Expanding Our Data Engine for Physical AI

As AI expands into the physical world through robotics, it faces a significant data bottleneck because physical interaction data cannot be easily scraped like text or images. This "robotics data gap" means existing open-source datasets are far too small to train robust foundation models capable of handling real-world complexity. Scale AI is addressing this challenge with its Data Engine for Physical AI, a solution for collecting and annotating massive, high-quality datasets for robotics companies. The process focuses on providing abundant, diverse, and enriched data that goes beyond raw motion to include semantic details like intent and task structure. By making this high-quality robotics data accessible, the company aims to accelerate breakthroughs for the next generation of Physical AI.