Natural systems show us only lower bounds to the possible, in cell repair as in everything else.— K. Eric Drexler, Engines of Creation, p. 105
Our ability to create models— virtual realities—in our brains, combined with our modest-looking thumbs, has been sufficient to usher in another form of evolution: technology. That development enabled the persistence of the accelerating pace that started with biological evolution. It will continue until the entire universe is at our fingertips. — Ray Kurzweil, The Singularity Is Near: When Humans Transcend Biology (Kindle Locations 9409-9412; all subsequent references in this format refer to this source)
The combination of nanotechnology and advanced AI will make possible intelligent, effective robots; with such robots, a state could prosper while discarding anyone, or even (in principle) everyone. — K. Eric Drexler, Engines of Creation, p. 176
Along with the massive money printing and debt-laden economy our overlords insist we need, there is another economy, so to speak, that defies their intentions. In the world of technology the
Keynesian horror known as price deflation is the overpowering fact. Far from bringing economic calamity, the accelerating growth of a widening range of technologies is
proving resistant to the Keynesian virus of central bank inflation. And as these technologies merge with our minds and bodies in increasingly diverse and intimate ways, decentralize and revolutionize nearly every aspect of our economy and culture, the world as we know it today will disappear during our lifetimes.
There are at least three reasons why today’s world will soon be ancient history:
1. The life force of capitalism (creativity, entrepreneurship, competition, free markets) is still alive, especially in information technology.
Ray Kurzweil (March 31, 2011 interview): The smartphones we carry around in our pockets are a billion times more powerful — per dollar — than the computer I used at MIT in the late 1960s. They're also 100,000 times smaller. In 25 years our cell phones will be the size of a blood cell and more powerful. (6:10)
2. Once a technology becomes an information technology it is subject to the
Law of Accelerating Returns, meaning it advances exponentially.
Human biology and medicine historically progressed at a linear rate until they were transformed by information technology. When the government version of the Human Genome Project began in 1990, for example, critics said it would take thousands of years to finish, given the speed at which the genome could then be scanned. Yet the 15 year project finished slightly ahead of schedule.
3. The spread of information technology introduces a deflationary effect that expands with advancements in technology.
You could buy one transistor for a dollar in 1968; in 2002 a dollar purchased about ten million transistors. (Kindle 1232)
Despite [the] massive deflation in the cost of information technologies, demand has more than kept up. The number of bits shipped has doubled every 1.1 years, faster than the halving time in cost per bit, which is 1.5 years. As a result, the semiconductor industry enjoyed 18 percent annual growth in total revenue from 1958 to 2002. The entire information-technology (IT) industry has grown from 4.2 percent of the gross domestic product in 1977 to 8.2 percent in 1998. (Kindle 1263-1266)
As Kurzweil has often articulated, exponential growth itself is growing exponentially and applies to a wide range of technologies, from electronic to biological. Nor does growth depend on a specific paradigm, such as Moore’s Law (shrinking of components on an integrated circuit). Since the U.S. census of 1890, there have been five paradigms of computing, each one showing exponential growth in price-performance — electromechanical, relays, vacuum tubes, discrete transistors, and integrated circuits. Each of these paradigms follows an S-curve life cycle — slow growth, followed by explosive growth, ending in a leveling off as it matures.
As a paradigm begins to stall, pressure grows for a replacement paradigm. Engineers were shrinking vacuum tubes in the 1950s while transistors were making their way into portable radios, and they later replaced vacuum tubes in computers. Moore’s Law will fade around the end of this decade and will be replaced by a sixth paradigm, which will likely be three-dimensional molecular computing.
More specifically, researchers have been experimenting with nanotubes — carbon atoms rolled up into a seamless tube — to replace silicon in computers. Because they’re very small nanotubes can achieve very high densities.
Last year, Stanford University engineers built a carbon nanotube computer that was comparable in performance to a 1971
Intel 4004. Peter Burke at California/Irvine in the peer-reviewed journal
Nano Letters says the theoretical speed limit of nanotube transistors should be one terahertz (1,000 GHz). Kurzweil estimates that a cubic inch of nanotube circuitry would be up to 100 million times more powerful than the human brain. (Kindle 1893)
Working smarter
As the computing substrate evolves and becomes orders of magnitude faster, we’re seeing evidence that the software component will lag only slightly behind the hardware advancements.
