The Singularity Is Nearer: When We Merge with AI

by Ray Kurzweil

Eventually nanotechnology will enable these trends to culminate in directly expanding our brains with layers of virtual neurons in the cloud. In this way we will merge with AI and augment ourselves with millions of times the computational power that our biology gave us. This will expand our intelligence and consciousness so profoundly that it’s difficult to comprehend. This event is what I mean by the Singularity.

With brains, we added roughly one cubic inch of brain matter every 100,000 years, whereas with digital computation we are doubling price-performance about every sixteen months.

In the Fifth Epoch, we will directly merge biological human cognition with the speed and power of our digital technology.

The Sixth Epoch is where our intelligence spreads throughout the universe, turning ordinary matter into computronium, which is matter organized at the ultimate density of computation.

A key capability in the 2030s will be to connect the upper ranges of our neocortices to the cloud, which will directly extend our thinking. In this way, rather than AI being a competitor, it will become an extension of ourselves. By the time this happens, the nonbiological portions of our minds will provide thousands of times more cognitive capacity than the biological parts.

Minsky taught me that there are two techniques for creating automated solutions to problems: the symbolic approach and the connectionist approach.

Experiments have shown that neural nets can learn their subject matter even with unreliable teachers. If the training data is labeled correctly only 60 percent of the time, a neural net can still learn its lessons with an accuracy well over 90 percent. Under some conditions, even smaller proportions of accurate labels can be used effectively.

Connectionism is thus a bit like the flying-machine inventions of Leonardo da Vinci—they were prescient ideas, but not workable until lighter and stronger materials could be developed.[29] Once the hardware caught up, vast connectionism, such as one-hundred-layer networks, became feasible. As a result, such systems were able to solve problems that had never been tackled before. This is the paradigm driving all the most spectacular advances of the past several years.

our multilayered neocortices give us more capacity for abstract thought than creatures with simpler cortices. And when humans are able to connect our neocortices directly to cloud-based computation, we’ll unlock the potential for even more abstract thought than our organic brains can currently support on their own.

similarities in neocortical firing patterns promote analogical thinking. The pattern that represents lowering the position of your hand will be related to the pattern that represents lowering the pitch of your voice—and even to metaphorical lowerings, like the concepts for a falling temperature or a declining empire in history. Thus, we can form a pattern from learning a concept in one domain and then apply it to a completely different domain. The neocortex’s ability to draw analogies between disparate fields is responsible for many of the key intellectual leaps throughout history.

One of the most promising applications of hyperdimensional language processing is a class of AI systems called transformers. These are deep-learning models that use a mechanism called “attention” to focus their computational power on the most relevant parts of their input data—in much the same way that the human neocortex lets us direct our own attention toward the information most vital to our thinking. Transformers are trained on massive amounts of text, which they encode as “tokens”—usually a combination of parts of words, words, and strings of words. The model then uses a very large number of “parameters” (billions to trillions, as I write this) to classify each of the tokens. You can think of parameters as factors that can be used to make predictions about something.

Zero-shot learning is the very essence of analogical thinking and intelligence itself. It demonstrates that the AI isn’t just parroting back what we feed it. It is truly learning concepts with the ability to creatively apply them to novel problems.

statistical sampling of individual cells would make their states seem essentially random, but we can see that each cell’s state results deterministically from the previous step—and the resulting macro image shows a mix of regular and irregular behavior. This demonstrates a property called emergence.[26] In essence, emergence is very simple things, collectively, giving rise to much more complex things. The fractal structures in nature, such as the gnarled path of each growing tree limb, the striped coats of zebras and tigers, the shells of mollusks, and countless other features in biology, all exhibit a class 4 type of coding.[27] We inhabit a world that is deeply affected by the kind of patterning found in such cellular automata—a very simple algorithm producing highly complex behavior straddling the boundary between order and chaos.

This opens the door to “compatibilism”—the view that a deterministic world can still be a world with free will.[31] We can make free decisions (that is, ones not caused by something else, like another person), even though our decisions are determined by underlying laws of reality. A determined world means that we could theoretically look either forward or backward in time, since everything is determined in either direction. But under rule 110–style rules, the only way we can perfectly see forward is through all the steps actually unfolding. And so, viewed through the lens of panprotopsychism, the emergent processes in our brains aren’t controlling us; they are us. We arise from deeper forces, but our choices cannot be known in advance—so we have free will as long as the processes that give rise to our consciousness are able to be expressed through our actions in the world.[32]

These and other experiments involving both hemispheres of the brain suggest that a normal person may actually have two brain units capable of independent decision-making, which nonetheless both fall within one conscious identity. Each will think that the decisions are its own, and since the two brains are closely commingled, it will seem that way to both of them.

