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技术奇点 (查看源代码)

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许多著名的技术专家和学者都对技术奇点的合理性提出质疑，包括[[Paul Allen]]、[[Jeff Hawkins]]、[[John Henry Holland | John Holland]]、[[Jaron Lanier]]和[[Gordon Moore]]，他的[[摩尔定律]]经常被引用来支持这一概念。<ref name="spectrum.ieee.org"/><ref name="ieee"/><ref name="Allen"/>

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--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）这段之前也出现过。不过前面的似乎是半截话，说了之后就没有下文了；这里似乎是符合上下文逻辑的。

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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 1998 book that the exponential growth curve could be extended back through earlier computing technologies prior to the integrated circuit.

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摩尔定律所显示的计算技术的指数增长通常被援引为奇点将在不远的将来出现的一个理由，许多作者已经提出了对摩尔定律的推广。计算机科学家和未来主义者汉斯·莫拉维奇Hans Moravec在1998年的一本书中提出，指数增长曲线可以通过集成电路出现之前的早期计算技术进行延伸。

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Most proposed methods for creating superhuman or [[transhuman]] minds fall into one of two categories: intelligence amplification of human brains and artificial intelligence. The speculated ways to produce intelligence augmentation are many, and include [[bioengineering]], [[genetic engineering]], [[nootropic]] drugs, AI assistants, direct [[brain–computer interface]]s and [[mind uploading]]. Because multiple paths to an intelligence explosion are being explored, it makes a singularity more likely; for a singularity to not occur they would all have to fail.<ref name="singinst.org">{{cite web|url=http://singinst.org/overview/whatisthesingularity |title=What is the Singularity? | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110908014050/http://singinst.org/overview/whatisthesingularity/ |archivedate=2011-09-08 }}</ref>

大多数创造超人或[[跨人类]]头脑的方法分为两类：人脑的智能增强和人工智能。据推测，智能增强的方法很多，包括[[生物工程]]、[[基因工程]]、[[nootropic]]药物、AI助手、直接[[脑-机接口]]和[[思维上传]]。因为人们正在探索通向智能爆炸的多种途径，这使得奇点更有可能；对于一个不会出现的奇点，所有这些都必将失败。<ref name="singinst.org">{{cite web|url=http://singinst.org/overview/whatisthesingularity |title=What is the Singularity? | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110908014050/http://singinst.org/overview/whatisthesingularity/ |archivedate=2011-09-08 }}</ref>

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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.

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<font color = "32cd32">雷 · 库兹韦尔假定了一个技术变革(更广泛地说，所有的进化过程)的速度的加速回报定律Ray Kurzweil postulates a law of accelerating returns in which the speed of technological change (and more generally, all evolutionary processes</font>。另一方面，有人认为，对具有奇点的21世纪，全球加速模式应该被描述为双曲型而不是指数型。

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[[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 to find.<ref name="hanson">{{cite web |url=https://mason.gmu.edu/~rhanson/vc.html#hanson |title=Some Skepticism |date=1998 |first=Robin |last=Hanson |author-link=Robin Hanson |accessdate=April 8, 2020}}</ref> Despite all of the speculated ways for amplifying human intelligence, non-human artificial intelligence (specifically seed AI) is the most popular option among the hypotheses that would advance the singularity.{{citation needed|date=July 2012}}

[[Robin Hanson]]对人类智能增强表示怀疑，他写道，一旦提高人类智力的“唾手可得的”简单方法用尽，进一步的改进将变得越来越难。<ref name="hanson">{{cite web |url=https://mason.gmu.edu/~rhanson/vc.html#hanson |title=Some Skepticism |date=1998 |first=Robin |last=Hanson |author-link=Robin Hanson |accessdate=April 8, 2020}}</ref>即使有各种提高人类智能的方法的推测，但对非人类人工智能(特别是种子人工智能)的推测仍是所有能推进奇点的假说中最受欢迎的一个。

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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. His predictions differ from Vinge's in that he predicts a gradual ascent to the singularity, rather than Vinge's rapidly self-improving superhuman intelligence.

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库兹韦尔将“奇点”一词用于描述人工智能(相对于其他技术)的快速增长，例如他写道: “奇点将允许我们超越生物体和大脑的局限……后奇点时代，人类与机器之间将不再有区别”。库兹韦尔相信奇点将在大约2045年之前出现。他的预测与Vinge 的不同之处在于，他预测的是一个逐渐上升到奇点的过程，而不是 Vinge 的快速自我完善的超人智慧。

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Whether or not an intelligence explosion occurs depends on three factors.<ref name="david_chalmers_singularity_lecture_resources_available">David Chalmers John Locke Lecture, 10 May, Exam Schools, Oxford, [http://www.fhi.ox.ac.uk/news/2010/david_chalmers_singularity_lecture_resources_available Presenting a philosophical analysis of the possibility of a technological singularity or "intelligence explosion" resulting from recursively self-improving AI] {{webarchive|url=https://web.archive.org/web/20130115205558/http://www.fhi.ox.ac.uk/news/2010/david_chalmers_singularity_lecture_resources_available |date=2013-01-15 }}.</ref> The first accelerating factor is the new intelligence enhancements made possible by each previous improvement. Contrariwise, as the intelligences become more advanced, further advances will become more and more complicated, possibly overcoming the advantage of increased intelligence. Each improvement should beget at least one more improvement, on average, for movement towards singularity to continue. Finally, the laws of physics will eventually prevent any further improvements.

