Metavalent Stigmergy

How New Default Consensus Realities Instantiate

On Intelligence

I’m presently listening to the Audible.com audio book version of Jeff Hawkins and Sandra Blakeslee’s “On Intelligence.” You can listen to a sample here. Audible.com just may win my subscription, if only I had the time to listen to more audio books. Unfortunately, even given the convenience and affordability of my $49 Sandisk Sansa m240 player (VERY cheap and effective alternative to the much overhype-pods), time is the limiting factor. [Note that the $69 m250 has twice the space (2GB) for only another $20; but was not yet released at the time of my purchase. Ug.]

Irregardless of time and USB-player capacity shortages, I’ll be so presumptuous as to pass along the suggestion to consider Hawkins take on “artificial” version “real” intelligence and his explanations as to why most of the history of the AI’s community’s dogged determination to beat the Turing Test, to create a brain in silicon, has been spent barking up the wrong tree. The only way we’ll ever achieve anything even close to AGI (artificial general intelligence) is to first understand ARI (actual real intelligence). Intentional tautologically repetitive redundancy of the latter TLA, duly noted.

To paraphrase the foregoing blather, “why waste time chasing down an ephemeral artificial intelligence, before we possess even the slightest idea what “real” intelligence is, in the first place?”

In short, Hawkins makes the shockingly obvious assertion that we cannot possibly model the brain in computers until we have a working model of the brain, itself. Toward that end:<blockquote>The Numenta Platform for Intelligent Computing is now available. The first release of the Numenta Platform for Intelligent Computing (NuPIC) is a research release targeted at sophisticated developers for the purpose of education and experimentation. NuPIC implements a hierarchical temporal memory system (HTM) patterned after the human neocortex. We expect NuPIC to be used on problems that, generally speaking, involve identifying patterns in complex data. The ultimate applications likely will include vision systems, robotics, data mining and analysis, and failure analysis and prediction.</blockquote>

BTW, thanks solely to BlogRovr, I also found this Read/Write up on Numenta.

Written on May 12, 2007


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