Hawkins spends a lot of verbiage describing the physiological structure of the neocortex. I found this interesting and informative, but as a non-expert on such things, I suspect that this is all well known. In particular, I'm assuming that it's standard and accepted that the neocortex is composed of about 150,000 cortical columns that appear essentially identical, although there does seem to be some specialization of cortical columns according to the area of the brain in which they are located. Likewise, I'm assuming it's well known that each cortical column is composed of several hundred minicolumns, each distinguishable under a microscope, and that each minicolumn contains about a hundred neurons spanning all the neocortical layers. All in all, a single cortical column is composed of about 100,000 neurons and 500,000,000 synapses (connections between neurons). Finally, I'll assume it's well known that cortical columns are sparsely interconnected, with some connections stretching long distances across the neocortex.
As for revelations that he and his research group have come up with, Hawkins presents the notion that cortical columns use something he calls "reference frames" to learn models of objects, and each cortical column can learn hundreds of object models. In short, each cortical column is a semi-autonomous neural network computer that makes guesses and predictions about what's going on in the world according to whatever sensory data it is wired up to receive. Cortical columns as a group then use their sparse interconnectivity to communicate their guesses, coming to a democratic consensus about what is going on in the world and what is likely to happen next. This is the way that the neocortex perceives (is conscious of and draws conclusions about) the surrounding world.
But I found Hawkins' view of consciousness to beg the question; indeed, I wonder if he actually perceives the question. Here is a quote from page 144:
"At some point in the future, we will accept that any system that learns a model of the world, continuously remembers the states of that model, and recalls the remembered states will be conscious. There will be remaining unanswered questions, but consciousness will no longer be talked about as 'the hard problem.' It won’t even be considered a problem."
In fact, as an engineer I would point out that any control system fits this description: It learns a model of the world from its sensors and it continuously remembers/recalls (what's the difference between "remembering" and "recalling"?) the states of that model. Left out of this statement is the additional property that a control system responds in some way to a current or predicted state of the world—that is the whole point of the control system, and this "predicting the next state" phenomenon also seems to be important in Hawkins' theory of the brain, so I'm surprised that he left it out here.
Is the control system of a Boeing 737 MAX, which determines whether the plane remains safely airborne or crashes, a conscious entity?
In fact, even a simple computer program running on a computer satisfies Hawkins' definition of consciousness: The state of its "world" is the collection of values of its program variables, which it continuously "recalls" and "remembers." At each step of its execution, the simple program is making a decision about what to do next based on the values of its program variables. Is a simple computer program conscious?
And where do you draw the boundary that separates one conscious entity from another? The internet, for example, is a worldwide system that has memory in the form of (for example) the routing tables in all the thousands of routers that control the flow of traffic. The state of "the world" from the internet's perspective is the pattern of traffic flowing over the internet's thousands of links, and the collection of thousands of routing tables is the internet's collective memory. As the routers sense the traffic flowing through them, they cooperate in adjusting their tables with the goal of keeping the flow of traffic as efficient as possible. Is the internet conscious? Maybe. Or maybe the individual routers are separately conscious, just like New York City is composed of eight million separately conscious entities but does not have a collective consciousness of its own. (However, some might argue that cities such as New York DO have a collective consciousness of their own; their unique and special "spirit of place." Perhaps a multitude of interacting, separately conscious entities create a meta-consciousness, such as bees that swarm and build a hive or ants that cooperate to construct and operate their anthill home.)
My goal in these comments is not to argue about what is or is not conscious, but simply to point out that I think Hawkins gives short shrift to the philosophical conundra underlying the whole question of consciousness.
This probably lies at the foundation of my overarching criticism of Hawkins' book, although I hesitate to use the word "criticism" because I found the book fascinating and I think what he and other researchers are doing to uncover the mysteries of the brain is very valuable. Anyway, my criticism is that he merely places labels on things without dealing with the real questions—although I freely admit that the "real questions," as I call them, may be unanswerable. Before I read Hawkins' book, indeed, long before I even had any formal education, I knew that the human brain was a processing system with memory. Without sounding disparaging, I hope, I say that all Hawkins has done is put labels on some aspects of its behavior. What difference does it make that a human, such as Hawkins, invents a term, such as "reference frames," to discuss what a cortical column does? Does the individual neuron or synapse "understand" the reference frame concept? Of course not. They are cells that do what they do, regardless of the name plastered on their behavior by a human. The real question is: Regardless of what terms you invent to talk about it, how is it that what they do, that is, how they interact with each other, produces, in the end, this thing called consciousness?