智能爆炸是否发生取决于三个因素。第一个加速因素是以前的每一次改进都使新的智能增强成为可能。相反，随着智力的进步，进一步的发展将变得越来越复杂，可能会抵消智力增长的优势。平均来说，每一次改进都应该至少再带来一次改进，以便继续朝着奇点的方向发展。最后，物理定律最终会阻止任何进一步的改进。

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Oft-cited dangers include those commonly associated with molecular nanotechnology and genetic engineering. These threats are major issues for both singularity advocates and critics, and were the subject of Bill Joy's Wired magazine article "Why the future doesn't need us".

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经常被引用的危险包括那些通常与分子纳米技术和基因工程有关的危险。这些威胁是奇点倡导者和批评者的主要问题，也是比尔 · 乔伊在《连线Wired》杂志上发表文章《为什么未来不需要我们Why the future doesn't need us》的主题。

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There are two logically independent, but mutually reinforcing, causes of intelligence improvements: increases in the speed of computation, and improvements to the [[algorithm]]s used.<ref name="consc.net">[http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis, David J. Chalmers]</ref> The former is predicted by [[Moore's law|Moore's Law]] and the forecasted improvements in hardware,<ref name="itrs">{{cite web |url=http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |title=ITRS |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110929173755/http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |archivedate=2011-09-29 }}</ref> and is comparatively similar to previous technological advances. But there are some AI researchers{{who|date=March 2017}} who believe software is more important than hardware.<ref>{{Cite web|url=https://blog.chronicled.com/why-software-is-more-important-than-hardware-right-now-6a4b58feaa7c|title=Why Software Is More Important Than Hardware Right Now|last=Kulkarni|first=Ajit|date=2017-12-12|website=Chronicled|access-date=2019-02-23}}</ref>{{citation needed|date=July 2012}}

智能改进有两个逻辑上独立但又相互加强的原因：计算速度的提高和使用的[[算法]]的改进。<ref name="consc.net">[http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis, David J. Chalmers]</ref> 前者由[[摩尔定律|摩尔定律]]和硬件方面的预测改进进行预测，<ref name="itrs">{{cite web |url=http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |title=ITRS |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110929173755/http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |archivedate=2011-09-29 }}</ref> 与以前的技术进步比较相似。但也有一些人工智能研究人员认为软件比硬件更重要。<ref>{{Cite web|url=https://blog.chronicled.com/why-software-is-more-important-than-hardware-right-now-6a4b58feaa7c|title=Why Software Is More Important Than Hardware Right Now|last=Kulkarni|first=Ajit|date=2017-12-12|website=Chronicled|access-date=2019-02-23}}</ref>{{citation needed|date=July 2012}}

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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 not be invariant under self-improvement, potentially causing the AI to optimise for something other than what was originally intended. Secondly, AIs could compete for the same scarce resources mankind uses to survive.

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由递归自我改进的算法集合引起的智能爆炸存在实质性的危险。首先，人工智能的目标结构可能不会在自我完善的情况下保持不变，这可能会导致人工智能为其他目标进行优化。其次，人工智能可以竞争人类赖以生存的稀缺资源。

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A 2017 email survey of authors with publications at the 2015 [[Conference on Neural Information Processing Systems|NeurIPS]] and [[International Conference on Machine Learning|ICML]] machine learning conferences asked about the chance of an intelligence explosion. Of the respondents, 12% said it was "quite likely", 17% said it was "likely", 21% said it was "about even", 24% said it was "unlikely" and 26% said it was "quite unlikely".<ref>{{cite arxiv|last1=Grace|first1=Katja|last2=Salvatier|first2=John|last3=Dafoe|first3=Allan|last4=Zhang|first4=Baobao|last5=Evans|first5=Owain|title=When Will AI Exceed Human Performance? Evidence from AI Experts|eprint=1705.08807|date=24 May 2017|class=cs.AI}}</ref>

2017年对2015年[[神经信息处理系统会议| NeurIPS]]和[[International Conference on Machine Learning | ICML]]机器学习会议上发表文章的作者的电子邮件调查询问了智能爆炸的可能性。在受访者中，12%的人认为“很有可能”，17%的人说“很可能”，21%的人说“差不多”，24%的人说“不太可能”，26%的人说“不太可能”。<ref>{{cite arxiv|last1=Grace|first1=Katja|last2=Salvatier|first2=John|last3=Dafoe|first3=Allan|last4=Zhang|first4=Baobao|last5=Evans|first5=Owain|title=When Will AI Exceed Human Performance? Evidence from AI Experts|eprint=1705.08807|date=24 May 2017|class=cs.AI}}</ref>

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While not actively malicious, there is no reason to think that AIs would actively promote human goals unless they could be programmed as such, and if not, might use the resources currently used to support mankind to promote its own goals, causing human extinction.

