What We Do
Building the foundation for AI that understands and interacts with the physical world
Physical World Training Data
High-quality, high-fidelity muti-sensor data. Ego-centric or otherwise, capturing real world dynamics for training embodied systems.
Reinforcement Learning Environments
Purpose-built simulation environments designed for training agents that interact with the physical world.