Kosmo provides high-quality, scalable real-world 3D data for Physical AI training, supporting three key stages - pre-training, post-training, and evaluation & deployment - to accelerate model iteration.
Physical AI Needs Scalable, High-Quality 3D Data to Move into the Real World
Internet images and videos lack complete spatial information, generative simulation cannot fully replicate the real world, and manual data collection is costly and time-consuming. Efficient access to high-quality 3D data is becoming a key challenge for robot training and real-world deployment.
Supporting the Full Training Lifecycle to Accelerate Physical AI Deployment
Stage 1: Pre-training
Kosmo generates real-world 3D data at scale, capturing geometry, scale, materials, textures, and lighting. It fills the spatial gaps in 2D images and videos, helping robots build a foundational understanding of the physical world.
Stage 2: Post-training
Kosmo provides high-fidelity 3D scenes for specific tasks and environments, supporting navigation, obstacle avoidance, and manipulation training. It reduces simulation setup costs, narrows the Sim-to-Real Gap, and improves real-world generalization and task success rates.
Stage 3: Evaluation & Deployment
Kosmo enables diverse, configurable 3D test environments with variations in obstacles, layouts, and materials. This expands long-tail coverage, enables scalable automated evaluation, and reduces real-world testing costs.
SUCCESS STORIES
LOREM IPSUM
In a new world full of robotics, a new spatial intelligence emerges and owns the robotic training...
