The Singularity Is Near: When Humans Transcend Biology (7 page)

                   —I
RVING
J
OHN
G
OOD
, “S
PECULATIONS
C
ONCERNING THE
F
IRST
U
LTRAINTELLIGENT
M
ACHINE
,” 1965

To put the concept of Singularity into further perspective, let’s explore the history of the word itself. “Singularity” is an English word meaning a unique event with, well, singular implications. The word was adopted by mathematicians to denote a value that transcends any finite limitation, such as the explosion of magnitude that results when dividing a constant by a number that gets closer and closer to zero. Consider, for example, the simple function
y
= 1/
x
. As the value of
x
approaches zero, the value of the function (
y
) explodes to larger and larger values.

A mathematical singularity:
As
x
approaches zero (from right to left), 1/
x
(or
y
) approaches infinity
.

Such a mathematical function never actually achieves an infinite value, since dividing by zero is mathematically “undefined” (impossible to calculate). But the value of
y
exceeds any possible finite limit (approaches infinity) as the divisor
x
approaches zero.

The next field to adopt the word was astrophysics. If a massive star undergoes a supernova explosion, its remnant eventually collapses to the point of apparently zero volume and infinite density, and a “singularity” is created at its center. Because light was thought to be unable to escape the star after it reached this infinite density,
¹⁶
it was called a black hole.
¹⁷
It constitutes a rupture in the fabric of space and time.

One theory speculates that the universe itself began with such a Singularity.
¹⁸
Interestingly, however, the event horizon (surface) of a black hole is of finite size, and gravitational force is only theoretically infinite at the zero-size center of the black hole. At any location that could actually be measured, the forces are finite, although extremely large.

The first reference to the Singularity as an event capable of rupturing the fabric of human history is John von Neumann’s statement quoted above. In the 1960s, I. J. Good wrote of an “intelligence explosion” resulting from intelligent machines’ designing their next generation without human intervention. Vernor Vinge, a mathematician and computer scientist at San Diego State University, wrote about a rapidly approaching “technological singularity” in an article for
Omni
magazine in 1983 and in a science-fiction novel,
Marooned in Realtime
, in 1986.
¹⁹

My 1989 book,
The Age of Intelligent Machines
, presented a future headed inevitably toward machines greatly exceeding human intelligence in the first half of the twenty-first century.
²⁰
Hans Moravec’s 1988 book
Mind Children
came to a similar conclusion by analyzing the progression of robotics.
²¹
In 1993 Vinge presented a paper to a NASA-organized symposium that described the Singularity as an impending event resulting primarily from the advent of “entities with greater than human intelligence,” which Vinge saw as the harbinger of a runaway phenomenon.
²²
My 1999 book,
The Age of Spiritual Machines: When Computers Exceed Human Intelligence
, described the increasingly intimate connection between our biological intelligence and the artificial intelligence we are creating.
²³
Hans Moravec’s book
Robot: Mere Machine to Transcendent Mind
, also published in 1999, described the robots of the 2040s as our “evolutionary heirs,” machines that will “grow from us, learn our skills, and share our goals and values, . . . children of our minds.”
²⁴
Australian scholar Damien Broderick’s 1997 and 2001 books, both titled
The Spike
, analyzed the pervasive impact of the extreme phase of technology acceleration anticipated within several decades.
²⁵
In an extensive series of writings, John Smart has described the Singularity as the inevitable result of what he calls “MEST” (matter, energy, space, and time) compression.
²⁶

From my perspective, the Singularity has many faces. It represents the nearly vertical phase of exponential growth that occurs when the rate is so extreme that technology appears to be expanding at infinite speed. Of course, from a mathematical perspective, there is no discontinuity, no rupture, and the growth rates remain finite, although extraordinarily large. But from our
currently
limited framework, this imminent event appears to be an acute and abrupt break in the continuity of progress. I emphasize the word “currently” because one of the salient implications of the Singularity will be a change in the nature of our ability to understand. We will become vastly smarter as we merge with our technology.

Can the pace of technological progress continue to speed up indefinitely? Isn’t there a point at which humans are unable to think fast enough to keep up? For unenhanced humans, clearly so. But what would 1,000 scientists, each 1,000 times more intelligent than human scientists today, and each operating 1,000 times faster than contemporary humans (because the information processing in their primarily nonbiological brains is faster) accomplish? One chronological year would be like a millennium for them.
²⁷
What would they come up with?

Well, for one thing, they would come up with technology to become even more intelligent (because their intelligence is no longer of fixed capacity). They would change their own thought processes to enable them to think even faster.
When scientists become a million times more intelligent and operate a million times faster, an hour would result in a century of progress (in today’s terms).

