This article applies scaling laws and unit economics to data collection in robotics, arguing that raw data volume isn’t the key metric. It breaks robot data into observational, interventional, and deployment streams, then shows how novelty and diversity drive model performance per dollar.

South Korea is steering its AI strategy toward “Physical AI,” backing robotics, smart manufacturing, and embodied agents with coordinated industrial policy. Non-Korean speakers face an information blackout on patents, research, and grants, so Fulcrum offers translated, structured intelligence to help foreign investors and companies spot trends and act fast.

The article argues that robot learning, autonomous science, and novel human-machine interfaces are poised to become the next AI frontier by leveraging shared primitives like learned physical dynamics, embodied-action architectures, and rich simulation data. It details how models—from vision-language-action systems and video-based world models to native embodied foundations—are converging to unlock scalable, real-world capabilities across robotics, labs, and neurotech.