Book Review: “A Thousand Brains” by Jeff Hawkins
I read this book when it came out a few weeks ago and enjoyed it, and share a lot of similar criticism as the author of this post. To restate briefly, the book&#x27;s main thesis is:<p>- The neocortex is a thin layer of neurons around the old brain. This is the wrinkled outer layer of the brain you think of when you see a picture of a brain.<p>- The neocortex is made of 1MM cortical columns. Cortical columns are clusters of neurons about the size of a grain of rice. They contain a few thousand neurons each.<p>- Cortical columns form a sort of fundamental learning unit of the brain. Each column is learning a model of the world. All cortical columns are running essentially the same algorithm, they are just hooked up to different inputs.<p>- Columns are sparsely connected to other columns. Columns take into account the predictions of other columns when making their own predictions. So the overall brain will tend to converge on a coherent view of the world after enough time steps.<p>- Columns learn to model the world via reference frames. Reference frames are a very general concept that take a while to wrap your head around what Hawkins means. A physical example would be a model of my body from the reference frame of my head. Or a model of my neighborhood from the reference frame of my house. But reference frames can also be non-physical, e.g. a model of economics from a reference frame in supply&#x2F;demand theory.<p>- Thus, very generally, you can think of the neocortex -- made up of this cortical column circuit -- as a thing that is learning a map of the world. It can answer questions like &quot;if I go north from my house, how long until I encounter a cafe?&quot; and &quot;if I don&#x27;t mow the lawn today, how will my wife react?&quot;.<p>- The old &quot;reptilian&quot; brain uses this map of the world to make us function as humans. Old reptilian brain says &quot;I want food, find me food&quot;. New neocortex says &quot;If you walk to the refrigerator, open the door, take out the bread and cheese, put them in the toaster, you will have a nice cheese sandwich&quot;.<p>I, like the author of this post, find Hawkins&#x27; handwaving of machine intelligence risks unconvincing. Hawkins&#x27; basic argument is &quot;the neocortex is just a very fancy map, and maps do not have motivations&quot;. I think he neglects the possibility that it might be incredibly simple to add a driver program that uses that map in bad ways.<p>He also rejects the notion of intelligence explosion on the grounds that while a silicon cortical column may be 10000x faster than a biological one, it still has to interact with the physical world to gather data, and it can&#x27;t do that 10000x faster due to various physical limits. I find this convincing in some fields, but totally dubious in others. I think Hawkins&#x27; underestimates the amount of new knowledge that could be derived by a superintelligence doing superhuman correlation of the results of already-performed scientific experiments. It does not seem completely impossible to me that a superintelligence might analyze all of the experiments performed in the particle colliders of the world and generate a &quot;theory of everything&quot; based on the data we have so far. It&#x27;s possible that we have all of the pieces and just haven&#x27;t put them together yet.<p>Overall, though, I really enjoyed the book and would recommend it to anyone who is interested in ML.