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The technological singularity —or simply the singularity  —is a hypothetical point in time at which technological growth will become radically faster and uncontrollable, resulting in unforeseeable changes to human civilization. Good ‘s intelligence explosion model, an upgradable intelligent agent will eventually enter a “runaway reaction” of self-improvement cycles, each new and more intelligent generation appearing more and more rapidly, causing an “explosion” in intelligence and resulting in a powerful superintelligence that qualitatively far surpasses all human intelligence.
The first person to use the concept of a “singularity” in the technological context was John von Neumann. The concept and the term “singularity” were popularized by Vernor Vinge in his essay The Coming Technological Singularity , in which he wrote that it would signal the end of the human era, as the new superintelligence would continue to upgrade itself and would advance technologically at an incomprehensible rate.
He wrote that he would be surprised if it occurred before or after Scientists, such as Stephen Hawking , have expressed concern that full artificial intelligence AI could result in human extinction.
Although technological progress has been accelerating in most areas though slowing in some , it has been limited by the basic intelligence of the human brain, which has not, according to Paul R. Ehrlich , changed significantly for millennia. If a superhuman intelligence were to be invented—either through the amplification of human intelligence or through artificial intelligence—it would vastly improve over human problem-solving and inventive skills.
Such an AI is referred to as Seed AI   because if an AI were created with engineering capabilities that matched or surpassed those of its human creators, it would have the potential to autonomously improve its own software and hardware to design an even more capable machine, which could repeat the process in turn.
This recursive self-improvement could accelerate, potentially allowing enormous qualitative change before any upper limits imposed by the laws of physics or theoretical computation set in. It is speculated that over many iterations, such an AI would far surpass human cognitive abilities. Good speculated in that artificial general intelligence might bring about an intelligence explosion: . Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever.
Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control. A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.
John von Neumann , Vernor Vinge and Ray Kurzweil define the concept in terms of the technological creation of super intelligence, arguing that it is difficult or impossible for present-day humans to predict what human beings’ lives would be like in a post-singularity world. Technology forecasters and researchers disagree regarding when, or whether, human intelligence will likely be surpassed.
Some argue that advances in artificial intelligence AI will probably result in general reasoning systems that bypass human cognitive limitations. Others believe that humans will evolve or directly modify their biology so as to achieve radically greater intelligence. The book The Age of Em by Robin Hanson outlines a future in which uploads of human brains emerge instead of or on the way to the emergence of superintelligence.
Some writers use “the singularity” in a broader way to refer to any radical changes in our society brought about by new technologies such as molecular nanotechnology ,    although Vinge and other writers specifically state that without superintelligence, such changes would not qualify as a true singularity.
A speed superintelligence describes an AI that can function like a human mind, only much faster. Many prominent technologists and academics have disputed the plausibility of a technological singularity, including Paul Allen , Jeff Hawkins , John Holland , Jaron Lanier , and Gordon Moore , whose law is often cited in support of the concept.
Most proposed methods for creating superhuman or transhuman minds fall into one of two categories: intelligence amplification of human brains and artificial intelligence. The many speculated ways to augment human intelligence include bioengineering , genetic engineering , nootropic drugs, AI assistants, direct brain—computer interfaces and mind uploading.
These multiple possible paths to an intelligence explosion, all of which will presumably be pursued, makes a singularity more likely. Robin Hanson expressed skepticism of human intelligence augmentation, writing that once the “low-hanging fruit” of easy methods for increasing human intelligence have been exhausted, further improvements will become increasingly difficult.
The possiblility of an intelligence explosion depends on three factors. Contrariwise, as the intelligences become more advanced, further advances will become more and more complicated, possibly outweighing the advantage of increased intelligence.
Each improvement should generate at least one more improvement, on average, for movement towards singularity to continue. Finally, the laws of physics will eventually prevent any further improvements. There are two logically independent, but mutually reinforcing, causes of intelligence improvements: increases in the speed of computation, and improvements to the algorithms used.
But there are some AI researchers, [ who? A email survey of authors with publications at the NeurIPS and ICML machine learning conferences asked about the chance of an intelligence explosion. Both for human and artificial intelligence, hardware improvements increase the rate of future hardware improvements. An analogy to Moore’s Law suggests that if the first doubling of speed took 18 months, the second would take 18 subjective months; or 9 external months, whereafter, four months, two months, and so on towards a speed singularity.
Jeff Hawkins has stated that a self-improving computer system would inevitably run into upper limits on computing power: “in the end there are limits to how big and fast computers can run. We would end up in the same place; we’d just get there a bit faster.
There would be no singularity. It is difficult to directly compare silicon -based hardware with neurons. But Berglas notes that computer speech recognition is approaching human capabilities, and that this capability seems to require 0.
This analogy suggests that modern computer hardware is within a few orders of magnitude of being as powerful as the human brain. The exponential growth in computing technology suggested by Moore’s law is commonly cited as a reason to expect a singularity in the relatively near future, and a number of authors have proposed generalizations of Moore’s law. Computer scientist and futurist Hans Moravec proposed in a book  that the exponential growth curve could be extended back through earlier computing technologies prior to the integrated circuit.
Ray Kurzweil postulates a law of accelerating returns in which the speed of technological change and more generally, all evolutionary processes  increases exponentially, generalizing Moore’s law in the same manner as Moravec’s proposal, and also including material technology especially as applied to nanotechnology , medical technology and others. Kurzweil reserves the term “singularity” for a rapid increase in artificial intelligence as opposed to other technologies , writing for example that “The Singularity will allow us to transcend these limitations of our biological bodies and brains There will be no distinction, post-Singularity, between human and machine”.
