Gen-Xer, software engineer, and lifelong avid reader. Soft spots for sci-fi, fantasy, and history, but I'll read anything good.
If, like me, you're a software developer with an interest in true artificial intelligence, this is a very stimulating book. Hawkins applies his own engineer's mind to an effort to discern and describe the human brain's underlying "cortical algorithm", the means by which intelligence "works". As Hawkins sees it, the neuroscience community has been too focused on the minutae of how neurons function, without giving adequate consideration to the brain's overall learning and decision-making architecture, while the computer science community has been too absorbed in traditional symbolic and procedural computation methods, ignoring insights that might be gleaned from studying the most powerful problem-solving system in nature. Of course, it's untrue that neuroscientists and comp-sci academics aren't interested in each other's disciplines, but the crossover is still a long way from mainstream. For coders working in industry (like me), Hawkin's thoughts may be revelatory.
The author focuses most of his attention on the cortex, the most recently evolved part of the human brain, and the one responsible for many functions of higher intelligence. His speculation is that this system uses the same generalized learning/prediction algorithm throughout, with little difference in how input from vision, hearing, touch, and other senses are processed. All this data is just sequences of patterns that the cortex filters through its multilayered hierarchy, each layer discerning trends in the input from lower layers, and forming models of the world.
This may sound like the traditional AI concept of "neural networks", but Hawkins breaks from that model with his view that the cortex uses massive amounts of feedback from higher, more time-invariant layers (which view the world more abstractly) to lower, more time-variant layers (which deal with more concrete experience), activating many context switches. He sees the cortex as a blank slate upon birth, which follows relatively simple programming to accumulate and categorizes knowledge. As our minds form, we find ourselves experiencing the world less through our sensory input, and more through our pre-formed models. Only when there is conflict between those models and our input sequences, is our conscious attention drawn to our senses.
In terms of biological neuroscience, this is all probably overly simplistic and not completely accurate (Hawkins doesn't give a lot of attention to the older, more instinctive parts of the brain), but if he's even partly right, his ideas have huge implications for artificial intelligence. If much our human intelligence really does boil down to a generalized memory-prediction algorithm -- one that may be complex, but not beyond our understanding -- the effects on the future will be astounding. Even if Hawkins wasn't able to prove his claims, they're fascinating to contemplate, and the next few decades will certainly shed a lot of light on their truth.
If this book speaks to you, consider also reading Marvin Minsky's A Society of Minds, which contains a lot of complementary ideas.