The Singularity involves the following principles, which I will document, develop, analyze, and contemplate throughout the rest of this book:

• The rate of paradigm shift (technical innovation) is accelerating, right now doubling every decade.
  ²⁸
  
• The power (price-performance, speed, capacity, and bandwidth) of information technologies is growing exponentially at an even faster pace, now doubling about every year.
  ²⁹
  This principle applies to a wide range of measures, including the amount of human knowledge.
  
• For information technologies, there is a second level of exponential growth: that is, exponential growth in the rate of exponential growth (the exponent). The reason: as a technology becomes more cost effective, more resources are deployed toward its advancement, so the rate of exponential growth increases over time. For example, the computer industry in the 1940s consisted of a handful of now historically important projects. Today total revenue in the computer industry is more than one trillion dollars, so research and development budgets are comparably higher.
  
• Human brain scanning is one of these exponentially improving technologies. As I will show in
  chapter 4
  , the temporal and spatial resolution and bandwidth of brain scanning are doubling each year. We are just now obtaining the tools sufficient to begin serious reverse engineering (decoding) of the human brain’s principles of operation. We already have impressive models and simulations of a couple dozen of the brain’s several hundred regions. Within two decades, we will have a detailed understanding of how all the regions of the human brain work.
  
• We will have the requisite hardware to emulate human intelligence with supercomputers by the end of this decade and with personal-computer-size devices by the end of the following decade. We will have effective software models of human intelligence by the mid-2020s.
  
• With both the hardware and software needed to fully emulate human intelligence, we can expect computers to pass the Turing test, indicating intelligence indistinguishable from that of biological humans, by the end of the 2020s.
  ³⁰
  
• When they achieve this level of development, computers will be able to combine the traditional strengths of human intelligence with the strengths of machine intelligence.
  
• The traditional strengths of human intelligence include a formidable ability to recognize patterns. The massively parallel and self-organizing nature
  of the human brain is an ideal architecture for recognizing patterns that are based on subtle, invariant properties. Humans are also capable of learning new knowledge by applying insights and inferring principles from experience, including information gathered through language. A key capability of human intelligence is the ability to create mental models of reality and to conduct mental “what-if” experiments by varying aspects of these models.
  
• The traditional strengths of machine intelligence include the ability to remember billions of facts precisely and recall them instantly.
  
• Another advantage of nonbiological intelligence is that once a skill is mastered by a machine, it can be performed repeatedly at high speed, at optimal accuracy, and without tiring.
  
• Perhaps most important, machines can share their knowledge at extremely high speed, compared to the very slow speed of human knowledge-sharing through language.
  
• Nonbiological intelligence will be able to download skills and knowledge from other machines, eventually also from humans.
  
• Machines will process and switch signals at close to the speed of light (about three hundred million meters per second), compared to about one hundred meters per second for the electrochemical signals used in biological mammalian brains.
  ³¹
  This speed ratio is at least three million to one.
  
• Machines will have access via the Internet to all the knowledge of our human-machine civilization and will be able to master all of this knowledge.
  
• Machines can pool their resources, intelligence, and memories. Two machines—or one million machines—can join together to become one and then become separate again. Multiple machines can do both at the same time: become one and separate simultaneously. Humans call this falling in love, but our biological ability to do this is fleeting and unreliable.
  
• The combination of these traditional strengths (the pattern-recognition ability of biological human intelligence and the speed, memory capacity and accuracy, and knowledge and skill-sharing abilities of nonbiological intelligence) will be formidable.
  
• Machine intelligence will have complete freedom of design and architecture (that is, they won’t be constrained by biological limitations, such as the slow switching speed of our interneuronal connections or a fixed skull size) as well as consistent performance at all times.
  
• Once nonbiological intelligence combines the traditional strengths of both humans and machines, the nonbiological portion of our civilization’s
  intelligence will then continue to benefit from the double exponential growth of machine price-performance, speed, and capacity.
  
• Once machines achieve the ability to design and engineer technology as humans do, only at far higher speeds and capacities, they will have access to their own designs (source code) and the ability to manipulate them. Humans are now accomplishing something similar through biotechnology (changing the genetic and other information processes underlying our biology), but in a much slower and far more limited way than what machines will be able to achieve by modifying their own programs.
  
• Biology has inherent limitations. For example, every living organism must be built from proteins that are folded from one-dimensional strings of amino acids. Protein-based mechanisms are lacking in strength and speed. We will be able to reengineer all of the organs and systems in our biological bodies and brains to be vastly more capable.
  
