Physically Viable World Models: A Case for Query-Conditioned Embodied AI

World models for embodied AI must be physically viable, representing the physical structure governing action outcomes rather than merely predicting future observations. This paper exposes that existing observation-predictive world models can produce visually plausible but physically wrong rollouts, arguing that embodied AI requires world models that identify the simplest physical abstraction sufficient to answer intervention queries.