Generates physics-aware video world states for physical AI development using text prompts and multiple spatial control inputs derived from real-world data or simulation.
Generalist model to generate future world state as videos from text and image prompts to create synthetic training data for robots and autonomous vehicles.
End-to-end autonomous driving stack integrating perception, prediction, and planning with sparse scene representations for efficiency and safety.