• As we will discuss in
  chapter 4
  , human intelligence does have a certain amount of plasticity (ability to change its structure), more so than had previously been understood. But the architecture of the human brain is nonetheless profoundly limited. For example, there is room for only about one hundred trillion interneuronal connections in each of our skulls. A key genetic change that allowed for the greater cognitive ability of humans compared to that of our primate ancestors was the development of a larger cerebral cortex as well as the development of increased volume of graymatter tissue in certain regions of the brain.
  ³²
  This change occurred, however, on the very slow timescale of biological evolution and still involves an inherent limit to the brain’s capacity. Machines will be able to reformulate their own designs and augment their own capacities without limit. By using nanotechnology-based designs, their capabilities will be far greater than biological brains without increased size or energy consumption.
  
• Machines will also benefit from using very fast three-dimensional molecular circuits. Today’s electronic circuits are more than one million times faster than the electrochemical switching used in mammalian brains. Tomorrow’s molecular circuits will be based on devices such as nanotubes, which are tiny cylinders of carbon atoms that measure about ten atoms across and are five hundred times smaller than today’s silicon-based transistors. Since the signals have less distance to travel, they will also be able to operate at terahertz (trillions of operations per second) speeds compared to the few gigahertz (billions of operations per second) speeds of current chips.
  
• The rate of technological change will not be limited to human mental
  speeds. Machine intelligence will improve its own abilities in a feedback cycle that unaided human intelligence will not be able to follow.
  
• This cycle of machine intelligence’s iteratively improving its own design will become faster and faster. This is in fact exactly what is predicted by the formula for continued acceleration of the rate of paradigm shift. One of the objections that has been raised to the continuation of the acceleration of paradigm shift is that it ultimately becomes much too fast for humans to follow, and so therefore, it’s argued, it cannot happen. However, the shift from biological to nonbiological intelligence will enable the trend to continue.
  
• Along with the accelerating improvement cycle of nonbiological intelligence, nanotechnology will enable the manipulation of physical reality at the molecular level.
  
• Nanotechnology will enable the design of nanobots: robots designed at the molecular level, measured in microns (millionths of a meter), such as “respirocytes” (mechanical red-blood cells).
  ³³
  Nanobots will have myriad roles within the human body, including reversing human aging (to the extent that this task will not already have been completed through biotechnology, such as genetic engineering).
  
• Nanobots will interact with biological neurons to vastly extend human experience by creating virtual reality from within the nervous system.
  
• Billions of nanobots in the capillaries of the brain will also vastly extend human intelligence.
  
• Once nonbiological intelligence gets a foothold in the human brain (this has already started with computerized neural implants), the machine intelligence in our brains will grow exponentially (as it has been doing all along), at least doubling in power each year. In contrast, biological intelligence is effectively of fixed capacity. Thus, the nonbiological portion of our intelligence will ultimately predominate.
  
• Nanobots will also enhance the environment by reversing pollution from earlier industrialization.
  
• Nanobots called foglets that can manipulate image and sound waves will bring the morphing qualities of virtual reality to the real world.
  ³⁴
  
• The human ability to understand and respond appropriately to emotion (so-called emotional intelligence) is one of the forms of human intelligence that will be understood and mastered by future machine intelligence. Some of our emotional responses are tuned to optimize our intelligence in the context of our limited and frail biological bodies. Future machine intelligence will also have “bodies” (for example, virtual
  bodies in virtual reality, or projections in real reality using foglets) in order to interact with the world, but these nanoengineered bodies will be far more capable and durable than biological human bodies. Thus, some of the “emotional” responses of future machine intelligence will be redesigned to reflect their vastly enhanced physical capabilities.
  ³⁵
  
• As virtual reality from within the nervous system becomes competitive with real reality in terms of resolution and believability, our experiences will increasingly take place in virtual environments.
  
• In virtual reality, we can be a different person both physically and emotionally. In fact, other people (such as your romantic partner) will be able to select a different body for you than you might select for yourself (and vice versa).
  
• The law of accelerating returns will continue until nonbiological intelligence comes close to “saturating” the matter and energy in our vicinity of the universe with our human-machine intelligence. By saturating, I mean utilizing the matter and energy patterns for computation to an optimal degree, based on our understanding of the physics of computation. As we approach this limit, the intelligence of our civilization will continue its expansion in capability by spreading outward toward the rest of the universe. The speed of this expansion will quickly achieve the maximum speed at which information can travel.
  
• Ultimately, the entire universe will become saturated with our intelligence. This is the destiny of the universe. (See
  chapter 6
  .) We will determine our own fate rather than have it determined by the current “dumb,” simple, machinelike forces that rule celestial mechanics.
  
• The length of time it will take the universe to become intelligent to this extent depends on whether or not the speed of light is an immutable limit. There are indications of possible subtle exceptions (or circumventions) to this limit, which, if they exist, the vast intelligence of our civilization at this future time will be able to exploit.