Hyperdimensional computing theory could change the way AI works

A paper by University of Maryland researchers just published in the journal Science Robotics introduces a new way of combining perception and motor commands using the so-called hyperdimensional computing theory, which could fundamentally alter and improve the basic artificial intelligence (AI) task of sensorimotor representation—how agents like robots translate what they sense into what they do. “Learning Sensorimotor Control with Neuromorphic Sensors: Toward Hyperdimensional Active Perception” was written by Computer Science Ph.D. students Anton Mitrokhin and Peter Sutor, Jr.; Cornelia Fermüller, an associate research scientist with the University of Maryland Institute for Advanced Computer Studies; and Computer Science Professor Yiannis Aloimonos. In the authors’ new computing theory, a robot’s operating system would be based on hyperdimensional binary vectors (HBVs), which exist in a sparse and extremely high-dimensional space.

Source: eng.umd.edu