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尽管人工智能并非主动怀有恶意，但我们没有理由认为它们会主动促进人类目标，除非它们能够被编入这样的程序，否则它们可能会利用目前用于支持人类的资源来促进其自身目标，从而导致人类灭绝。

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=== Speed improvements速度改进 ===

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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."

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卡尔 · 舒尔曼和安德斯 · 桑德伯格认为，算法改进可能是奇点的限制因素; 虽然硬件效率趋向于稳步提高，但软件创新更加不可预测，可能会被连续的、累积的研究所阻碍。他们认为，在软件受限的奇点情况下，智能爆炸实际上比硬件受限的奇点更有可能发生，因为在软件受限的情况下，一旦开发出人类水平的人工智能，它可以在非常快速的硬件上连续运行，而大量廉价的硬件将使人工智能研究受到更少的限制。一旦软件知道如何使用，就可以释放大量积累的硬件，这被称为“计算过剩”

Both for human and artificial intelligence, hardware improvements increase the rate of future hardware improvements. Simply put,<ref name="arstechnica">{{cite web|last=Siracusa |first=John |url=https://arstechnica.com/apple/reviews/2009/08/mac-os-x-10-6.ars/8 |title=Mac OS X 10.6 Snow Leopard: the Ars Technica review |publisher=Arstechnica.com |date=2009-08-31 |accessdate=2011-09-09}}</ref> [[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.<ref name="singularity6">Eliezer Yudkowsky, 1996 [http://www.yudkowsky.net/obsolete/singularity.html "Staring into the Singularity"]</ref> An upper limit on speed may eventually be reached, although it is unclear how high this would be. 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."<ref name="Hawkins">{{cite magazine |url=https://spectrum.ieee.org/computing/hardware/tech-luminaries-address-singularity |title=Tech Luminaries Address Singularity |date=1 June 2008 |magazine=[[IEEE Spectrum]]}}</ref>

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很难直接将基于[[硅]]的硬件与[[神经元]]相比较。但是{Harvtxt| Berglas|2008}指出计算机[[语音识别]]正在接近人类的能力，而且这种能力似乎需要0.01%的脑容量。这个类比表明，现代计算机硬件与人脑一样强大，只差几个数量级。

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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.}}

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一些批评家，比如哲学家休伯特 · 德雷福斯，断言计算机或机器不能实现人类智能，而另一些人，比如物理学家斯蒂芬 · 霍金，则认为如果最终结果是相同的，那么智能的定义就无关紧要

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====Exponential growth指数增长====

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In a 2007 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.

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在2007年的一篇论文中，施密德胡贝尔Schmidhuber指出主观上“显著事件”的频率似乎正在接近21世纪的奇点，但提醒读者，对这些主观事件的情节要持保留态度：也许对最近和遥远的事件记忆上的差异，可能会造成一种在根本不存在的情况下加速变化的错觉。

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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 1998 book<ref>{{cite book|author=Moravec, Hans|title=Robot: Mere Machine to Transcendent Mind|year=1999|publisher=Oxford U. Press|page=61|url=https://books.google.com/books?id=fduW6KHhWtQC&pg=PA61|isbn=978-0-19-513630-2}}</ref> that the exponential growth curve could be extended back through earlier computing technologies prior to the [[integrated circuit]].

摩尔定律所建议的计算技术的指数增长通常被认为是在相对不远的将来出现奇点的一个理由，许多作者已经提出了摩尔定律的推广。计算机科学家和未来学家[[Hans Moravec]]在1998年的一本书中提出<ref>{{cite book|author=Moravec, Hans|title=Robot: Mere Machine to Transcendent Mind|year=1999|publisher=Oxford U. Press|page=61|url=https://books.google.com/books?id=fduW6KHhWtQC&pg=PA61|isbn=978-0-19-513630-2}}</ref>指数增长曲线可以通过[[集成电路]]之前的早期计算技术进行延伸。

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Paul Allen argued the opposite of accelerating returns, the complexity brake; He goes on to assert: "The reason to believe in human agency over technological determinism is that you can then have an economy where people earn their own way and invent their own lives. 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 ... to embrace [the idea of the Singularity] would be a celebration of bad data and bad politics."

