Generate exponentially large amounts of synthetic motion trajectories for robot manipulation from just a few human demonstrations.
Generates physics-aware video world states from text and image prompts for physical AI development.
Generates future frames of a physics-aware world state based on simply an image or short video prompt for physical AI development.
Simulate, test, and optimize physical AI and robotic fleets at scale in industrial digital twins before real-world deployment.
Generates physics-aware video world states from text and image prompts for physical AI development.
Generates future frames of a physics-aware world state based on simply an image or short video prompt for physical AI development.
Expressive and engaging English voices for Q&A assistants, brand ambassadors, and service robots
ProteinMPNN is a deep learning model for predicting amino acid sequences for protein backbones.