Pattern Memory, Inc. - About Us
My personal interest in pattern recognition began 30 years ago as an
Engineering and Biophysics graduate student at the University of
Minnesota. My passionate interest was: "Why can't computers see like we
do"? The answer was obvious at that time, computers were slow, cameras
had low resolution, and memory capacity was limited. Thirty years later with
many orders of magnitudes performance increase in all aspects related to
computers - still not much progress compared to what we do naturally
(e.g. visual recognition and continuous speech understanding).
The current barriers relate to the use of complex
mathematics to represent and process patterns. We can be sure that there
is nothing resembling a computer doing mathematical computations in
biological systems. Also, we learn patterns after many examples from
simple building blocks to more complex patterns. Neuroscientists
generally agree that biological systems represent and learn patterns
using a hierarchy of neural oscillations. This is the concept
implemented in PMT. PMT represents patterns by cycles (sometimes called
attractors). These cycles occur naturally with no computation required
other than sampling the pattern. The patterns learned do not need to be
stored, the process never needs to compare one pattern with another, and
there is no quantization of pattern magnitudes -
in stark contrast to conventional mathematical approaches. Similar
patterns produce similar cycles which provides the basis for high speed
identification of similar patterns - solving the most common barrier for
developers in a broad range of applications.
Much of the our previous research was to discover and extract the fundamental simplicity of neural oscillations and implement it for practical benefit. The simplicity of this model accounts for the incomparable performance of PMT. A type of simplicity consistent with the theme of Stephen Wolfram's book, A New Kind of Science "simple programs with simple rules can exhibit complex behavior".
Company and Technology History
Pattern Memory Inc. is only 3 years old however its technology has evolved over many years including two successful company startups, 6 patents (4 expired), millions of dollars in research/development and thousands of successful installations. The first company was PPTVision, using cameras for high speed visual inspection of manufactured products. The second was AutoData Systems, for automatically reading hand printed information from scanned forms. I was the founder of these corporations and contributed in various roles including president, research scientist, and marketing manager.
These early versions of PMT exhibited a small degree of similar pattern clustering, however it was not easily controlled or adjustable. Research in the past 5 years identified parameters to easily adjust the range of similarity without compromising speed and probably represents the most important breakthrough for PMT. This discovery initiated the formation of Pattern Memory Inc. along with additional patents pending on the similarity clustering.
Pattern Memory, Inc. offers PMT as a tool for developers. Focused on one applications barrier: high speed identifications of similar patterns in noisy raw data. PMT basically converts a block of conventional computer memory into pattern memory, (the origin of the company name) allowing developers to use conventional computers to enhance their pattern recognition applications.
Pattern Memory Inc. is a small company and is seeking corporate partners in different market segments. Corporations for which PMT will offer new opportunities to enhance existing or create new products. Corporations that have a vested interest in specific market segments and are motivated to establish a development effort to take their products to the next level.
Much of the our previous research was to discover and extract the fundamental simplicity of neural oscillations and implement it for practical benefit. The simplicity of this model accounts for the incomparable performance of PMT. A type of simplicity consistent with the theme of Stephen Wolfram's book, A New Kind of Science "simple programs with simple rules can exhibit complex behavior".
Company and Technology History
Pattern Memory Inc. is only 3 years old however its technology has evolved over many years including two successful company startups, 6 patents (4 expired), millions of dollars in research/development and thousands of successful installations. The first company was PPTVision, using cameras for high speed visual inspection of manufactured products. The second was AutoData Systems, for automatically reading hand printed information from scanned forms. I was the founder of these corporations and contributed in various roles including president, research scientist, and marketing manager.
These early versions of PMT exhibited a small degree of similar pattern clustering, however it was not easily controlled or adjustable. Research in the past 5 years identified parameters to easily adjust the range of similarity without compromising speed and probably represents the most important breakthrough for PMT. This discovery initiated the formation of Pattern Memory Inc. along with additional patents pending on the similarity clustering.
Pattern Memory, Inc. offers PMT as a tool for developers. Focused on one applications barrier: high speed identifications of similar patterns in noisy raw data. PMT basically converts a block of conventional computer memory into pattern memory, (the origin of the company name) allowing developers to use conventional computers to enhance their pattern recognition applications.
Pattern Memory Inc. is a small company and is seeking corporate partners in different market segments. Corporations for which PMT will offer new opportunities to enhance existing or create new products. Corporations that have a vested interest in specific market segments and are motivated to establish a development effort to take their products to the next level.
From the President and inventor of PMT; Larry Werth