Технологиялық ерекшелік немесе өзінен өсу кезеңі

Hypothetical point in time when technological growth becomes uncontrollable and irreversible

The technological singularity—or simply the singularity—is a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable consequences for human civilization. According to the most popular version of the singularity hypothesis, I. J. Good's intelligence explosion model, an upgradable intelligent agent will eventually enter a positive feedback loop of self improvement cycles, each new and more intelligent generation appearing more and more rapidly, causing a rapid increase ("explosion") in intelligence which ultimately results 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 the 20th century Hungarian American mathematician John von Neumann. Stanislaw Ulam reported in 1958 an earlier discussion with von Neumann "centered on the 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". The consequences of the singularity and its potential benefit or harm to the human race have been intensely debated. Prominent technologists and academics dispute the plausibility of a technological singularity and the associated artificial intelligence explosion, including Paul Allen, However, with the increasing power of computers and other technologies, it might eventually be possible to build a machine that is significantly more intelligent than humans. If a superhuman intelligence were to be invented—either through the amplification of human intelligence or through artificial intelligence—it would, in theory, 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. I. J. Good speculated in 1965 that superhuman intelligence might bring about an intelligence explosion: For example, with a million fold increase in the speed of information processing relative to that of humans, a subjective year would pass in 30 physical seconds. 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. A number of futures studies focus on scenarios that combine these possibilities, suggesting that humans are likely to interface with computers, or upload their minds to computers, in a way that enables substantial intelligence amplification. The book The Age of Em by Robin Hanson describes a hypothetical future scenario in which human brains are scanned and digitized, creating "uploads" or digital versions of human consciousness. In this future, the development of these uploads may precede or coincide with the emergence of superintelligent artificial intelligence.

Some writers use "the singularity" in a broader way to refer to any radical changes in society brought about by new technology (such as molecular nanotechnology), and the singularity in 2045. In a 2017 interview, Kurzweil reaffirmed his estimates. In 1988, Moravec predicted that if the rate of improvement continues, the computing capabilities for human level AI would be available in supercomputers before 2010. Four polls of AI researchers, conducted in 2012 and 2013 by Nick Bostrom and Vincent C. Müller, suggested a confidence of 50% that human level AI would be developed by 2040–2050.

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. 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) On the other hand, it has been argued that the global acceleration pattern having the 21st century singularity as its parameter should be characterized as hyperbolic rather than exponential. 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". Kurzweil believes that the singularity will occur by approximately 2045. 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. While not actively malicious, AIs would promote the goals of their programming, not necessarily broader human goals, and thus might crowd out humans. 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. An abundance of accumulated hardware that can be unleashed once the software figures out how to use it has been called "computing overhang".

Dramatic changes in the rate of economic growth have occurred in the past because of technological advancement. Based on population growth, the economy doubled every 250,000 years from the Paleolithic era until the Neolithic Revolution. The new agricultural economy doubled every 900 years, a remarkable increase. In the current era, beginning with the Industrial Revolution, the world's economic output doubles every fifteen years, sixty times faster than during the agricultural era. If the rise of superhuman intelligence causes a similar revolution, argues Robin Hanson, one would expect the economy to double at least quarterly and possibly on a weekly basis.

The term "technological singularity" reflects the idea that such change may happen suddenly, and that it is difficult to predict how the resulting new world would operate. So, facing possible futures of incalculable benefits and risks, the experts are surely doing everything possible to ensure the best outcome, right? Wrong. If a superior alien civilisation sent us a message saying, "We'll arrive in a few decades," would we just reply, "OK, call us when you get here – we'll leave the lights on"? Probably not – but this is more or less what is happening with AI. claims that there is no direct evolutionary motivation for an AI to be friendly to humans. Evolution has no inherent tendency to produce outcomes valued by humans, and there is little reason to expect an arbitrary optimisation process to promote an outcome desired by humankind, rather than inadvertently leading to an AI behaving in a way not intended by its creators. Anders Sandberg has also elaborated on this scenario, addressing various common counter arguments. AI researcher Hugo de Garis suggests that artificial intelligences may simply eliminate the human race for access to scarce resources, and humans would be powerless to stop them. Alternatively, AIs developed under evolutionary pressure to promote their own survival could outcompete humanity. proposes an AI design that avoids several dangers including self delusion, unintended instrumental actions, and corruption of the reward generator. and testing AI. His 2001 book Super Intelligent Machines advocates the need for public education about AI and public control over AI. It also proposed a simple design that was vulnerable to corruption of the reward generator.

