Jeff Hawkins' Talk on a Biologically-Inspired Intelligent Architecture

Yesterday, I was particularly impressed by Jeff Hawkins’ dynamic talk on building an intelligent architecture based on the current theory of the neocortex. For those who missed the talk, he proposed a hierarchical temporal memory system with a Bayesian construction that is motivated by the current theory of mammalian neocortex construction. One interesting point of his architecture is that he claims it links both sensory and motor abilities into the units. Most of his talk is covered in his book On Intelligence, but the mathematical construction is not included, as it is a more recent development. I am particularly sorry that we didn’t get a chance to see a demo of his software that did pattern recognition of primitive symbols.

One of his main points was that the individual units of the network are homogeneous initially (regardless of the sensory modality), but it is the connections between the units that lead to specialization of particular regions. This notion of initial homogeneity is very attractive -- it reminds me of blank real estate. Certain areas are used for houses; others are cultivated to grow crops, etc. The regions become specialized, although they are flexible to a degree. I also like the notions of units being tightly integrated with both sensory and motor systems, and having many excess units. These ideas link solidly with those discussed by Minsky in his keynote talk. I’m reserving full judgment on the architecture until I see the details, but I did appreciate his ideas. Many of these ideas have been shared by AI researchers for quite a while, but it is nice to see that the biologically-based approach yields similar conclusions.