Some singularity proponents argue its inevitability through extrapolation of past trends, especially those pertaining to shortening gaps between improvements to technology. In one of the first uses of the term “singularity” in the context of technological progress, Stanislaw Ulam tells of a conversation with John von Neumann about accelerating change:. One conversation centered on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.
Kurzweil claims that technological progress follows a pattern of exponential growth , following what he calls the ” law of accelerating returns “. Whenever technology approaches a barrier, Kurzweil writes, new technologies will surmount it.
He predicts paradigm shifts will become increasingly common, leading to “technological change so rapid and profound it represents a rupture in the fabric of human history”.
Oft-cited dangers include those commonly associated with molecular nanotechnology and genetic engineering. Some intelligence technologies, like “seed AI”,   may also have the potential to not just make themselves faster, but also more efficient, by modifying their source code.
These improvements would make further improvements possible, which would make further improvements possible, and so on. The mechanism for a recursively self-improving set of algorithms differs from an increase in raw computation speed in two ways. First, it does not require external influence: machines designing faster hardware would still require humans to create the improved hardware, or to program factories appropriately.
While speed increases seem to be only a quantitative difference from human intelligence, actual algorithm improvements would be qualitatively different. Eliezer Yudkowsky compares it to the changes that human intelligence brought: humans changed the world thousands of times more rapidly than evolution had done, and in totally different ways.
Similarly, the evolution of life was a massive departure and acceleration from the previous geological rates of change, and improved intelligence could cause change to be as different again. There are substantial dangers associated with an intelligence explosion singularity originating from a recursively self-improving set of algorithms. First, the goal structure of the AI might self-modify, potentially causing the AI to optimise for something other than what was originally intended.
Secondly, AIs could compete for the same scarce resources humankind uses to survive. Carl Shulman and Anders Sandberg suggest that algorithm improvements may be the limiting factor for a singularity; while hardware efficiency tends to improve at a steady pace, software innovations are more unpredictable and may be bottlenecked by serial, cumulative research.
They suggest that in the case of a software-limited singularity, intelligence explosion would actually become more likely than with a hardware-limited singularity, because in the software-limited case, once human-level AI is developed, it could run serially on very fast hardware, and the abundance of cheap hardware would make AI research less constrained.
Some critics, like philosopher Hubert Dreyfus , assert that computers or machines cannot achieve human intelligence , while others, like physicist Stephen Hawking , hold that the definition of intelligence is irrelevant if the net result is the same. Psychologist Steven Pinker stated in There is not the slightest reason to believe in a coming singularity. The fact that you can visualize a future in your imagination is not evidence that it is likely or even possible. Look at domed cities, jet-pack commuting, underwater cities, mile-high buildings, and nuclear-powered automobiles—all staples of futuristic fantasies when I was a child that have never arrived.
Sheer processing power is not a pixie dust that magically solves all your problems. University of California, Berkeley , philosophy professor John Searle writes:. We design them to behave as if they had certain sorts of psychology , but there is no psychological reality to the corresponding processes or behavior.
Martin Ford in The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future  postulates a “technology paradox” in that before the singularity could occur most routine jobs in the economy would be automated, since this would require a level of technology inferior to that of the singularity.
This would cause massive unemployment and plummeting consumer demand, which in turn would destroy the incentive to invest in the technologies that would be required to bring about the Singularity. Job displacement is increasingly no longer limited to work traditionally considered to be “routine. Theodore Modis  and Jonathan Huebner  argue that the rate of technological innovation has not only ceased to rise, but is actually now declining.
Evidence for this decline is that the rise in computer clock rates is slowing, even while Moore’s prediction of exponentially increasing circuit density continues to hold. This is due to excessive heat build-up from the chip, which cannot be dissipated quickly enough to prevent the chip from melting when operating at higher speeds.
Advances in speed may be possible in the future by virtue of more power-efficient CPU designs and multi-cell processors. In a detailed empirical accounting, The Progress of Computing , William Nordhaus argued that, prior to , computers followed the much slower growth of a traditional industrial economy, thus rejecting extrapolations of Moore’s law to 19th-century computers. In a paper, Schmidhuber stated that the frequency of subjectively “notable events” appears to be approaching a 21st-century singularity, but cautioned readers to take such plots of subjective events with a grain of salt: perhaps differences in memory of recent and distant events could create an illusion of accelerating change where none exists.
Paul Allen argued the opposite of accelerating returns, the complexity brake;  the more progress science makes towards understanding intelligence, the more difficult it becomes to make additional progress.
A study of the number of patents shows that human creativity does not show accelerating returns, but in fact, as suggested by Joseph Tainter in his The Collapse of Complex Societies ,  a law of diminishing returns. The number of patents per thousand peaked in the period from to , and has been declining since. Jaron Lanier refutes the idea that the Singularity is inevitable. He states: “I do not think the technology is creating itself.
It’s not an autonomous process. If you structure a society on not emphasizing individual human agency, it’s the same thing operationally as denying people clout, dignity, and self-determination Economist Robert J. Standard of Living Since the Civil War , points out that measured economic growth has slowed around and slowed even further since the financial crisis of — , and argues that the economic data show no trace of a coming Singularity as imagined by mathematician I.
It distracts us from much more pressing problems”, adding “AI tools that we become hyper-dependent on, that is going to happen. And one of the dangers is that we will give them more authority than they warrant. In addition to general criticisms of the singularity concept, several critics have raised issues with Kurzweil’s iconic chart.
One line of criticism is that a log-log chart of this nature is inherently biased toward a straight-line result. Others identify selection bias in the points that Kurzweil chooses to use.
For example, biologist PZ Myers points out that many of the early evolutionary “events” were picked arbitrarily.
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