Embodied AI Scaling Laws: Coverage Over Volume

New research (GEN-0, EgoScale) argues that scaling in embodied AI is about coverage of environments, objects, and embodiments rather than data volume, challenging the dominant language-model scaling narrative. This paradigm shift has major implications for robot data collection and training pipelines.