My mentor Marvin Minsky was prescient in seeing the brain not as a single united decision-making machine but rather as a complex network of neural machinery whose individual parts may favor different options when we consider a decision. Minsky described our brains as a “society of mind” (the title of his second book) containing various simpler processes that reflect many different perspectives.

what keeps your identity intact is information and function—not any particular structure or material.

For years I have often gazed at the beautiful Charles River near my home. If I look at the Charles today, I tend to think of it as the same body of water that it was a day ago, or a decade ago, when I commented on the river’s continuity in How to Create a Mind. This is because even though all of the water molecules passing through a given slice of it are completely different every few milliseconds, those molecules act in a consistent pattern that defines the course of the river. It is the same for minds. As we place nonbiological systems into our bodies and brains, the continuity of our information patterns will make each of us feel like the person we are today—except for the fact that our perceptions may be better or our cognition smarter.

mental tasks that seem hard to humans—like square-rooting large numbers and remembering large amounts of information—are comparatively easy for computers. Conversely, mental tasks that are effortless to humans—like recognizing a face or keeping one’s balance while walking—are much more difficult for AI. The likely reason is that these latter functions have evolved over tens or hundreds of millions of years and run in the backgrounds of our brains, whereas “higher” cognition is powered by the neocortex, which is the center of our consciousness and which didn’t reach its roughly modern form until several hundred thousand years ago.[85]

Who Can I Be? Our questions of identity are tightly interconnected with issues of consciousness, free will, and determinism. In light of these ideas, I could say that this particular person—Ray Kurzweil—is both the result of incredibly precise prior conditions and the product of my own choices. As a self-modifying information pattern, I have certainly shaped myself through decisions throughout my life about whom to interact with, what to read, and where to go. Yet despite my share of responsibility for who I am, my self-actualization is limited by many factors outside my control. My biological brain evolved for a very different kind of prehistoric life and predisposes me to habits that I would rather not have. It cannot learn fast enough or remember well enough to know all the things I would like to know. I can’t reprogram it to free me of fears, traumas, and doubts that I know are preventing me from achieving what I would like to achieve. And my brain sits in a body that is gradually aging—although I work hard to slow this process—and is biologically programmed to eventually destroy the information pattern that is Ray Kurzweil. The promise of the Singularity is to free us all from those limitations. For thousands of years, humans have gradually been gaining greater control over who we can become. Medicine has enabled us to overcome injuries and disabilities. Cosmetics have allowed us to shape our appearance to our personal tastes. Many people use legal or illegal drugs to...

Day-by-day positive trends have been progressing for years and, at slower rates, for decades and centuries.

Another evolutionary adaptation is the well-documented psychological bias toward remembering the past as being better than it actually was. Memories of pain and distress fade more quickly than positive memories.

When we look back on our past experiences, the pain, stresses, and challenges have faded, and we tend to remember the more positive aspects of life. Conversely, when we think of the present, we are highly cognizant of our current worries and difficulties. This leads to the often false impression that the past was better than the present, despite overwhelming objective evidence to the contrary.

we are conditioned to expect entropy—the idea that the default state of the world is things falling apart and getting worse.

Pessimism can be a self-fulfilling prophecy.”

Yet my converse observation is: “Optimism is not an idle speculation on the future but rather a self-fulfilling prophecy.” Belief that a better world is genuinely possible is a powerful motivator to work hard on creating it.

globalization has made available a much wider selection of products and services than people could access in 1929. It is difficult to assign a monetary value to the dizzying variety available to modern consumers relative to past decades. Even if you can have only Chinese food or Mexican food at a given meal, you would probably rather have the choice instead of just one option. This variety has affected countless areas of life. Instead of having three television stations to choose from, we have hundreds. Instead of a few fruits at the supermarket, we get out-of-season fruit flown in from the opposite hemisphere. Instead of a few thousand books at a bookstore, we can choose from among millions on Amazon. These choices help everyone satisfy their preferences better, but they are especially important to people who have unusual tastes and interests. Thanks to the globalized economy made possible by information technology, if you love collecting old kaleidoscopes, you can go on eBay and buy them from anywhere in the world. And if you’re a kid interested in math and science, you can watch hours of educational shows that nurture your curiosity instead of being stuck watching Gunsmoke around your family’s single TV set, as was common back in my generation. The maturation of 3D printing and eventually nanotechnology will exponentially accelerate this diversification of our choices in the coming decades.

