A Theory of Cortical Function: Hierarchical Temporal Memory (HTM)

On Sunday, November 4th 2007 the Emergent Epistemology Salon tried an experiment in meeting to discuss videos rather than text. The videos were of talks by Jeff Hawkins regarding his work developing a quantitative and biologically plausible general theory explaining the human cortex. His proposed "cortical algorithm" is named Hierarchical Temporal Memory (HTM). Here are some videos of him talking about this stuff:

A 20-minute chat at TED (which appears to have been given when the actual algorithm was only in the intuition stage) entitle "Brain science is about to fundamentally change computing".


"Prospects and Problems of Cortical Theory" given at UC Berkeley on October 7, 2005 - it's a little over an hour long and gives all the basics of the theory. (Warning: the words don't perfectly sync with the images... it's a pretty good talk but the medium imposes on you a little.)


This talk, "Hierarchical Temporal Memory: Theory and Implementation" is less chatty and spends more time on the theory. There's a pitch at the end for the software tools his startup wrote.


Significant parts of this material are also covered in his 2004 book On Intelligence and he has working algorithms (designed by Dileep George) with publicly accessible code (if you don't mind some non-standard licensing) that you can find by clicking around the website of his startup company, Numenta. The code is implemented in C++ with an eye towards scaling to clusters and has Python bindings.

Our actual discussion of the material was weaker than normal. Mostly we went over the algorithms and talked about whether they might be able able to capture various kinds of cognition and/or concept formation. Part of the problem may have been that we turned out to be a much more literate crowd than a video watching crowd.