IBM’s Deep Blue defeated chess champion Garry Kasparov in 1997. Deep Blue, though, was an expensive supercomputer built for that one purpose. Less than a decade later Deep Fritz 10, running on a desktop PC with two Intel Core 2 Duo CPUs, accomplished a similar feat by
defeating the undisputed world champion Vladimir Kramnik in Bonn, Germany. More recently Christophe Théron's
Tiger chess engine, which won tournaments between 2000-2002,
has found a home on Apple’s mobile devices.
Desktop computers and smartphones lack the speed and capacity of 1990s supercomputers. So how can they be so good at playing chess?
In The Age of Intelligent Machines (p. 130), Kurzweil estimated that it would take about 40 billion years to make the “perfect” move in a typical chess match, assuming a 30-move game in which a computer would analyze 8^30 possible moves at the rate of one billion moves per second. (As Kurzweil notes the computer would probably blow up with Big Bang II before the first move was determined.) Rather than attempt the perfect move, human players consider various paths and “prune away” unpromising moves based on pattern-recognition judgments.
That’s how humans approach chess. That’s also how Deep Fritz plays chess. Chess software has become more human-like.
The Evolution of Watson
Watson, the IBM supercomputer that
defeated Jeopardy!’s two all-time champions in 2011, added a new element to computer evolution with its advanced natural language abilities. Watson could not only “read” and retain massive amounts of English-language content, it could understand Alex Trebek’s queries (which were often tricky), determine the probability that it knew the correct answer, and decide whether to respond or not. Watson had to do all this in less than three seconds, on average. To meet this challenge IBM
developed a computer architecture called DeepQA. (QA refers to question answering.)
Perhaps we should be addressing it as Dr. Watson. Watson can read two hundred million pages of clinical data, cross-reference the symptoms of one million cancer patients or read millions of current medical journals to test hypotheses. It can do any of these tasks in 15 seconds or less.
So, for example, the query: “Which disease causes ‘Uveitis’ in a patient with a family history of arthritis presenting circular rash, fever, and headache?”, a traditional search engine would answer with a set of links to web pages which a domain expert then has to read through in order to get the relevant information.
If you ask the same question to Watson, the answer would be:
76% Lyme disease,
1% Behcet’s disease,
1% Sarcoidosis
And Watson has trimmed down considerably.
The version that starred on Jeopardy occupied a large, air conditioned room that was connected to the TV show through an avatar. Today’s Watson,
according to IBM, is 24 times faster, 90 percent smaller and delivered from the cloud. Watson has gone from the size of a master bedroom to three stacked pizza boxes. The latter will seem huge when Watson becomes available on mobile devices.
Can Watson pass for human?
How would Watson technology do in a well-designed Turing test? Better than most but it still lacks some of the subtleties most people regard as uniquely human. Alan Turing
designed the test on the grounds that if a machine can think it can pass for human.
According to Kurzweil,
there are no simple language tricks that would enable a computer to pass a well-designed Turing test. A computer would need to actually master human levels of understanding to pass this threshold.
And when a computer does pass that threshold, Kurzweil will regard it as human. There of course will be controversy over the results. By the time most people concede that machines can think, Kurzweil contends, they will already be “thousands of times smarter than us.” Which means that a strategy for passing the test will be to dumb itself down, which it will easily be smart enough to do.
Given the exponential price-performance growth of technology, he projects that the hardware to simulate the human brain will be available for $1,000 by 2020. This assumes a PC capable of operating at 10^16(ten quadrillion) calculations per second, using dedicated
ASIC chips, and harvesting unused computational capacity of the internet. The software to replicate the functions should take about a decade longer. He’s
betting that by 2029 a computer will pass Turing. “By 2030 it will take a village of human brains (around one thousand) to match a thousand dollars’ worth of computing.”
The engines of revolution
While information technology drives the “strong AI” movement to make computers indistinguishable from humans, it is also engaged in a balancing act elevating humans far beyond their biological origins. Kurzweil refers to this as the Genetics - Nanotechnology - Robotics revolution.