Where humans once only identified with small groups, communication technology (books, then radio and television, then computers and the internet) enabled us to exchange ideas with an ever wider sphere of people and discover what we have in common. The ability to watch gripping video of disasters in distant lands can lead to historical myopia, but it also powerfully harnesses our natural empathy and extends our moral concern across our whole species.

Further, the more wealth grows and poverty declines, the greater incentives people have for cooperation, and the more zero-sum struggles for limited resources are alleviated. Many of us have a deeply ingrained tendency to view the struggle for scarce resources as an unavoidable cause of violence and as an inherent part of human nature.

Almost every aspect of our technological civilization requires energy, but our longtime reliance on fossil fuels is unsustainable for two main reasons. Most obviously, it creates toxic pollution and greenhouse gas emissions, but it also limits us to scarce resources that are becoming more expensive to extract even as humanity’s need for cheap energy is soaring.

Machines Achieving Record-Setting Price-Performance

Certainly manufacturing and transporting these types of resources has grown more efficient thanks to ever-improving hardware and software, but we are about to enter an era in which goods like food and clothing are not simply being made more economical by information technology, but are themselves actually becoming information technologies—as resource and production costs fall as a result of automation and artificial intelligence taking on dominant roles in production.[210] Such goods will, therefore, be subject to the same high deflation rates that we see for other information technologies.

Meat taken from animal carcasses has several major disadvantages: it inflicts suffering on innocent creatures, it is often unhealthy for humans, and it causes severe environmental impacts through both toxic pollution and carbon emissions.

It will also force us to reconsider why we do what we do.

Biological life is suboptimal because evolution is a collection of random processes optimized by natural selection. Thus, as evolution has “explored” the range of possible genetic traits, it has depended heavily on chance and the influence of particular environmental factors. Also, the fact that this process is gradual means that evolution can achieve a design only if all the intermediate steps toward a given feature also lead creatures to be successful in their environments. So there are surely some potential traits that would be very useful but that are inaccessible because the incremental steps needed to build them would be evolutionarily unfit. By contrast, applying intelligence (human or artificial) to biology will allow us to systematically explore the full range of genetic possibilities in search of those traits that are optimal—that is, most beneficial. This includes those inaccessible to normal evolution.

Exponentially improving information technology is a rising tide that lifts all the boats of the human condition. And we are now about to enter the period when this tide surges upward as never before. The key to this is artificial intelligence, which is now allowing us to turn many kinds of linearly advancing technology into exponential information technology—from agriculture and medicine to manufacturing and land use. This force is what will make life itself exponentially better in the time ahead.

So the problem is that GDP naturally counts today’s $900 chip as equivalent to one produced over two decades ago, even though the current one is more than 72,000 times more powerful for the same price. Thus, nominal wealth and income increases over the past few decades do not properly reflect the massive lifestyle advantages enabled by new technology. This distorts the interpretation of economic data and creates misleading perceptions, such as apparently slow or even stagnant wage growth. Even if your nominal wages stayed flat over the past two decades, you can now buy many thousands of times more computing power with them.[96]

Even though such services are free to consumers, we can approximate people’s willingness to pay for them (also known as consumer surplus) by looking at their choices.[98] For example, if you could earn $20 by mowing a neighbor’s lawn but choose to spend that time on TikTok instead, we can say that TikTok is giving you at least $20 of value. As Tim Worstall estimated in Forbes in 2015, Facebook’s US-based revenue was about $8 billion, which would thus be its official contribution to GDP.[99] But if you value the amount of time people spend on Facebook even at minimum wage, the true benefit to consumers was around $230 billion.[100]

Valuing social media use at minimum wage is hardly a perfect measure, since, for example, it’s more practical to surf Facebook while waiting in line for coffee than to use those few minutes doing remote freelance work. But as a general approximation, it reveals that people place enormous value on social media usage, yet only a small fraction of that value is visible to economists as revenue. Wikipedia is an even more extreme example: its official contribution to GDP is basically zero. The same analysis applies to countless web- and app-based services.

These effects go far beyond areas that are obviously “technology.” Technological change has enabled countless other benefits that don’t show up in GDP—from less pollution and safer living conditions to expanded opportunities for learning and entertainment. That said, these changes haven’t affected all areas of the economy evenly. For example, despite dramatic deflation in computing prices, health care has been getting more expensive faster than overall inflation—so someone who needs a lot of medical treatments may not be comforted much by how much cheaper GPU cycles are getting.[104] The good news, though, is that artificial intelligence and technological convergence will turn more and more kinds of goods and services into information technologies during the 2020s and 2030s—allowing them to benefit from the kinds of exponential trends that have already brought such radical deflation to the digital realm.

