How to Create a Mind: The Secret of Human Thought Revealed

by Ray Kurzweil

multiverse spawning an evolution of universes with the boring (non-information-bearing) ones dying out.

The mathematics of how Bernoulli’s principle produces wing lift is still not yet fully settled among scientists,

In this book I present a thesis I call the pattern recognition theory of mind (PRTM),

The operating principle of the neocortex is arguably the most important idea in the world, as it is capable of representing all knowledge and skills as well as creating new knowledge.

I will do so by describing how a basic ingenious mechanism for recognizing, remembering, and predicting a pattern, repeated in the neocortex hundreds of millions of times, accounts for the great diversity of our thinking.

“Identity lies not in our genes, but in the connections between our brain cells.”

This is why we invent tools—to compensate for our shortcomings.

Consider that we see what we expect to ___ I’m confident that you were able to complete the above sentence. Had I written out the last word, you would have needed only to glance at it momentarily to confirm that it was what you had expected.

predicting the future and hypothesizing what we will experience. This expectation influences what we actually perceive.

Predicting the future is actually the primary reason tha...

Human beings have only a weak ability to process logic, but a very deep core capability of recognizing patterns.

The neocortex is, therefore, predicting what it expects to encounter. Envisaging the future is one of the primary reasons we have a neocortex.

Recursion, according to Chomsky, is the ability to put together small parts into a larger chunk, and then use that chunk as a part in yet another structure, and to continue this process iteratively. In this way we are able to build the elaborate structures of sentences and paragraphs from a limited set of words.

New memories such as the cat-elephant face are stored in an available pattern recognizer.

Our thoughts are not conceived primarily in the elements of language, although since language also exists as hierarchies of patterns in our neocortex, we can have language-based thoughts. But for the most part, thoughts are represented in these neocortical patterns.

We do not immediately visualize the scene unless we can call upon a lot of other memories that enable us to synthesize a more robust recollection. If we do visualize the scene in that way, we are essentially creating it in our mind from hints at the time of recollection; the memory itself is not stored in the form of images or visualizations.

Relaxing professional taboos turns out to be useful for creative problem solving. I use a mental technique each night in which I think about a particular problem before I go to sleep. This triggers sequences of thoughts that will continue into my dreams. Once I am dreaming, I can think—dream—about solutions to the problem without the burden of the professional restraints I carry during the day.

can then access these dream thoughts in the morning while in an in-between state of dreaming and being awake, sometimes referred to as “lucid dreaming.”

Our dreams are created by our neocortex, and thus their substance can be revealing of the content and connections found there.

The relaxation of the constraints on our thinking that exist while we are awake is also useful in revealing neocortical content that we otherwise would be unable to access directly. It is also reasonable to conclude that the patterns that end up in our dreams represent important matters to us and thereby clues in understanding our unresolved desires and fears.

thousands of years—for a species without a neocortex to learn significant new behaviors (or in the case of plants, other adaptation strategies). The salient survival advantage of the neocortex was that it could learn in a matter of days.

let’s summarize what we can observe from the neuroscience literature and from our own thought experiments.

The capacity of the hippocampus is limited, so its memory is short-term. It will transfer a particular sequence of patterns from its short-term memory to the long-term hierarchical memory of the neocortex by playing this memory sequence to the neocortex over and over again.

This is not the approach that your brain adopts. It basically simplifies the problem by collapsing a lot of equations into a simple trend model, considering the trends of where the ball appears to be in your field of vision and how quickly it is moving within it. It does the same thing with your hand, making essentially linear predictions of the ball’s apparent position in your field of view and that of your hand. The goal, of course, is to make sure they meet at the same point in space and time. If the ball appears to be dropping too quickly and your hand appears to be moving too slowly, your brain will direct your hand to move more quickly, so that the trends will coincide. This “Gordian knot” solution to what would otherwise be an intractable mathematical problem is called basis functions, and they are carried out by the cerebellum, a bean-shaped and appropriately baseballsized region that sits on the brain stem.

If the neocortex is good at solving problems, then what is the main problem we are trying to solve? The problem that evolution has always tried to solve is survival of the species. That translates into the survival of the individual, and each of us uses his or her own neocortex to interpret that in myriad ways. In order to survive, animals need to procure their next meal while at the same time avoiding becoming someone else’s meal. They also need to reproduce. The earliest brains evolved pleasure and fear systems that rewarded the fulfillment of these fundamental needs along with basic behaviors that facilitated them.

It is the job of our neocortex to enable us to be the master of pleasure and fear and not their slave.

In humans the amygdala now depends on perceptions of danger to be transmitted by the neocortex.

Once the amygdala does decide that danger is ahead, an ancient sequence of events occurs. The amygdala signals the pituitary gland to release a hormone called ACTH (adrenocorticotropin). This in turn triggers the stress hormone cortisol from the adrenal glands, which results in more energy being provided to your muscles and nervous system. The adrenal glands also produce adrenaline and noradrenaline, which suppress your digestive, immune, and reproductive systems (figuring that these are not high-priority processes in an emergency). Levels of blood pressure, blood sugar, cholesterol, and fibrinogen (which speeds blood clotting) all rise. Heart rate and respiration go up. Even your pupils dilate so that you have better visual acuity of your enemy or your escape route. This is all very useful if a real danger such as a predator suddenly crosses your path. It is well known that in today’s world, the chronic activation of this fight-or-flight mechanism can lead to permanent health damage in terms of hypertension, high cholesterol levels, and other problems.

