“技术奇点”的版本间的差异

2020年12月21日 (一) 20:58的版本

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{{简介}技术增长变得不可控制和不可逆转的假设时间点}}

The technological singularity—also, simply, the singularity^[1]—is a hypothetical point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization.^[2]^[3] According to the most popular version of the singularity hypothesis, called intelligence explosion, 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 technological singularity—also, simply, the singularity—is a hypothetical point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization. According to the most popular version of the singularity hypothesis, called intelligence explosion, 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.

技术奇点Technological singularity——简称奇点Singularity——是一个假设的时间点，在这个时间点上，技术增长变得不可控制和不可逆转，从而导致人类文明发生无法预见的变化。根据最流行的奇点假说，称为智能爆炸，一个可升级的智能体最终将进入自我完善周期的“失控反应”，每一个新的、更智能的一代出现得越来越快，在智力上引起“爆炸”，并产生一种在质量上远远超过所有人类智力的强大的超智能。

The first use of the concept of a "singularity" in the technological context was John von Neumann.^[4] Stanislaw Ulam reports a 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".^[5] Subsequent authors have echoed this viewpoint.^[3]^[6]

The first use of the concept of a "singularity" in the technological context was John von Neumann. Stanislaw Ulam reports a 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".

“奇点”概念在技术领域的第一次使用是约翰·冯·诺依曼。Stanislaw Ulam报告了与冯·诺依曼的一次讨论，“集中在技术的加速进步和人类生活方式的变化上，这给人一种接近种族历史上某些基本奇点的表象，在这些奇点之外，我们所知的人类事务将无法继续下去”。

I. J. Good's "intelligence explosion" model predicts that a future superintelligence will trigger a singularity.^[7]

I. J. Good's "intelligence explosion" model predicts that a future superintelligence will trigger a singularity.

I. j.古德的“智能爆炸”模型预测，未来的超级智能将触发一个奇点。

The concept and the term "singularity" were popularized by Vernor Vinge in his 1993 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 2005 or after 2030.^[7]

The concept and the term "singularity" were popularized by Vernor Vinge in his 1993 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 2005 or after 2030. The consequences of the singularity and its potential benefit or harm to the human race have been intensely debated.

这个概念和术语“奇点”是由 Vernor Vinge 在他1993年的文章《即将到来的技术奇异点》中推广的，他在文中写道，这将标志着人类时代的终结，因为新的超级智能将继续自我升级，并以一种不可思议的速度在技术上进步。他写道，如果它发生在2005年之前或2030年之后，他会感到惊讶。奇点的后果及其对人类的潜在利益或伤害已经引起了激烈的争论。

Public figures such as Stephen Hawking and Elon Musk have expressed concern that full artificial intelligence (AI) could result in human extinction.^[8]^[9] The consequences of the singularity and its potential benefit or harm to the human race have been intensely debated.

Four polls of AI researchers, conducted in 2012 and 2013 by Nick Bostrom and Vincent C. Müller, suggested a median probability estimate of 50% that artificial general intelligence (AGI) would be developed by 2040–2050.

2012年和2013年，尼克 · 博斯特罗姆(Nick Bostrom)和文森特 · c · 穆勒(Vincent c. Müller)对人工智能研究人员进行了四次民意调查，结果显示，到2040年至2050年，人工通用智能(AGI)开发的概率中值估计为50% 。

Four polls of AI researchers, conducted in 2012 and 2013 by Nick Bostrom and Vincent C. Müller, suggested a median probability estimate of 50% that artificial general intelligence (AGI) would be developed by 2040–2050.^[10]^[11]

Although technological progress has been accelerating, it has been limited by the basic intelligence of the human brain, which has not, according to Paul R. Ehrlich, changed significantly for millennia. 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.

虽然技术进步一直在加速，但是它受到人类大脑基本智能的限制，据保罗 · r · 埃利希说，几千年来人类大脑并没有发生显著的变化。然而，随着计算机和其他技术能力的增强，最终可能会造出一台比人类智能得多的机器。

Background背景

Although technological progress has been accelerating, it has been limited by the basic intelligence of the human brain, which has not, according to Paul R. Ehrlich, changed significantly for millennia.^[12] 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.^[13]

虽然技术进步一直在加速，但它受到人脑基本智力的限制，而根据Paul R.Ehrlich的说法，人类大脑的基本智力在几千年来没有发生显著变化。^[12]然而，随着计算机和其他技术的日益强大，最终有可能制造出一台比人类更智能得多的机器。^[13]

If a superhuman intelligence were to be invented—either through the amplification of human intelligence or through artificial intelligence—it would bring to bear greater problem-solving and inventive skills than current humans are capable of. 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 or design an even more capable machine. This more capable machine could then go on to design a machine of yet greater capability. These iterations of 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.