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保罗 · 艾伦认为加速回报的反面是复杂性制动器; 他继续断言: “相信人类的能动性而非技术决定论的原因在于，你可以拥有一种经济，在这种经济中，人们可以自食其力，创造自己的生活。如果你建立一个不强调个人能动性的社会，那么在操作层面上，这与否定人们的影响力、尊严和自决是一回事... ... 接受[奇点理念]将是对错误数据和错误政治的颂扬。”

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[[Ray Kurzweil]] postulates a [[law of accelerating returns]] in which the speed of technological change (and more generally, all evolutionary processes<ref name="google"/>) 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|medical technology]] and others.<ref name="singularity2"/> Between 1986 and 2007, machines' application-specific capacity to compute information per capita roughly doubled every 14 months; the per capita capacity of the world's general-purpose computers has doubled every 18 months; the global telecommunication capacity per capita doubled every 34 months; and the world's storage capacity per capita doubled every 40 months.<ref name="HilbertLopez2011">[http://www.sciencemag.org/content/332/6025/60 "The World's Technological Capacity to Store, Communicate, and Compute Information"], Martin Hilbert and Priscila López (2011), [[Science (journal)|Science]], 332(6025), 60–65; free access to the article through here: martinhilbert.net/WorldInfoCapacity.html</ref> 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 growth|hyperbolic]] rather than exponential.<ref>[https://link.springer.com/book/10.1007/978-3-030-33730-8 ''The 21st Century Singularity and Global Futures. A Big History Perspective''] (Springer, 2020)</ref>

[[Ray Kurzweil]]假设了一个[[加速回报定律]]，其中技术变革的速度（更广泛地说，所有进化过程<ref name="google"/>）急剧增长。从1986年到2007年，摩尔定律以与莫拉维克提案相同的方式呈指数增长，并包括材料技术（尤其是应用于[[纳米技术]]）、[[医疗技术|医疗技术]]和其他技术，计算机计算人均信息的特定应用能力大约每14个月翻一番；世界通用计算机的人均容量每18个月翻一番；全球人均电信容量每34个月翻一番；世界人均存储容量每40个月翻一番。<ref name="HilbertLopez2011">[http://www.sciencemag.org/content/332/6025/60 "The World's Technological Capacity to Store, Communicate, and Compute Information"], Martin Hilbert and Priscila López (2011), [[Science (journal)|Science]], 332(6025), 60–65; free access to the article through here: martinhilbert.net/WorldInfoCapacity.html</ref> 另一方面，有人认为，以21世纪奇点为参数的全球加速度模式应该被描述为[[双曲线增长|双曲]]而不是指数型<ref>[https://link.springer.com/book/10.1007/978-3-030-33730-8 ''The 21st Century Singularity and Global Futures. A Big History Perspective''] (Springer, 2020)</ref>

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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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除了对奇点概念的普遍批评外，一些评论家还对库兹韦尔的标志性图表提出了质疑。有一种批评意见认为，这种性质的对数图表天生偏向于直线结果。其他人则认为库兹韦尔选择使用的观点存在选择偏差。例如，生物学家 pzmyers 指出，许多早期的进化“事件”是随意挑选的。

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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".<ref name="singularity3"/> He also defines his predicted date of the singularity (2045) in terms of when he expects computer-based intelligences to significantly exceed the sum total of human brainpower, writing that advances in computing before that date "will not represent the Singularity" because they do "not yet correspond to a profound expansion of our intelligence."<ref name="transformation"/>

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====Accelerating change加速变革====

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~~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.~~

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~~“技术奇点”一词反映了这种变化可能会突然发生的想法，而且很难预测由此产生的新世界将如何运作。~~

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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 mankind, 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.

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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:

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{{quote|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.<ref name=mathematical/>}}

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声称人工智能对人类友好并没有直接的进化动机。进化并没有产生人类所重视的结果的内在倾向，也没有理由期望一个任意的优化过程来促进人类所期望的结果，而不是无意中导致人工智能以一种非其创造者意图的方式行为。anderssandberg也详细阐述了这个场景，讨论了各种常见的反论点。Hugai认为，如果研究人员排除了人类稀缺的智力资源，那么他们可能就无能为力了。另一方面，人工智能是在进化的压力下发展起来的，以促进自身的生存，这一点可以超越人类。提出了一个人工智能设计，避免了一些危险，包括自欺欺人，无意识的工具行为，和奖励生成器的腐败。测试人工智能。他在2001年出版的《超级智能机器》（Super Intelligent Machines）一书倡导公众对人工智能的教育和公众对人工智能的控制。它还提出了一个简单的设计，容易腐败的奖励生成器。

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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: {{quote|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.<ref name=mathematical/>}}

一些奇点的支持者通过对过去趋势的推断，特别是那些与缩短技术进步之间差距的趋势，来论证它的必然性。在技术进步的背景下，第一次使用“奇点”一词时，[[Stanislaw Ulam]]讲述了与[[John von Neumann]]关于加速变革的谈话：{{引用}一次围绕不断加速的技术进步和人类生活方式变化的对话，这使得人类历史上出现了一些基本的奇点，超过了这些奇点，人类的事务，如我们所知，将无法继续下去。<ref name=mathematical/>}}

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=== here ===

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 shift]]s will become increasingly common, leading to "technological change so rapid and profound it represents a rupture in the fabric of human history".<ref name="Kurzweil 2001">{{Citation

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Kurzweil believes that the singularity will occur by approximately 2045.[38] His predictions differ from Vinge's in that he predicts a gradual ascent to the singularity, rather than Vinge's rapidly self�improving superhuman intelligence.