Together, these overlapping developments will usher in what he calls the Singularity, “a future period in which technological change will be so rapid and its impact so profound that every aspect of human life will be irreversibly transformed.” [
Transcendent Man, the movie] Kurzweil’s estimated date for the Singularity is 2045 — thirty-one years from now.
So far, most of his
many predictions have been either correct or essentially correct.
We are already well underway to the Singularity with the Genetics revolution:
By understanding the information processes underlying life, we are starting to learn to reprogram our biology to achieve the virtual elimination of disease, dramatic expansion of human potential, and radical life extension. (Kindle 3675-3677)
With an increased understanding of biochemical pathways,
researchers are finding ways to control gene expression. By manipulating peptides (short chains of amino acids), for example, they are finding they can turn off disease-causing genes or turn on helpful genes that may not be expressed in a certain type of cell.
Yet, reprogramming our biology will never elevate us beyond what Hans Moravec called second-class robots.
The [nanotechnology] revolution will enable us to redesign and rebuild— molecule by molecule— our bodies and brains and the world with which we interact, going far beyond the limitations of biology. (Kindle 3679-3681)
Researcher and author Robert A. Freitas, Jr., a pioneering nanotechnology theorist, has designed robotic replacements for human red blood cells called respirocytes that function many times more effectively than their biological counterparts. A conservative analysis shows if you replaced a portion of your red blood cells with respirocytes, you could do an Olympic sprint for 15 minutes. Without taking a breath. (Kindle 4675)
Freitas estimates that eliminating 50% of medically preventable conditions would extend human life expectancy to 150 years; eliminating 90% would extend it to 1,000 years or more.
we will learn how to augment our 100 trillion very slow inter-neuronal connections with high-speed virtual connections via nano-robotics. This will allow us to greatly boost our pattern-recognition abilities, memories, and overall thinking capacity, as well as to directly interface with powerful forms of computer intelligence. The technology will also provide wireless communication from one brain to another.
In other words, the age of telepathic communication is almost upon us.
Nanorobots, or nanobots as Kurzweil usually calls them, are robots of size 100 nanometers or less and will play an important role in our future. They are programmable, introduced through the blood stream without surgery, and can be directed to leave our bodies. They can rev up our brainpower or amuse us with virtual reality.
We will be more machine than human, and in another sense, if man is indeed a thinking animal, more human than ever.
Once our brains are fully online we will be able to download new knowledge and skills. The role of work will be to create knowledge of all kinds, from music and art to math and science. The role of play will also be to create knowledge. In the future, there won’t be a clear distinction between work and play.
Of the three revolutions the most profound will be robotics, or strong AI. The Turing test will come and go, computers will begin modifying their software to make themselves smarter, leaving even geeks in the dust, and by the “end of this century, computational or mechanical intelligence will be trillions of trillions of times more powerful than unaided human brain power.”
We will then infuse the matter and energy of the universe with nonbiological intelligence, causing it to “wake up.” But this will take awhile, unless there's a way to exceed or circumvent the speed of light.
Conclusion
How do we know we will continue expanding at an exponential rate?
We don’t. If we sit back and let it happen, it won’t happen. But given the realities of the world the trend is just about unshakable. All the wars of the 20th century, the Great Depression, the Cold War, the recent recession — none of it disrupted the exponential progression of technology. On a project by project level, we obviously can’t make firm predictions,
Kurzweil points out. Fifteen years ago it was clear search engines were coming but we didn’t know which one would prevail. Which ideas will win out is not known, either. But the overall trend has been remarkably predictable. As Kurzweil writes, “We would have to repeal capitalism and every vestige of economic competition to stop this progression.” (Kindle 1647-1648)
The downsides to technology are well-known, and it cannot advance without posing a threat. There will always be psychopaths and many of them are enthusiastically voted into political office. Eric Drexler, the father of modern nanotechnology, issues this warning:
The coming breakthroughs will confront states with new pressures and opportunities, encouraging sharp changes in how states behave. This naturally gives cause for concern. States have, historically, excelled at slaughter and oppression. (p. 175)
Fortunately, the exponential favors the individual, especially young people who are eager to embrace new technology. States, as monuments of
bureaucracy and incompetence, are overwhelmed by rapid change. These considerations, in combination with the decentralizing and deflationary aspects of information technology, may ultimately relegate states and their Keynesian priests to the ash bin of history.