如果通过扩大人类智能或人工智能来发明一种超人类智能，那么它将比现在的人类拥有更强的解决问题和创造能力。这种人工智能被称为种子人工智能，因为如果人工智能的工程能力与人类创造者的能力相匹配或超越人类，那么它就有潜力自主改进自己的软件和硬件，或者设计出更强大的机器。这台能力更强的机器可以继续设计一台能力更强的机器。这些递归自我改进的迭代可以加速，在物理定律或理论计算设置的任何上限之前，潜在地允许巨大的定性变化。据推测，经过多次迭代，这样的人工智能将远远超过人类的认知能力。

If a superhuman intelligence were to be invented—either through the amplification of human intelligence or through artificial intelligence—it would bring to bear greater problem-solving and inventive skills than current humans are capable of. Such an AI is referred to as Seed AI^[14]^[15] 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 or design an even more capable machine. This more capable machine could then go on to design a machine of yet greater capability. These iterations of 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.

如果一种超人智能是通过人类智能的放大或人工智能发明的，那么它将带来比现在人类所能具备的更大的解决问题和发明的能力。这样的人工智能被称为“种子人工智能”^[14]引用错误：没有找到与</ref>对应的<ref>标签 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.^[16] Such a difference in information processing speed could drive the singularity.^[17]

速度超级智能描述了一个人工智能，它可以做任何人类能做的事情，唯一的区别是机器运行得更快。^[18]例如，与人类相比，信息处理速度提高了100万倍，一个主观的一年将在30个物理秒内过去。^[16] Such a difference in information processing speed could drive the singularity.^[19]

Ray Kurzweil writes that, due to [[paradigm shifts, a trend of exponential growth extends Moore's law from integrated circuits to earlier transistors, vacuum tubes, relays, and electromechanical computers. He predicts that the exponential growth will continue, and that in a few decades the computing power of all computers will exceed that of ("unenhanced") human brains, with superhuman artificial intelligence appearing around the same time.]]

雷 · 库兹韦尔Ray Kurzweil写道，由于[[范式的转变，指数增长的趋势将摩尔定律从集成电路扩展到早期的晶体管、真空管、继电器和机电计算机。他预测，这种指数增长将继续下去，在几十年内，所有计算机的计算能力将超过（“未增强的”）人脑，超人人工智能将同时出现]]

Kurzweil's graph). The 7 most recent data points are all NVIDIA GPUs.]]

Kurzweil's graph).最近的7个数据点都是 NVIDIA GPU。]

Plausibility合理性

Many prominent technologists and academics dispute 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.^[20]^[21]^[22]

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 Holland、Jaron Lanier和Gordon Moore，他的摩尔定律经常被引用来支持这一概念。^[20]^[21]^[22]

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.

摩尔定律所显示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主义者汉斯·莫拉维奇在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。

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 interfaces 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.^[16]

大多数被提议的创造超人或跨人类头脑的方法分为两类：人脑的智能放大和人工智能。据推测，产生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、直接大脑-计算机接口和思维上传。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；要想不出现奇点，所有这些都必须失败。^[16]

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.

雷 · 库兹韦尔假定了一个技术变革的速度(更广泛地说，所有的进化过程)的加速收益定律。另一方面，有人认为，以21世纪奇点为参数的全球加速模式应该被描述为双曲型而不是指数型。

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.^[23] 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]}

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简单方法的“低挂果实”用尽，进一步的改进将变得越来越难找到。^[23]尽管有各种增强人类智能的推测方法，但非人类人工智能（特别是种子人工智能）是最受欢迎的选择，这些假设将促进奇异性。^{[citation needed]}

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.

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这些局限... ..。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年出现。他的预测与 Vinge 的不同之处在于，Vinge 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。

Whether or not an intelligence explosion occurs depends on three factors.^[24] 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。^[24] 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。

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".

