Exploring the merging of AI and robotics to create physical intelligence through liquid networks, a new approach inspired by worm neural structures. Liquid networks enable AI to learn continuously after training, fostering adaptable and physics-rooted thinking in machines.
The convergence of AI and robotics will unlock a wonderful new world of possibilities in everyday life, says robotics and AI pioneer Daniela Rus. Diving into the way machines think, she reveals how "liquid networks" — a revolutionary class of AI that mimics the neural processes of simple organisms — could help intelligent machines process information more efficiently and give rise to "physical intelligence" that will enable AI to operate beyond digital confines and engage dynamically in the real world.