But a key issue remains: What happens between now and then? In a personal dialogue I had with Daniel Kahneman, he concurred with my view that information technology has been growing and will continue to grow exponentially in price-performance and capacity and that this will ultimately encompass physical products such as clothing and food. He also agreed that we are headed toward an era of abundance that will meet our physical needs and that the primary struggle will then be to satisfy higher levels of Maslow’s hierarchy. However, he envisioned a protracted period of conflict, and even violence, between now and then. He pointed out that there will invariably be winners and losers as automation continues its impact. A driver losing his job is not going to be satisfied by the promise of humanity moving up the hierarchy of life, because he as an individual may not, in fact, be able to make that transition.

One of the great challenges of adapting to technological changes is that they tend to bring diffuse benefits to a large population, but concentrated harms to a small group. For example, autonomous vehicles will bring massive benefits to society—from saved lives to lower pollution, eased congestion, more free time, and lower transportation costs. All of the United States’ population—projected to be almost 400 million by 2050—will share to varying degrees in these improvements.[157] Depending on which assumptions are used, estimates of the total potential benefits are valued at between $642 billion and $7 trillion per year.[158] Suffice it to say, it’s an enormous number. Yet the benefits to any single person are unlikely to totally transform their life. And even though we know statistically that tens of thousands of lives will be spared annually, there’ll be no way to identify which individual people avoid death each year.[159] By contrast, the harms from autonomous vehicles will be mainly confined to the several million people who work as drivers and will lose their livelihoods. These people will be specifically identifiable, and the disruption to their lives may be quite serious. When someone is in this position, it’s not enough to know that the overall benefits to society outweigh their individual suffering. They’ll need policies in place that help reduce their economic pain and ease their transition to something else that provides meaning, dignity, and economic security.

One phenomenon that supports Kahneman’s concern is that popular fears are typically far worse than the reality, as I discussed previously. Losing your job when you already feel like everything in society is getting worse is a good formula for alienation. Kahneman and I agree that a lot of the polarization we see in politics today is the product of automation, both actual and anticipated, rather than coming from traditional political issues such as immigration.[160] If you have a high level of anxiety...

The true value of products, then, would lie in the information they contain—in essence, all the innovation that has gone into them, from creative ideas to lines of software code that control their manufacture. This has already taken place for goods that can be digitized. Think of e-books. When books were first invented, they had to be copied by hand, so labor was a massive component of their value. With the advent of the printing press, physical materials like paper, binding, and ink took on the dominant share of the price. But with e-books, the costs of energy and computation to copy, store, and transmit a book are effectively zero. What you’re paying for is creative assembly of information into something worth reading (and often some ancillary factors, like marketing). One way to see this difference for yourself is by browsing Amazon for blank journals and then browsing for hardcover novels with roughly similar bindings. If you look only at the prices, you won’t be immediately and consistently able to tell which are which. On the other hand, e-book novels are usually priced at several dollars, while the idea of paying any money at all for a blank e-book is laughable. This is what it means for a product’s value to be entirely information.

The idea that wealthy elites would simply hoard this new abundance is grounded in a misunderstanding. When goods are truly abundant, hoarding them is pointless. Nobody bottles up air for themselves, because it’s easy to get and there’s enough for everyone. Similarly, when other people use Wikipedia, it doesn’t make any of the information less available to you. The next step is simply extending that kind of abundance into the world of material goods.

A deeper virtual neocortex will give us the ability to think thoughts more complex and abstract than we can currently comprehend. As a dimly suggestive example, imagine being able to clearly and intuitively visualize and reason about ten-dimensional shapes.

In the 2040s and 2050s, we will rebuild our bodies and brains to go vastly beyond what our biology is capable of, including their backup and survival. As nanotechnology takes off, we will be able to produce an optimized body at will: we’ll be able to run much faster and longer, swim and breathe under the ocean like fish, and even give ourselves working wings if we want them. We will think millions of times faster, but most importantly, we will not be dependent on the survival of any of our bodies for our selves to survive.

Cassandra: But people need deeper purpose. If AIs can do everything that humans can do in every intellectual sphere, and do it far better than the best humans and at far greater speeds, what is there for humans to do that will give us meaning? Ray: Well, that’s why we want to merge with the intelligence we are creating. The AIs will become part of us, and thus it is we who will be doing those things.

conflict can be minimized when people feel they have purpose. And extending our neocortex into the cloud will be critical to humans keeping a sense of purpose. Just as growing more neocortex hundreds of thousands of years ago elevated our primate ancestors from survival instinct to contemplating philosophy, extended humans will have even more capacity for empathy and ethics.