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.
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.