Coaxing computers to perform basic acts of perception and robotics, let alone high-level thought, has been difficult. No existing computer can recognize pictures, understand language, or navigate through a cluttered room with anywhere near the facility of a child. Hawkins and his colleagues have developed a model of how the neocortex performs these and other tasks. The theory, call Hierarchical Temporal Memory, explains how the hierarchical structure of the neocortex builds a model of its world and uses this model for inference and prediction. To turn this theory into a useful technology, Hawkins has created a company called Numenta. In this talk, Hawkins will describe the theory, its biological basis, and a software platform created by Numenta that allows anyone to apply this theory to a variety of problems. Part of this theory was described in Hawkins' 2004 book, "On Intelligence".
This talk is by the Chairman of the Redwood Neuroscience Institute and co-founder of Palm Computing and Handspring, and is co-sponsored by Calit2 at UCSD, the Jacobs School's Computer Science and Engineering (CSE)department, and the Institute for Neural Computation (INC).
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