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》杂志上发表文章《为什么未来不需要我们》的主题。

There are two logically independent, but mutually reinforcing, causes of intelligence improvements: increases in the speed of computation, and improvements to the algorithms used.^[25] The former is predicted by Moore's Law and the forecasted improvements in hardware,^[26] and is comparatively similar to previous technological advances. But there are some AI researchers模板:Who who believe software is more important than hardware.^[27]^{[citation needed]}

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。^[25] 前者由摩尔定律和硬件方面的预测改进进行预测，^[26] 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。^[28]^{[citation needed]}

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.

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。

A 2017 email survey of authors with publications at the 2015 NeurIPS and 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".^[29]

2017年对2015年 NeurIPS和 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”。^[30]

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.

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。

Speed improvements速度改进

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."

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,^[31] 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.^[32] 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."^[33]

无论对于人类智能还是人工智能，硬件改进都会提高未来硬件改进的速度。简单地说，^[31]Moore's Law认为，如果第一次速度翻倍需要18个月，第二次则需要18个主观月；或者9个外部月，之后，4个月、2个月，以此类推，走向速度奇点^[32] 速度的上限最终可能会达到，尽管还不清楚这会有多高。杰夫·霍金斯（Jeff Hawkins）曾表示，一个自我完善的计算机系统不可避免地会遇到计算能力的上限：“最终，计算机的运行速度和速度都是有限的。我们最终会在同一个地方；我们只会更快到达那里。不会有奇点。”^[33]

It is difficult to directly compare silicon-based hardware with neurons. But 模板:Harvard citation notes that computer speech recognition is approaching human capabilities, and that this capability seems to require 0.01% of the volume of the brain. This analogy suggests that modern computer hardware is within a few orders of magnitude of being as powerful as the human brain.

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。

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.}}

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

Exponential growth指数增长

Martin Ford in The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future

马丁 · 福特在《隧道中的灯光: 自动化，加速技术和未来经济》一书中

Ray Kurzweil writes that, due to paradigm shifts, a trend of exponential growth extends Moore's law from integrated circuits to earlier transistors, vacuum tubes, relays, and electromechanical computers. He predicts that the exponential growth will continue, and that in a few decades the computing power of all computers will exceed that of ("unenhanced") human brains, with superhuman artificial intelligence appearing around the same time.

[[图片：PPTMooresLawai.jpg|thumb | Ray Kurzweil写道，由于范式转换s，指数增长的趋势将摩尔定律从集成电路扩展到早期的晶体管、真空管、继电器和机电机械计算机。他预测，这种指数增长将继续下去，在几十年内，所有计算机的计算能力将超过（“未增强的”）人脑，同时出现超人人工智能

An updated version of Moore's law over 120 Years (based on Kurzweil's graph). The 7 most recent data points are all NVIDIA GPUs.

[[资料图：摩尔超过120的定律年.png|拇指|左|摩尔定律120年的更新版本（基于 Kurzweil's 图形）。最近的7个数据点都是 Nvidia GPU.]]

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.

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。

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^[34] 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^[35]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。

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."

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。”

Ray Kurzweil postulates a law of accelerating returns in which the speed of technological change (and more generally, all evolutionary processes^[36]) 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.^[37] 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.^[38] 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.^[39]

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^[36]）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。^[38] 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而不是指数型^[40]

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.

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。

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".^[41] 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."^[42]

Kurzweil将“奇点”一词保留为人工智能的快速增长（与其他技术相反），他举例写道，“奇点将使我们超越我们生物身体和大脑的这些限制。。。在奇点之后，人类和机器之间将没有区别。^[43]他还将他预测的奇点日期（2045年）定义为，他预计基于计算机的智能将大大超过人类脑力总和，在那之前写下计算技术的进步“不会代表奇点”，因为它们“还不符合我们智力的深刻扩展”。^[42]

Accelerating change加速变革

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.

“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。

文件:ParadigmShiftsFrr15Events.svg

According to Kurzweil, his logarithmic graph of 15 lists of paradigm shifts for key historic events shows an exponential trend

[[图片：ParadigmShiftsFrr15Events.svg|thumb |根据Kurzweil的说法，他对关键的历史事件的15个范式转移列表的对数图显示了指数趋势]]

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.

