World Action Models give robots the ability to simulate consequences before they move
World Action Models, a class of robotics AI architecture, enable robots to simulate physical consequences before acting and can learn from unlabelled everyday video, according to a new survey of roughly 100 papers.
World Action Models tackle a basic weakness of today's robotics AI: current models learn which movements match which camera images, but they don't understand how the world actually changes as a result. A new survey organizes about a hundred papers into two architectural lines and shows a key edge: these models can learn from everyday videos that contain no robot action labels.
That kind of data was nearly useless for traditional robotics AI. The article World Action Models give robots the ability to simulate consequences before they move appeared first on The Decoder.