库兹韦尔声称，技术进步遵循[[指数增长]的模式，遵循他所称的“[[加速回报定律]”。库兹韦尔写道，每当技术接近障碍时，新技术就会克服它。他预测[[范式转变]将变得越来越普遍，导致“技术变革如此迅速和深刻，它代表着人类历史结构的断裂”。<ref name="Kurzweil 2001">{{Citation

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~~| first=Raymond~~

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major ~~evolutionary transitions~~" ~~in information processing~~.

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Oft-cited dangers include those commonly associated with molecular nanotechnology and genetic engineering. These threats are major issues for both singularity advocates and critics, and were the subject of Bill Joy's Wired magazine article "Why the future doesn't need us".

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~~信息处理中的”主要进化转变”。~~

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经常被引用的危险包括那些通常与分子纳米技术和基因工程有关的危险。这些威胁是奇点倡导者和批评者的主要问题，也是比尔 · 乔伊在《连线Wired》杂志上发表文章《为什么未来不需要我们Why the future doesn't need us》的主题。

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~~| last=Kurzweil~~

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~~| authorlink=Raymond Kurzweil~~

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~~| title=The Law of Accelerating Returns~~

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~~| year=2001~~

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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 Asilomar 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.

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2009年2月，在美国美国人工智能协会协会(AAAI)的主持下，Eric Horvitz 在加利福尼亚州太平洋格罗夫的 Asilomar 主持了一次由顶尖计算机科学家、人工智能研究人员和机器人专家参加的会议。其目的是讨论机器人能够自给自足并能够自己做决定这一假设可能性的潜在影响。他们讨论了计算机和机器人可以获得自主性的程度，以及他们可以在多大程度上使用这些能力来构成威胁或危险。

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~~| publisher=Lifeboat Foundation~~

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~~| url=http://lifeboat.com/ex/law.of.accelerating.returns~~

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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. One example of this is solar energy, where the Earth receives vastly more solar energy than humanity captures, so capturing more of that solar energy would hold vast promise for civilizational growth.

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~~弗兰克 · s~~ · 罗宾逊预言，一旦人类实现了一台具有人类智能的机器，科学和技术问题将会用远远超过人类智能的智力来解决和解决。他指出，人工系统能够比人类更直接地共享数据，并预测这将导致一个超级智能的全球网络，这将使人类的能力相形见绌。罗宾逊还讨论了这种智力爆发后的未来可能会有多么巨大的不同。这方面的一个例子是太阳能，地球获得的太阳能远远超过人类所获得的，因此获取更多的太阳能将为文明的发展带来巨大的希望。

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~~| accessdate=2007-08-07~~

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~~| bibcode=2008NatPh...4..507B~~

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~~| volume=4~~

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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).

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在这个递归自我改进的样例场景中，人类修改人工智能的体系结构将能够使其性能每三年翻一番，例如，在用尽所有可行的改进之前，通过30代(左)。相反，如果人工智能足够聪明，能够像人类研究人员那样修改自己的架构，那么每一代人完成一次重新设计所需的时间，将在6年内完成所有30代人的可行性(对)。

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~~| page=507~~

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~~| journal=Nature Physics~~

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In a hard takeoff scenario, an AGI 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 AGI's goals. In a soft takeoff scenario, AGI 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 AGI's development.

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在艰难起飞的场景中，AGI 会迅速自我提高，“控制”世界(可能在几个小时内) ，速度太快，无法进行重大的人为错误纠正，也无法逐步调整 AGI 的目标。在软起飞的场景中，AGI 仍然比人类要强大得多，但是在一个持续的人类互动和修正可以有效地引导 AGI 的发展的时间尺度上，它的速度与人类相似(可能在几十年左右)。

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~~| doi=10.1038/nphys1010~~

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~~| issue=7~~

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Ramez Naam argues against a hard takeoff. He has pointed 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."

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拉米兹•纳姆(Ramez Naam)反对强力起飞。他指出，我们已经看到了通过超智能(比如公司)进行的递归自我提升。例如，英特尔拥有“数以万计的人类和可能数以百万计的 CPU 核心的集体智慧... 设计更好的 CPU! ”然而，这并没有导致经济的硬性起飞，相反，它导致了摩尔定律形式的软性起飞。Naam 进一步指出，高级智能的计算复杂性可能远远大于线性，比如“创造智能大脑的难度可能是创造智能大脑的两倍多。”

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}}</ref> Kurzweil believes that the singularity will occur by approximately [[Predictions made by Raymond Kurzweil#2045: The Singularity|2045]].<ref>''The Singularity Is Near''</ref> His predictions differ from Vinge's in that he predicts a gradual ascent to the singularity, rather than Vinge's rapidly self-improving superhuman intelligence.

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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.

