Training a robot to pick up an object sounds simple until you realize how many separate systems are involved: a vision model to understand the scene, a reasoning model to plan the action, a dynamics model to predict what happens next, and a policy model to generate motor commands. Each component is trained separately, stitched together with glue code, and prone to compounding errors at every handoff. NVIDIA's Cosmos 3, released on June 1, 2026, takes a different approach. It is a single foundation model — what NVIDIA calls an "omnimodal world model" — that handles physical reasoning, world simulation, and action generation within one unified architecture. This post breaks down how it works, what the Mixture-of-Transformers (MoT) design actually does, and where the limits are. The Core Problem: Fragmented Pipelines for Physical AI Most physical AI systems today are pipelines.…