Avoiding Data Leakage in Synthetic Data Projects
Synthetic data offers vast opportunities for machine learning model training without real-world constraints. Yet, beneath this promise lies the risk of…
Read more →Claru collects and annotates real-world video for robotics and embodied-AI training, drawing on a network of human video collectors across six continents to capture egocentric and environmental footage in manufacturing, kitchen, warehouse, and driving settings. Footage is enriched with depth maps, pose estimation, segmentation masks, and structured metadata, then delivered as custom datasets to AI labs building world models and vision-language-action systems.
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