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.

Project Samples

Project Activity

See All Activity >

Follow openHTM

openHTM Web Site

nel_h2
MongoDB Atlas runs apps anywhere Icon
MongoDB Atlas runs apps anywhere

Deploy in 115+ regions with the modern database for every enterprise.

MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of openHTM!

Additional Project Details

Registered

2013-01-31