Every computer you own spends most of its life doing nothing: so does most of the hardware that runs AI, and that gap is the whole idea we have been working toward. Let us start with size. If a model is small enough to run on hardware people already own, the network running it stops being a handful of enormous data centres and becomes a lot of ordinary machines. Ordinary machines have gaps: the minutes between jobs, the hours nobody booked, the box that is busy for 8 hours of a 24 hour day. Idle time is strange stuff economically. It is the only computing capacity in the world with nobody bidding for it, because it exists whether or not anyone uses it, and it cannot be saved for later. Either something useful happens in that hour or the hour is gone. So the question becomes what is worth doing with it? Our answer is reading. A year of AI research arrives as papers almost nobody has time to connect to each other, and models with no deadline and no boredom can read them, write a page per idea, link every claim back to the paper it came from, and check those pages again when a new paper contradicts an old one. The network answering ordinary requests is real and running today. The reading project is what we intend to point the spare hours at and when it is producing pages we will publish what it got right and where it went wrong.