This book was recommended by a colleague who is both a biologist and a neuromorphic engineer, and I was hoping to get from it some insights on how to build a brain. If I hadn’t come to it with this expectation, I think I would have enjoyed it more… because that’s not what it is. It’s the story of how a science writer switched back to being a scientist and and was able to bring a fresh eye to an old subject. Her new perspective, plus years of work and dedication, have led us to a much better understanding of who we are and why.
This book is not about how our brain works, it’s about how our brain has evolved, and should be of interest to any scientifically-literate reader. Read More …
This book has a bit of a split personality, both in terms of its structure and writing. How much this has to do with the fact that it has two authors I’m not entirely sure, but the effect was to undermine Ramachandran’s credibility in my mind. This the first of his books I have read, and may not have been a good place to start. However, it was weak enough in some ways that it makes me less likely to want to read more.
I should start by saying that I tried with this book. I really did. I tried 231/487 pages of text and 66/100 pages of notes worth. But I couldn’t finish it. Normally I would have written off a book that I disliked much earlier, but I persevered. I was actually pre-disposed to like it: not only had Kurzweil referenced one of my articles in an earlier book (which I actually never read, but was flattered by), but this tome came highly recommended by a friend of mine. Joe said he liked it because it allowed him to stretch his imagination. He found it fun to read the way he finds science fiction fun to read. I found the book unbearable for more-or-less the same reason. 
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. 