openHTM is an open-source implementation of the HTM Cortical Learning Algorithms initially proposed by Jeff Hawkins in his book On Intelligence.
Hierarchical temporal memory (HTM) is a machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world.
openHTM is colaborattive effort that arose with wish of a few competent HTM fans of implement and improve the current state of the HTM algoritms discussed on the Numenta white papers.
For more information, do not hesitate in access our wiki.
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