Download (2.6 MB)
This presentation provides an update on biologically inspired computation. In particular, it focuses on two important developments in this area, the DARPA SyNAPSE program (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) and the HTM (Hierarchical Temporal Memory) being developed by Numenta.
The SyNAPSE Program’s ultimate goal is to build a low-power, compact electronic chip combining novel analog circuit design and a neuroscience-inspired architecture that can address a wide range of cognitive abilities: perception, planning, decision making and motor control. According to DARPA program manager Todd Hylton, “Our research progress in this area is unprecedented, No suitable electronic synaptic device that can perform critical functions of a biological brain like spike-timing-dependent plasticity has ever before been demonstrated or even articulated.”
The HTM algorithm is the work of Jeff Hawkins and Dileep George. Jeff (Palm Pilot inventor) founded the Redwood Neuroscience Institute, from which has emerged a synthesis of a number of existing and new ideas of cortical operation. The models have worked so well that he has now spun out a company, Numenta, Inc.
HTMs use a unique combination of the following ideas:
- A hierarchy in space and time to share and transfer learning;
- Slowness of time, which, combined with the hierarchy, enables efficient learning of intermediate levels of the hierarchy;
- Learning of causes by using time continuity and actions;
- Models of attention and specific memories;
- A probabilistic model specified in terms of relations between a hierarchy of causes; and
- Belief Propagation in the hierarchy to use temporal and spatial context for inference.
Dan Hammerstrom received the BS degree from Montana State University, the MS degree from Stanford University, and the PhD degree from the University of Illinois. He was and an Assistant Professor in the Electrical Engineering Department at Cornell University from 1977 to 1980.
In 1980 he joined Intel in Oregon, where he participated in the development and implementation of the iAPX-432, the i960, and iWarp. In 1988 he founded Adaptive Solutions, Inc., which specialized in high performance silicon technology (the CNAPS chip set) for image processing and pattern recognition. He is now a Professor in the Electrical and Computer Engineering Department and Associate Dean for Research in the Maseeh College of Engineering and Computer Science at Portland State University.
Prof. Hammerstrom has joint appointments in the IDE (Information, Computation, and Electronics) Department at Halmstad University, Halmstad, Sweden and in the BioMedical Engineering Department of the Oregon Health & Science University.
Natural computation, Computational intelligence, Signal processing -- Digital techniques, Neural networks (Computer science), System theory
© Copyright the author(s)
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
The purpose of this statement is to help the public understand how this Item may be used. When there is a (non-standard) License or contract that governs re-use of the associated Item, this statement only summarizes the effects of some of its terms. It is not a License, and should not be used to license your Work. To license your own Work, use a License offered at https://creativecommons.org/
Hammerstrom, Dan, "Biologically Inspired Computing: The DARPA SyNAPSE Program & The Hierarchical Temporal Memory" (2010). Systems Science Friday Noon Seminar Series. 36.