• Two major advancements toward general-purpose embodied AI agents capable of performing challenging sensorimotor skills have been announced.
  • An artificial visual cortex (VC-1) supports a diverse range of tasks, environments, and embodiments, and a new approach called adaptive (sensorimotor) skill coordination (ASC) achieves near-perfect performance on the task of robotic mobile manipulation.

Key terms:

  • Moravec’s paradox: The thesis that the hardest problems in AI involve sensorimotor skills, not abstract thought or reasoning.
  • Artificial visual cortex (VC-1): A single perception model that supports a diverse range of sensorimotor skills, environments, and embodiments.
  • Ego4D dataset: A groundbreaking dataset created by Meta AI and academic partners, containing videos of people performing everyday tasks.
  • Adaptive (sensorimotor) skill coordination (ASC): A new approach that achieves near-perfect performance on the challenging task of robotic mobile manipulation in physical environments.
  • CortexBench: A curated set of 17 different sensorimotor tasks in simulation, spanning locomotion, navigation, and dexterous and mobile manipulation.


Research Open Source Alignment embodied AI Robots CortexBench Ego4D dataset Robotic Manipulation embodied AI agents Sensorimotor Skills