robotics, while training data is. Frontier-level compute could accelerate progress if data improves.
We project how many notable AI models will exceed training compute thresholds. Model counts rapidly grow from 10 above 1e26 FLOP by 2026, to over 200 by 2030.