It is fair to say that our emotional experiences take place in both the old and the new brains. Thinking takes place in the new brain (the neocortex), but feeling takes place in both.

There is a continual struggle in the human brain as to whether the old or the new brain is in charge. The old brain tries to set the agenda with its control of pleasure and fear experiences, whereas the new brain is continually trying to understand the relatively primitive algorithms of the old brain and seeking to manipulate it to its own agenda.

This is my simple religion. There is no need for temples; no need for complicated philosophy. Our own brain, our own heart is our temple; the philosophy is kindness. —The Dalai Lama

Our emotional thoughts also take place in the neocortex but are influenced by portions of the brain ranging from ancient brain regions such as the amygdala to some evolutionarily recent brain structures such as the spindle neurons, which appear to play a key role in higher-level emotions.

It is important to point out that these cells are not doing rational problem solving, which is why we don’t have rational control over our responses to music or over falling in love. The rest of the brain is heavily engaged, however, in trying to make sense of our mysterious high-level emotions.

Neocortical abilities—for example, the ability of the neocortex to master the signals of fear that the amygdala generates (when presented with disapproval)—play a significant role, as do attributes such as confidence, organizational skills, and the ability to influence others.

The problem is never how to get new, innovative thoughts into your mind, but how to get old ones out. Every mind is a building filled with archaic furniture. Clean out a corner of your mind and creativity will instantly fill it. —Dee Hock

A key aspect of creativity is the process of finding great metaphors—symbols that represent something else. The neocortex is a great metaphor machine, which accounts for why we are a uniquely creative species.

One approach to expand the available neocortex is through the collaboration of multiple humans. This is accomplished routinely via the communication between people gathered in a problem-solving community. Recently there have been efforts to use online collaboration tools to harness the power of real-time collaboration, which have shown success in mathematics and other fields.

Studies of ecstatic religious experiences also show the same physical phenomena; it can be said that the person having such an experience is falling in love with God or whatever spiritual connection on which they are focused.

The ecstatic phase of love leads to the attachment phase and ultimately to a long-term bond. There are chemicals that encourage this process as well, including oxytocin and vasopressin.

From an evolutionary perspective, love itself exists to meet the needs of the neocortex. If we didn’t have a neocortex, then lust would be quite sufficient to guarantee reproduction.

At the far end of the story of love, a loved one becomes a major part of our neocortex. After decades of being together, a virtual other exists in the neocortex such that we can anticipate every step of what our lover will say and do. Our neocortical patterns are filled with the thoughts and patterns that reflect who they are. When we lose that person, we literally lose part of ourselves. This is not just a metaphor—all of the vast pattern recognizers that are filled with the patterns reflecting the person we love suddenly change their nature.

That is not to say that these are not learned behaviors. It is just that these animals did not learn them in a single lifetime—they learned them over thousands of lifetimes. The evolution of animal behavior does constitute a learning process, but it is learning by the species, not by the individual, and the fruits of this learning process are encoded in DNA.

To appreciate the significance of the evolution of the neocortex, consider that it greatly sped up the process of learning (hierarchical knowledge) from thousands of years to months (or less). Even if millions of animals in a particular mammalian species failed to solve a problem (requiring a hierarchy of steps), it required only one to accidentally stumble upon a solution. That new method would then be copied and spread exponentially through the population.

The art moves through time and you can view it at electricsheep. org.

Those processes are specified in the genome. As I will demonstrate in chapter 11, the amount of unique information in the genome (after lossless compression) as applied to the brain is about 25 million bytes, which is equivalent to less than a million lines of code.

Artificial intelligence is all around us—we no longer have our hand on the plug. The simple act of connecting with someone via a text message, e-mail, or cell phone call uses intelligent algorithms to route the information. Almost every product we touch is originally designed in a collaboration between human and artificial intelligence and then built in automated factories.

Let’s use the observations I have discussed above to begin building a brain. We will start by building a pattern recognizer that meets the necessary attributes. Next we’ll make as many copies of the recognizer as we have memory and computational resources to support. Each recognizer computes the probability that its pattern has been recognized. In doing so, it takes into consideration the observed magnitude of each input (in some appropriate continuum) and matches these against the learned size and size variability parameters associated with each input. The recognizer triggers its simulated axon if that computed probability exceeds a threshold. This threshold and the parameters that control the computation of the pattern’s probability are among the parameters we will optimize with a genetic algorithm.

The organization of the brain is far from optimal. Of course it didn’t need to be—it only needed to be good enough to achieve the threshold of being able to create tools that would compensate for its own limitations.

My own view, which is perhaps a subschool of panprotopsychism, is that consciousness is an emergent property of a complex physical system. In this view a dog is also conscious but somewhat less than a human. An ant has some level of consciousness, too, but much less that of a dog. The ant colony, on the other hand, could be considered to have a higher level of consciousness than the individual ant; it is certainly more intelligent than a lone ant. By this reckoning, a computer that is successfully emulating the complexity of a human brain would also have the same emergent consciousness as a human.

Before brains there was no color or sound in the universe, nor was there any flavor or aroma and probably little sense and no feeling or emotion. —Roger W. Sperry