This book is a very interesting reading for everyone who wants to get a hold of a emerging framework for understanding intelligence, specially as a it emerges from a common algorithm in the neurocortex.

The neuro and cognitive sciences are, by the experts own admission, lacking a common and powerful framework where to try out the large corpus of data that exists and continue to be collected. This book presents a very compelling hypothesis for one. Basically Jeff argues that

The neocortex areas act as one single mechanism.

and that its main function is to recognize patterns and elaborate predictions based on them. Roughly there is a upward flow of information in the neocortex from the diverse senses and a downward flow that fills information and elaborates predictions (this is overly simplified, you should really grab a copy of the book and read the whole argument). Here is a small quote that tries to clarify this point:

Think about information flowing from your eyes, ears, and skin into the neocortex. Each region of the neocortex tries to understand what this information means. Each region tries to understand the input in terms of the sequences it knows. If it does understand the input, it says, "I understand this, it is just part of the object I am already seeing. I won't pass on the details." If a region doesn't understand the current input, it passes it up the hierarchy until some higher region does. However, a pattern that is truly novel will escalate further and further up the hierarchy. Each successively higher region says, "I don't know what this is, I didn't anticipate it, why don't you higher-ups look at it?" The net effect is that when you get to the top of the cortical pyramid, what you have left is information that can't be understood by previous experience. You are left with the part of the input that is truly new and unexpected.

One thing that the reader should be aware is that the book is a new framework proposal, so there is a lot of assumptions going on. That is not to say that Jeff is wrong, but simply that there is not enough compelling evidence for the framework yet. He honestly admits that on chapter 6 (where he presents the kernel of the framework) of the book:

To find and establish a new scientific framework, it is necessary to look for the simplest concepts capable of uniting and explaining what were large quantities of disparate facts. It is an unavoidable consequence of this process that the pendulum swings too far toward simplification. Important details are likely to be ignored, and facts will be misinterpreted. If the framework takes hold, refinements and fixes will inevitably be found showing where the initial proposal went too far, didn't go far enough, or was in error. In this chapter, I have introduced many speculative ideas on how the neocortex works.

Jeff also makes a very interesting analysis of creativity and why it is so mystified:

Isn't creativity some extraordinary quality that requires high intelligence and giftedness? Not really. Creativity can be defined simply as making predictions by analogy, something that occurs everywhere in cortex and something you do continually while awake. Prediction by analogy— creativity— is so pervasive we normally don't notice it.

That lead to some insight on how to improve one's creativity

First, you need to assume up front that there is an answer to what you are trying to solve. Second, you need to let your mind wander. You need to give your brain the time and space to discover the solution.

what mind is and some warnings about the failings of the brain/mind:

I hope I have convinced you that mind is just a label of what the brain does. Our brains are always looking at patterns and making analogies. If correct correlations cannot be found, the brain is more than happy to accept false ones. Pseudoscience, bigotry, faith, and intolerance are often rooted in false analogy.

I did had a problem with his Einstein example:

It had more support cells, called glia, per neuron than average. It showed an unusual pattern of grooves, or sulci, in the parietal lobes— a region thought to be important for mathematical abilities and spatial reasoning. It was also 15 percent wider than most other brains. We may never know why Einstein was as creative and smart as he was, but it is a safe bet that part of his talent derived from genetic factors.

Given the brains plasticity, we cannot be sure that Einstein's brain differences are genetic in nature or the result of his efforts and focus on creative process.

His framework is sound and very promising, and this book is probably a landmark in neuroscience study. I did have a couple of problems with the book though.

He is careful to make a distiction between intelligence and intelligent behavior. That is paramount and of course there is a difference. But his failing in this case is to use The Chinese Room argument to illustrate his point. I think that argument is a fallacy, and I use Jeff's own words to illustrate why it is a fallacy:

There is a single powerful algorithm implemented by every region of cortex. If you connect regions of cortex together in a suitable hierarchy and provide a stream of input, it will learn about its environment.

Here he makes a case where intelligence is rested on a given algorithm. Well, the same could be said about the chinese room, invalidating it's supposed conclusion that computers cannot be intelligent.

The second point I would critisize is his suggestion to read Hubert Dreyfus in the end of the book. For anyone interested in a thoughful analysis on Dreyfus ideas and why they are filled with fallacies I suggest and old work by Seymour Papert.

To summarize, it is a great reading, his framework sounds very promising and a new encompassing algorithm was really needed in the field. Go ahead, it is more than worth the money and time. And if you feel curious, fetch his article explaining in more depth his theories.