The hardware chapter of Stanford's annual AI Index report: data on AI chip performance, costs, and who controls the computing power behind modern AI.
Why I recommend it: Free to download. It's the institute's own synthesis, and some compute and investment figures come from data supplied by the companies being measured — the broad picture is reliable, the fine print less so.
The Tony Blair Institute's hub explaining compute — the hardware, software and infrastructure stack that stores, processes and moves data at scale — and arguing that access to it now determines which countries and public services can use AI at all. Collects its work on infrastructure, digital skills, regulation and international collaboration.
Why I recommend it: Useful for the plain definition and for seeing how governments are being asked to think about this. It is advocacy, not neutral analysis: the Institute campaigns for rapid state adoption of technology and is funded in part by technology donors, so it rarely dwells on the land, water and electricity costs that the same build-out imposes locally. Read it alongside the data-center cases on our impacts page.
Trillions in compute commitments come due in 2027–2028. The Reset Wall reveals how the AI boom breaks, and when.
From the site: Trillions in compute commitments come due in 2027–2028. The Reset Wall reveals how the AI boom breaks, and when.
Why I recommend it: A clear-eyed look at where the AI build-out may hit a financing and infrastructure wall — useful context for anyone advising job seekers or founders betting on the sector.
