Of all the topics that one could write about, why write about a fairly obscure new machine learning technology known as hierarchical temporal memory (HTM)? The fact is, I have been interested in the idea of intelligent machines since I was a kid back in the 1980's. The idea of robots and computers that could think for themselves was fascinating to me. At the time, it seemed as though the idea of artificial intelligence was dead. I lost interest in technology for a very long time (roughly ten years from the early 90's until late 2004). One night, with nothing better to do, I went on the internet, and went looking for tech websites. I found that times had changed, somewhat. Robots were still lumbering zombies, but it still seemed as though significant progress was being made with getting computers to think for themselves.
At that time, I also heard about a new book by Jeff Hawkins (famous for the creation of the Palmpilot and Treo) called "On Intelligence." I did not read the book at the time (I was in the middle of law school with a wife and new baby so pleasure reading was not high on my list at that time). Yet, I heard that the book, a theory of brain intelligence and how computers could be built on similar principles, was well received even by many neuroscientists. I wondered if, perhaps, Mr. Hawkins was on to something better than the many failed AI experiments of the past. Hawkins himself alluded in his book to many of these failures dating back to the beginning of the computer age. About a year ago, I saw someone on a website mention Numenta, Hawkins' new company that was created to replicate in computers his brain theory set forth in "On Intelligence." This individual essentially said that Numenta had failed to deliver on Hawkins' promises. I decided to go back and read "On Intelligence."
I now have a wife and three small children, but my daily train commute allows for plenty of pleasure reading. Early this year, I finally sat down and read the book, and was blown away by it. In my mind, Hawkins brilliantly explained why the field of artificial intelligence has largely failed in its goal of implementing any degree of general intelligence in computers. Further, he made a plausible case that it wouldn't be terribly difficult to begin to implement his theory into hardware and software. I wondered whether the person mentioned above was correct in his assessment that Numenta was largely a failure. I found quite the contrary. Numenta has made steady progress since its founding in early 2005 toward its ultimate goal of creating a brain-like computer. I will try to discuss some of this progress here in this blog.
I want to make a disclaimer. I am not an engineer, computer scientist, or neuroscientist by trade, so this blog will definitely be less technical than what you might see from other tech blogs. While I am interested at some level in the nuts and bolts of Numenta's technology, my knowledge certainly does not extend to the mathematical theory behind HTM.
My blog is meant simply to be a repository for any news about HTM and Numenta. There are many interesting news articles and videos on the topic dating back several years, but they are spread across the entire web. Numenta's website is a good start, but there is so much more out there.