In February 2009, under the auspices of the Association for the Advancement of Artificial Intelligence (AAAI), Eric Horvitz chaired a meeting of leading computer scientists, artificial intelligence researchers and roboticists at the Asilomar conference center in Pacific Grove, California. The goal was to discuss the potential impact of the hypothetical possibility that robots could become self sufficient and able to make their own decisions. They discussed the extent to which computers and robots might be able to acquire autonomy, and to what degree they could use such abilities to pose threats or hazards. Frank S. Robinson predicts that once humans achieve a machine with the intelligence of a human, scientific and technological problems will be tackled and solved with brainpower far superior to that of humans. He notes that artificial systems are able to share data more directly than humans, and predicts that this would result in a global network of super intelligence that would dwarf human capability. Robinson also discusses how vastly different the future would potentially look after such an intelligence explosion.

thumb|upright=1.6|In this sample recursive self improvement scenario, humans modifying an AI's architecture would be able to double its performance every three years through, for example, 30 generations before exhausting all feasible improvements (left). If instead the AI is smart enough to modify its own architecture as well as human researchers can, its time required to complete a redesign halves with each generation, and it progresses all 30 feasible generations in six years (right). In a hard takeoff scenario, an artificial superintelligence rapidly self improves, "taking control" of the world (perhaps in a matter of hours), too quickly for significant human initiated error correction or for a gradual tuning of the agent's goals. In a soft takeoff scenario, the AI still becomes far more powerful than humanity, but at a human like pace (perhaps on the order of decades), on a timescale where ongoing human interaction and correction can effectively steer the AI's development. Ramez Naam argues against a hard takeoff. He has pointed out that we already see recursive self improvement by superintelligences, such as corporations. Intel, for example, has "the collective brainpower of tens of thousands of humans and probably millions of CPU cores to design better CPUs!" However, this has not led to a hard takeoff; rather, it has led to a soft takeoff in the form of Moore's law. Naam further points out that the computational complexity of higher intelligence may be much greater than linear, such that "creating a mind of intelligence 2 is probably more than twice as hard as creating a mind of intelligence 1." J. Storrs Hall believes that "many of the more commonly seen scenarios for overnight hard takeoff are circular – they seem to assume hyperhuman capabilities at the starting point of the self improvement process" in order for an AI to be able to make the dramatic, domain general improvements required for takeoff. Hall suggests that rather than recursively self improving its hardware, software, and infrastructure all on its own, a fledgling AI would be better off specializing in one area where it was most effective and then buying the remaining components on the marketplace, because the quality of products on the marketplace continually improves, and the AI would have a hard time keeping up with the cutting edge technology used by the rest of the world. Ben Goertzel agrees with Hall's suggestion that a new human level AI would do well to use its intelligence to accumulate wealth. The AI's talents might inspire companies and governments to disperse its software throughout society. Goertzel is skeptical of a hard five minute takeoff but speculates that a takeoff from human to superhuman level on the order of five years is reasonable. He refers to this scenario as a "semihard takeoff". Max More disagrees, arguing that if there were only a few superfast human level AIs, that they would not radically change the world, as they would still depend on other people to get things done and would still have human cognitive constraints. Even if all superfast AIs worked on intelligence augmentation, it is unclear why they would do better in a discontinuous way than existing human cognitive scientists at producing super human intelligence, although the rate of progress would increase. More further argues that a superintelligence would not transform the world overnight: a superintelligence would need to engage with existing, slow human systems to accomplish physical impacts on the world. "The need for collaboration, for organization, and for putting ideas into physical changes will ensure that all the old rules are not thrown out overnight or even within years."