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J. Storrs Hall 认为，“很多常见的一夜之间硬起飞的场景都是循环的——它们似乎是在自我提升过程的起点上假设了超人类的能力” ，以便人工智能能够进行起飞所需的戏剧性的、领域一般性的改进。霍尔认为，一个初出茅庐的人工智能最好专注于它最有效的一个领域，然后在市场上购买剩余的部件，而不是自己不断地自我改进硬件、软件和基础设施，因为市场上的产品质量不断提高，人工智能很难跟上世界其他地方使用的尖端技术。

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Oft-cited dangers include those commonly associated with molecular nanotechnology and [[genetic engineering]]. These threats are major issues for both singularity advocates and critics, and were the subject of [[Bill Joy]]'s ''[[Wired (magazine)|Wired]]'' magazine article "[[Why the future doesn't need ~~us]]".<ref name=chalmers /><ref name="JoyFuture"/>~~

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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. Goerzel refers to this scenario as a "semihard takeoff".

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Ben Goertzel 同意 Hall 的建议，即一个新的人类级别的人工智能将会很好地利用它的智能来积累财富。人工智能的天赋可能会激励公司和政府将其软件推广到整个社会。戈特泽尔对五分钟的起飞持怀疑态度，但他推测五年从人类到超人级别的起飞是合理的。Goerzel 将这种情况称为“半硬起飞”。

=== Algorithm improvements算法改进 ===

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Some intelligence technologies, like "seed AI",<ref name="Yampolskiy, Roman V 2015"/><ref name="ReferenceA"/> 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.

一些智能技术，比如“种子人工智能”，<ref name="Yampolskiy, Roman V 2015"/><ref name="ReferenceA"/> 通过修改它们的[[源代码]]，也可能不仅使自己更快，而且更高效。这些改进将使进一步的改进成为可能，从而再次使进一步的改进成为可能，以此类推。

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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."

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马克斯 · 莫尔不同意这种观点，他认为，如果只有少数几个超快的人工智能，它们不会从根本上改变世界，因为它们仍然依赖于其他人来完成事情，仍然会受到人类认知的约束。即使所有超快的人工智能都在增强智力，也不清楚为什么它们会以不连续的方式比现有的人类认知科学家在产生超人类智力方面做得更好，尽管进步的速度会加快。更进一步认为，超级智能不会在一夜之间改变世界: 超级智能需要与现有的、速度缓慢的人类系统接触，以完成对世界的物理影响。“合作、组织以及将想法转化为实际变化的需要，将确保所有旧规则不会在一夜之间甚至几年之内被抛弃。”

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递归自改进算法集的机制在两个方面不同于原始计算速度的提高。首先，它不需要外部影响：设计更快硬件的机器仍然需要人类来创建改进的硬件，或者对工厂进行适当的编程。

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In his 2005 book, The Singularity is Near, Kurzweil suggests that medical advances would allow people to protect their bodies from the effects of aging, making the life expectancy limitless. Kurzweil argues that the technological advances in medicine would allow us to continuously repair and replace defective components in our bodies, prolonging life to an undetermined age. Kurzweil further buttresses his argument by discussing current bio-engineering advances. Kurzweil suggests somatic gene therapy; after synthetic viruses with specific genetic information, the next step would be to apply this technology to gene therapy, replacing human DNA with synthesized genes.

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在他2005年出版的《奇点迫近书中，Kurzweil 提出，医学的进步将使人们能够保护自己的身体免受衰老的影响，从而使人的寿命无限。库兹韦尔认为，医学技术的进步将使我们能够不断地修复和替换身体中有缺陷的组件，从而延长寿命，直到不确定的年龄。库兹韦尔通过讨论当前生物工程的进展进一步支持他的论点。库兹韦尔建议进行体细胞基因治疗; 在合成具有特定基因信息的病毒之后，下一步将把这项技术应用于基因治疗，用合成基因取代人类 DNA。

Second, as with [[Vernor Vinge]]’s conception of the singularity, it is much harder to predict the outcome. 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.<ref name="yudkowsky">{{cite web|author=Eliezer S. Yudkowsky |url=http://yudkowsky.net/singularity/power |title=Power of Intelligence |publisher=Yudkowsky |accessdate=2011-09-09}}</ref>

第二，和[[Vernor Vinge]]关于奇点的概念一样，预测结果要困难得多。虽然速度的提高似乎与人类的智能只是数量上的区别，但实际的算法改进在质量上是不同的。[[Eliezer Yudkowsky]]将其与人类智能带来的变化相比较：人类改变世界的速度比进化速度快数千倍，而且方式完全不同。同样地，生命的进化与以前的地质变化率有着巨大的背离和加速，而智能的提高可能会使变化再次变得不同<ref name="yudkowsky">{{cite web|author=Eliezer S. Yudkowsky |url=http://yudkowsky.net/singularity/power |title=Power of Intelligence |publisher=Yudkowsky |accessdate=2011-09-09}}</ref>

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K. Eric Drexler, one of the founders of nanotechnology, postulated cell repair devices, including ones operating within cells and utilizing as yet hypothetical biological machines, in his 1986 book Engines of Creation.

