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Presented by: Subutai Ahmad, VP of Engineering, Numenta, Inc.
Date: Wednesday, 9 September 2009, 6:30 PM
Location: NASA Exploration Center
NASA Ames Research Center
Moffett Field, CA
Many basic tasks of perception, pattern recognition, and motor control are easy for people but impossible for computers. No existing machine can recognize pictures, understand language, or swiftly navigate through a cluttered room. The gap hints at multiple business opportunities and represents a new industry in intelligent computing. Numenta is creating a technology, called Hierarchical Temporal Memory (HTM), based on the principles of the neocortex. The theory, developed by Jeff Hawkins and described in his book entitled “On Intelligence”, explains how the hierarchical structure of the neocortex builds a model of its world and uses this model for inference and prediction. Numenta has released an open research platform that allows software programmers to apply this theory to a variety of problems. We are have started applying the technology to a number of domains, including vision, text analytics, and web analytics. In this talk Subutai Ahmad will describe the basics of HTM theory, its applications, and Numenta's collaborative business model. He is particularly interested in discussing potential applications of HTM in the data mining field..
About the Speaker
Subutai Ahmad has experience in real time systems, computer vision and learning. Prior to Numenta, as VP Engineering at Yes Video, he helped grow Yes Video from a three-person start-up to a leader in automated digital media authoring. Yes Video's real time video analysis systems have been deployed internationally on a variety of platforms: From large scale distributed clusters to embedded customer set-top boxes. In 1997, he co-founded ePlanet Interactive, a spin-off from Interval Research. ePlanet created the Intel Play Me2Cam, the first computer vision product developed for consumers. Subutai holds an AB in Computer Science from Cornell University, and a PhD in Computer Science from the University of Illinois at Urbana-Champaign

Tags: pattern, perception, recognition, software

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