Nix and AI, are we there yet?

AI stacks look like the perfect use-case for Nix: Massively multiplying dependency matrices, double-digit-GB OCI images, tedious, Sisyphean build → push → pull → test loops. In ML/AI dev, "It runs" literally means "It runs … on this machine." So … why aren't more ML teams using Nix? This talk is a field guide to the logistics and sociotechnics of what it takes to make Nix happen in AI. Its point of departure is the following question: "Why do we ship what we ship the way we ship it? Either Nix fits the conveyor belt people already ship on, or ML teams learn a new way to build → ship → deploy software. So what will it take to fit Nix to this conveyor belt?