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K、埃里克·德雷克斯勒K. Eric Drexler，纳米技术的创始人之一，在他1986年出版的《创造的引擎》一书中提出了假设的细胞修复装置，包括在细胞内运作并利用假设的生物机器的装置。

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 not be invariant under self-improvement, potentially causing the AI to optimise for something other than what was originally intended.<ref name="selfawaresystems">[http://selfawaresystems.com/2007/11/30/paper-on-the-basic-ai-drives/ Omohundro, Stephen M., "The Basic AI Drives." Artificial General Intelligence, 2008 proceedings of the First AGI Conference, eds. Pei Wang, Ben Goertzel, and Stan Franklin. Vol. 171. Amsterdam: IOS, 2008 ]</ref><ref name="kurzweilai">{{cite web|url=http://www.kurzweilai.net/artificial-general-intelligence-now-is-the-time |title=Artificial General Intelligence: Now Is the Time |publisher=KurzweilAI |accessdate=2011-09-09}}</ref> Secondly, AIs could compete for the same scarce resources mankind uses to survive.<ref name="selfawaresystems.com">[http://selfawaresystems.com/2007/10/05/paper-on-the-nature-of-self-improving-artificial-intelligence/ Omohundro, Stephen M., "The Nature of Self-Improving Artificial Intelligence." Self-Aware Systems. 21 Jan. 2008. Web. 07 Jan. 2010.]</ref><ref>{{cite book|last1=Barrat|first1=James|title=Our Final Invention|year=2013|publisher=St. Martin's Press|location=New York|isbn=978-0312622374|pages=78–98|edition=First|chapter=6, "Four Basic Drives"|title-link=Our Final Invention}}</ref>

智能爆炸奇点源于一组递归的自我改进算法，这有着巨大的危险。首先，人工智能的目标结构在自我完善的情况下可能不是一成不变的，这可能会导致人工智能对原本计划之外的东西进行优化。<ref name="selfawaresystems">[http://selfawaresystems.com/2007/11/30/paper-on-the-basic-ai-drives/ Omohundro, Stephen M., "The Basic AI Drives." Artificial General Intelligence, 2008 proceedings of the First AGI Conference, eds. Pei Wang, Ben Goertzel, and Stan Franklin. Vol. 171. Amsterdam: IOS, 2008 ]</ref><ref name="kurzweilai">{{cite web|url=http://www.kurzweilai.net/artificial-general-intelligence-now-is-the-time |title=Artificial General Intelligence: Now Is the Time |publisher=KurzweilAI |accessdate=2011-09-09}}</ref>第二，人工智能可以竞争人类赖以生存的稀缺资源。<ref name="selfawaresystems.com">[http://selfawaresystems.com/2007/10/05/paper-on-the-nature-of-self-improving-artificial-intelligence/ Omohundro, Stephen M., "The Nature of Self-Improving Artificial Intelligence." Self-Aware Systems. 21 Jan. 2008. Web. 07 Jan. 2010.]</ref><ref>{{cite book|last1=Barrat|first1=James|title=Our Final Invention|year=2013|publisher=St. Martin's Press|location=New York|isbn=978-0312622374|pages=78–98|edition=First|chapter=6, "Four Basic Drives"|title-link=Our Final Invention}}</ref>

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According to Richard Feynman, it was his former graduate student and collaborator Albert Hibbs who originally suggested to him (circa 1959) the idea of a medical use for Feynman's theoretical micromachines. Hibbs suggested that certain repair machines might one day be reduced in size to the point that it would, in theory, be possible to (as Feynman put it) "swallow the doctor". The idea was incorporated into Feynman's 1959 essay There's Plenty of Room at the Bottom.

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据理查德 · 费曼说，正是他以前的研究生兼合作者阿尔伯特 · 希布斯(Albert Hibbs)最初(大约在1959年)向他提出了费曼理论微型机器的医学用途的想法。希布斯建议，某些维修机器可能有一天会缩小到理论上可以(如费曼所说)“吞下医生”的程度。这个想法被纳入了费曼1959年的文章有足够的空间在底部。

While not actively malicious, there is no reason to think that AIs would actively promote human goals unless they could be programmed as such, and if not, might use the resources currently used to support mankind to promote its own goals, causing human extinction.<ref name="kurzweilai.net">{{cite web|url=http://www.kurzweilai.net/max-more-and-ray-kurzweil-on-the-singularity-2 |title=Max More and Ray Kurzweil on the Singularity |publisher=KurzweilAI |accessdate=2011-09-09}}</ref><ref name="ReferenceB">{{cite web|url=http://singinst.org/riskintro/index.html |title=Concise Summary | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09}}</ref><ref name="nickbostrom7">[http://www.nickbostrom.com/fut/evolution.html Bostrom, Nick, The Future of Human Evolution, Death and Anti-Death: Two Hundred Years After Kant, Fifty Years After Turing, ed. Charles Tandy, pp. 339–371, 2004, Ria University Press.]</ref>

