I watched the whole thing and like the philosophy of the approach. Unfortunately there isn't a single demonstration of the software, nor a direct comparison between the software and other machine learning algorithms.<p>At one point Hawkins even says he's not going to waste time by talking about specific data sets they've applied the software to because there are too many! Then pick one! Pick the best!
Hawkins has also given some great talks on starting a company. He has an interesting take on entrepreneurship in that he views it as a tool of last resort to be used when you can't get something made within an existing organization:<p><a href="http://ecorner.stanford.edu/author/jeff_hawkins" rel="nofollow">http://ecorner.stanford.edu/author/jeff_hawkins</a>
This was really fun to watch. I read On Intelligence, by Jeff Hawkins several years ago and wondered when or if Numenta was ever going to get off the ground. It looks like they're getting close to their goal. Yeah, there were no real demonstrations, but this looks a lot more promising than previous AI/Neural Network stuff.
Have they compared their algorithm against standard well-known algorithms for the tasks they claim to solve? Last time I checked they still hadn't done that, or at least hadn't reported any such results. Without that, they're not worth anyone's time.
Very interesting video, these concepts seemed to have progressed a lot since last I checked in on them.<p>That being said, I'm finding it very difficult to find any objective comparisons of these algorithms to other, more mainstream machine learning techniques. In the talk, he gave the impression that there was a tremendous amount of data to back up these claims, and that he just didn't have time to present it all. I went through many of the white papers available on the Numenta website. Many were just overall outlines of the approach. A few of them demonstrate tasks for which some form of learning is occurring, however, it was hard for me to know, in the absence of objective comparisons to other techniques, just how good the results really are.<p>So far, the only objective comparison I could find involved handwritten character recognition, and that was against what appeared to be a standard feed forward neural network with only a single hidden layer. Not exactly state of the art.. why not compare to SVMs, convolutional NNs, deep belief nets, etc..?<p>So I am at this point hopeful, but fairly skeptical. If nothing else these are some inspiring ideas.
Coincidentally, I just finished On Intelligence, and I found it pretty mind-blowing. If you're interested in learning and the brain, read it! You can also read about the HTM algorithm they are working on here: <a href="http://www.numenta.com/htm-overview/education.php" rel="nofollow">http://www.numenta.com/htm-overview/education.php</a> According to the first paper, there's enough detail there for you to implement the algorithm yourself. Cool!
Or a YouTube video of a presentation from earlier this year: <a href="http://www.youtube.com/watch?v=TDzr0_fbnVk#" rel="nofollow">http://www.youtube.com/watch?v=TDzr0_fbnVk#</a>.<p>Flash video is sadly unfriendly to my iPad (where I am now)
Jeff Hawkins began a few decades ago by criticizing all those neural-net researchers who were all promises and no results and (surprise!) he's become one of them now.