Maybe there is no answer. I just prefer that researchers not pretend to have an answer when they do not.
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Brilliant and tantalizing book but heavy in opinion and falls short in some key areas
Reviewed in the United States on September 21, 2022
A Thousand Brains: A New Theory of Intelligence presents a brilliant and tantalizing theory on how our brains work and what the future may hold. Yet, this book is heavy in opinion and falls short in some key areas.Hawkins starts part 1 of his book with the introduction of the old brain / new brain dichotomy. Brains develop additively, and the mammalian neocortex was added at a much later time in our evolutionary history than our reptilian old brain, which is responsible for our emotions, drives and our survival and reproduction drives.Furthermore, the neocortex and the old brain continuously negotiate for control over the host body — old brain overrides the neocortex by flooding it with hormones (danger, there is a lion over there, run), and the neocortex halts the old brain on its tracks by suppressing its instinctive drives (hold on there, don’t eat that cake, not good for you). I find this framing to be brilliant. Would not it be amazing if the old and new brain could just get along and allow us to just do the right thing all the time? I digress.The neocortex is what endows us (and all mammals) with intelligence. Unlike the old brain, which has specialized components, the neocortex is uniform and comprises of cortical columns. The neocortex learns to navigate the physical (and metaphysical) world by creating models of the world that Hawkins terms reference frames. These reference frames are encoded in the place and grid cells of the cortical columns. This, Hawkins surmises, explains a number of emergent human behavior such as false beliefs and consciousness.Our sense of self is an inevitable consequence of this intelligence and arises from the need to create a model of ourselves and others. I completely agree with Hawkins’ conclusion that this model of self, ie consciousness, exists in all mammals to varying degrees.So far, so wonderful.What I found less satisfying in part 1 is the significance of understanding precisely how our cortical columns store information. How information is stored is likely to be an emergent behavior of the structure and make of the evolved brain without real insight into the design of the overall system or why it works at all. It is akin to trying to figure out how the weights and biases of a neural network store the various aspects of image features in an image classification system. A deeper understanding to me seems to be to figure out what the structure of the neural network is and how it processes information, the number of hidden layers, etc. To truly illustrate the structure of the human brain, one needs to do experiments that are currently beyond our capability. Therein is where part 1 is weakest. This book is short on experiments and large on personal convictions this or that has to be true.Parts 2 and 3 of the book focus on the consequence of intelligence, the prospects for an artificial general intelligence (aka machine intelligence), and how we can ensure human knowledge survives into the distant future.I agree that for now our best hope is to model machine intelligence based on human intelligence. Yet, Hawkins’ claim that machine intelligence could only be developed by modeling the neocortex on a computer to be unfounded. Perhaps more bizarre is Hawkins out of hand dismissal of the risks posed by machine intelligence. Here I have multiple objections. Let’s mention two.First, in apparent self contradiction, Hawkins reminisces our species breaking free from the chains put on us by our selfish genes. Yet, he sees no issue with stating a machine intelligence that is potentially a million times more intelligent than us would never overcome the chains placed on it by its human overlords.Second, Hawkins posits a machine intelligence that is able to learn a million times faster than us would still be unable to overtake us because ultimately all real knowledge requires experimentation that can not be speeded up (for example, rats in a lab). While he acknowledges theoretical fields such as mathematics could be learned thousands or perhaps millions of times faster, he reassures us that there is nothing to worry about. I find this bizarre. Could you imagine arriving at general relativity without calculus? Machine intelligence could discover new branches of mathematics that, far example, could easily unify all of the forces of nature. Perhaps provide a formulation for time travel. What if they discover something about the universe that human intelligence is simply unable to grasp — akin to explaining the photoelectric effect to chimpanzees or worse ants. A better understanding of nature could mean new theories that are unfathomable to human intelligence are discovered more easily by machines. How things would evolve from there would be completely out of our control.The book ends on a chapter about persevering our knowledge. I find the goal of preserving human knowledge to be a meaningless endeavor in and of itself. For one thing, we didn’t invent knowledge, thus there is no reason to “preserve” it as if it would vanish if we were to go extinct. Nature knows how it works. Atoms are the embodiment of the thing we call knowledge. Space, time, and energy know exactly how to behave, and they see no conflict between quantum mechanics and general relativity. My point is there simply is no reason to preserve knowledge were it not ultimately connected to the interests of our old brain: our survival.All in all, I recommend this book for anyone interested in a neat theory about intelligence.
Reviewed in the United States on September 21, 2022
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