虽然不是恶意的，但没有理由认为人工智能会积极促进人类目标的实现，除非这些目标可以被编程，如果不能，就可能利用目前用于支持人类的资源来促进自己的目标，从而导致人类灭绝。<ref name="kurzweilai.net">{{cite web|url=http://www.kurzweilai.net/max-more-and-ray-kurzweil-on-the-singularity-2 |title=Max More and Ray Kurzweil on the Singularity |publisher=KurzweilAI |accessdate=2011-09-09}}</ref><ref name="ReferenceB">{{cite web|url=http://singinst.org/riskintro/index.html |title=Concise Summary | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09}}</ref><ref name="nickbostrom7">[http://www.nickbostrom.com/fut/evolution.html Bostrom, Nick, The Future of Human Evolution, Death and Anti-Death: Two Hundred Years After Kant, Fifty Years After Turing, ed. Charles Tandy, pp. 339–371, 2004, Ria University Press.]</ref>

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Beyond merely extending the operational life of the physical body, Jaron Lanier argues for a form of immortality called "Digital Ascension" that involves "people dying in the flesh and being uploaded into a computer and remaining conscious".

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~~除了延长肉体的运作寿命，Jaron Lanier 还主张一种称为“数字提升”的永生形式，即“人们死于肉体，被上传到计算机中并保持清醒”。~~

[[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.<ref name=ShulmanSandberg2010>{{cite journal|last=Shulman|first=Carl|author2=Anders Sandberg |title=Implications of a Software-Limited Singularity|journal=ECAP10: VIII European Conference on Computing and Philosophy|year=2010|url=http://intelligence.org/files/SoftwareLimited.pdf|accessdate=17 May 2014|editor1-first=Klaus|editor1-last=Mainzer}}</ref> An abundance of accumulated hardware that can be unleashed once the software figures out how to use it has been called "computing overhang."<ref name=MuehlhauserSalamon2012>{{cite book|last=Muehlhauser|first=Luke|title=Singularity Hypotheses: A Scientific and Philosophical Assessment|year=2012|publisher=Springer|chapter-url=http://intelligence.org/files/IE-EI.pdf|author2=Anna Salamon |editor=Amnon Eden |editor2=Johnny Søraker |editor3=James H. Moor |editor4=Eric Steinhart|chapter=Intelligence Explosion: Evidence and Import}}</ref>

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===Criticisms危机===

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A paper by Mahendra Prasad, published in AI Magazine, asserts that the 18th-century mathematician Marquis de Condorcet was the first person to hypothesize and mathematically model an intelligence explosion and its effects on humanity.

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~~发表在《人工智能杂志》上的一篇论文声称，18世纪的数学家马奎斯·孔多塞是第一个假设和数学模拟智能爆炸及其对人类影响的人。~~

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.<ref name="dreyfus"/>

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{{quote|... 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. ...<ref name="spectrum.ieee.org"/>}}

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In his 1958 obituary for John von Neumann, Ulam recalled a conversation with von Neumann about 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." For example, Kurzweil extrapolates current technological trajectories past the arrival of self-improving AI or superhuman intelligence, which Yudkowsky argues represents a tension with both I. J. Good's proposed discontinuous upswing in intelligence and Vinge's thesis on unpredictability.

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在他1958年为《约翰·冯·诺伊曼志撰写的讣告中，Ulam 回忆了他与 von Neumann 的一次对话，内容是关于“科技的不断加速进步和人类生活方式的变化，这使得人类历史上出现了一些本质奇点，而我们所知道的人类事务是不可能继续下去的。”例如，库兹韦尔推断当前的技术轨迹超越了自我完善的人工智能或超人类智能的出现，尤德科夫斯基认为这代表了与 i. j。古德提出智力的间断性提升和文奇关于不可预测性的论点。

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[[University of California, Berkeley]], [[philosophy]] professor [[John Searle]] writes:

[[加州大学伯克利分校]，[[哲学]]教授[[John Searle]]写道：

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~~Former President of the United States Barack Obama spoke about singularity in his interview to Wired in 2016:~~

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~~美国前总统巴拉克 · 奥巴马在2016年接受《连线》杂志采访时谈到了奇点:~~

{{blockquote|[Computers] have, literally ..., no [[intelligence]], no [[motivation]], no [[autonomy]], and no agency. 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. ... [T]he machinery has no beliefs, desires, [or] motivations.<ref>[[John R. Searle]], “What Your Computer Can’t Know”, ''[[The New York Review of Books]]'', 9 October 2014, p. 54.</ref>}}

{{blockquote |[计算机]从字面上讲，没有[[智能]]、没有[[动机]]、没有[[自主]]和代理。我们设计他们的行为，好像他们有某种[[心理学]]，但没有心理现实的对应过程或行为。。。[T] 机械没有信仰、欲望或动机。<ref>[[John R. Searle]], “What Your Computer Can’t Know”, ''[[The New York Review of Books]]'', 9 October 2014, p. 54.</ref>}}

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[[Martin Ford (author)|Martin Ford]] in ''The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future''<ref name="thelightsinthetunnel"/> 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."<ref name="nytimes"/>

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