On Intelligence by Jeff Hawkins

I have mixed feelings about what I consider to be 'celebrity' popular science books: being big in Silicon Valley and having something sensible to say about intelligent machines are two different things. In my view, however, Jeff Hawkins has paid his dues and deserves to be taken seriously. Though there is a lot wrong with On Intelligence, I believe Hawkins central theses—that much of what we call intelligence is based on the ability of our neocortex to make predictions, that the function of the neocortex is basic across sensing and actuation, and that this function can be understood in a relatively straightforward way—are all correct. If we're smart, some of us in the machine intelligence and neuroscience communities will take up his challenge to work on filling out this new theory.

However, I fear that this book was as much about promoting Hawkins new company as really pushing neuroscience forwards. If so, it's done a great job.

The book's biggest flaw from my perspective is that it puts up several unncessary barriers for those of us who are serious about the subject. The introductory chapters, for instance, are both too aggressive and too defensive. On the one hand Hawkins slights the last 30 years of research into artificial intelligence and neural networks in a far-too-general way, and on the other hand he talks up his own contribution in a way that made me uncomfortable (maybe I've been based in the UK too long?). Even if he's right, it's not polite (or necessary) to say it in the way he does. I don't know whether the writing style reflected Hawkins personality or not, but he didn't come across as a terribly generous person. This has nothing to do with his theories, of course, but much to do with the digestibility of the book.

I also found that the book was just a little too popular-science to be useful at times. I wanted more examples of real research, more cases where the theory tied into the reality of what other scientists had found. I also wanted more diagrams and fewer handwaving explanations. I felt particularly cheated because at various times we were promised that the sparse bibliography was supplemented by more stuff on the book website. This claim gave the book an undeserved credibility, as there are a total of four additional references on that site (at time of posting), hardly enough to have been worth missing out of the original book bibliography in the first place.

That said, the thesis is consistent with what I know about the brain (I'm no neuroscientist), well thought through, and well explained (if in a way that is not very helpful technically). Essentially, Hawkins argues that as information comes in from the senses it is sorted into increasing levels of complexity as it rises up the layers of neurons that make up the neocortex. So, for instance, lines become shapes then faces then specific people as you move up the hierarchy. At the same time, feedback from above filters the information coming in, so that the lower levels are specifically 'looking' for particular things. So if you see the top half of your friends head and then the rest is revealed, you'll be predisposed to see the bottom half you're expecting.

The next issue is that, if you don't (see what you're expecting), the information will be passed up the hierarchy until some level does expect it: either that, or it forces a new memory to form (Hawkins believes this happens in the hippocampus). Finally, he argues that this hierarchical traffic can go both ways: you can think about what you see (going up), or you can see (and do) what you're thinking about (going down). There's more to it, of course, but that's the gist.

Hawkins is right in that, as far as I know, that no-one has expressed this as an overarching theory in this way before. And I've little doubt that he's basically correct. However, all the pieces of this puzzle have been floating around for a while, and most researchers are only given the opportunity to work on pieces rather than the big picture. I felt a little more modesty wouldn't have hurt.

But perhaps that's the Silicon Valley talking. The book had two things in common with a patent application: a constant discussion of novelty with a distinct lack of details that would make it useful as a point of research for other people's work. A mixture of "insanely great" with "I'd tell you but then I'd have to kill you," if you will. I'm sure Numenta, the company formed to take advantage of the new technology, will do extremely well from this book.

The latter sections vary, and should be treated with care. After convincing us of his neocortex idea, he exposes us to several predjudices about embodied intelligent machines (robots), and  dismisses the problem of interconnections between neurons as hardly worth discussing. (It's a hard problem, and—many believe—a dealbreaker for artificial brains of any size). On the other hand he says some sensible things about consciousness and creativity

Anyone serious about machine intelligence, or brains in general, should read this book. Unfortunately, there is another, better, book out there to be written that really ties together Hawkins thesis with the evidence that supports it and explains his model well enough so that we could all go out and work on it... as he claims he wants to encourage us to do.

Comments

[Paul]

Thanks for the review - this book has been sitting on my desk for a while, just waiting for me to get a kick to start reading it!

I am familiar with Hawkins' theory only in the most general terms - and from the little I know, it seems to share many common elements with the Network Memory theory put forward by Joaquin Fuster (I am of course not suggesting anything more than similarity). This also postulates the hierarchical nature (indeed, Fuster notes that the idea of the brain being organised in hierarchies originates with Lashley and Hayek, among others, in the 70's, so its hardly new), and is backed up by multiple decades of empirical research. I just wondered whether you were familiar with it, and if so, how it compared with Hawkins' theory? If not, theres a ref to a short paper below. It influences my work (cognitive robotics), but then I'm just a student!

Thanks for your posts though, they're all very interesting.

J. M. Fuster, "Network Memory," Trends in Neuroscience, vol. 20, pp. 451-459, 1997.