Using Numenta Vision system for decision space based ai

From the Cognimem chip pdf...
http://www.recognetics.com/download/CogniMem%20Reference%20Guide.pdf
Pattern recognition starts with the definition of a decision space suitable to discriminate different
categories of objects. A decision space can be represented by a graph with N dimensions where N is the
number of attributes or measurements considered to represent the objects. The N attributes compose a
feature vector or signature which can be plotted in the graph. After a significant number of samples has
been entered, the decision space starts taking shape and hopefully revealing clusters of objects
corresponding to different categories. If this is not the case, the decision space might not turn very useful,
and other features should be considered to build a space in which categories are noticeable.

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• neuron
• brain
• Jeff
• Hawkins