Jeff Hawkins - Hierarchical Temporal Memory

UBC

How a Theory of the Neocortex May Lead to Truly Intelligent Machines

Jeff Hawkins (Numenta founder) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, March 18, 2010.

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, called 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 progress in applying Hierarchical Temporal Memory to machine learning problems.

Part of this theory was described in Hawkins' 2004 book, On Intelligence. Further information can be found at www.Numenta.com