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。

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: /* Styling for Template:Quote */ .templatequote { overflow: hidden; margin: 1em 0; padding: 0 40px; } .templatequote .templatequotecite {

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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。^[5]}}

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".引用错误：没有找到与</ref>对应的<ref>标签 Kurzweil believes that the singularity will occur by approximately 2045.^[44] 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.

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.

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。

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".^[6]^[45]

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".

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

Some intelligence technologies, like "seed AI",^[14]^[15] 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”，^[14]^[15] 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。

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."

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。”

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.^{[citation needed]} An AI rewriting its own source code could do so while contained in an AI box.

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。

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.

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.^[46]

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^[46]

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.

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.^[47]^[48] Secondly, AIs could compete for the same scarce resources mankind uses to survive.^[49]^[50]

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。^[47]^[48]第二，人工智能可以竞争人类赖以生存的稀缺资源。^[49]^[51]

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.

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.^[52]^[53]^[54]

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。^[52]^[53]^[54]

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".

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.^[55] An abundance of accumulated hardware that can be unleashed once the software figures out how to use it has been called "computing overhang."^[56]

Carl Shulman和Anders Sandberg认为，算法改进可能是奇点的限制因素；虽然硬件效率趋于稳步提高，但软件创新更具不可预测性，可能会受到连续、累积研究的限制。他们认为，在软件受限奇点的情况下，智能爆炸实际上比硬件受限奇点更可能发生，因为在软件有限的情况下，一旦开发出人类水平的人工智能，它可以在非常快的硬件上连续运行，廉价硬件的丰富将使人工智能研究不那么受限制。^[55]一旦软件知道如何使用，大量积累的硬件可以释放出来，这被称为“计算过剩”^[56]

Criticisms危机

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.

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.^[57]

一些批评家，如哲学家Hubert Dreyfus断言计算机或机器无法实现人类智能，而其他人，如物理学家Stephen Hawking，则认为如果最终结果相同，那么智力的定义就无关紧要。^[57]

An early description of the idea was made in John Wood Campbell Jr.'s 1932 short story "The last evolution".

早在1932年约翰·W·坎贝尔的短篇小说《最后的进化》中就对这个想法进行了描述。

Psychologist Steven Pinker stated in 2008:

心理学家Steven Pinker在2008年指出：

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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.

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。

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：

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

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:

[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.^[58]

[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。^[59]

Martin Ford in The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future^[60] 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."^[61]

Martin Ford在“隧道中的灯光：自动化、加速技术和未来经济”^[62]提出了一个“技术悖论”，即在奇点出现之前，经济体中的大多数日常工作都将自动化，因为这需要的技术水平低于奇点。这将导致大规模的失业和消费者需求的骤降，这反过来又会破坏投资于实现奇点所需技术的动力。取代工作越来越不再局限于传统上被认为是“例行公事”的工作。^[61]

Theodore Modis^[63]^[64] and Jonathan Huebner^[65] 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.^[66] While Kurzweil used Modis' resources, and Modis' work was around accelerating change, Modis distanced himself from Kurzweil's thesis of a "technological singularity", claiming that it lacks scientific rigor.^[64]

Theodore Modis^[67]^[43]和Jonathan Huebner^[68]认为技术创新的速度不仅停止上升，而且现在实际上在下降。这种下降的证据是计算机时钟速率的增长正在放缓，尽管摩尔关于电路密度指数增长的预测仍然成立。这是由于芯片产生过多的热量，当以较高的速度运行时，这些热量不能迅速散去，以防止芯片熔化。在未来，由于更节能的CPU设计和多单元处理器，速度的提高可能成为可能。^[66]虽然库兹韦尔利用了莫迪斯的资源，而莫迪斯的工作是围绕加速变革展开的，但莫迪斯却与库兹韦尔的“技术奇点”理论保持距离，声称该理论缺乏科学严谨性。^[64]

In a detailed empirical accounting, The Progress of Computing, William Nordhaus argued that, prior to 1940, computers followed the much slower growth of a traditional industrial economy, thus rejecting extrapolations of Moore's law to 19th-century computers.^[69]

在一份详细的实证会计“计算的进步”中，William Nordhaus认为，在1940年以前，计算机遵循传统工业经济增长缓慢的趋势，因此拒绝了摩尔定律对19世纪计算机的推断。^[70]

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.^[71]

在2007年的一篇论文中，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。^[72]

Paul Allen argued the opposite of accelerating returns, the complexity brake;^[22] 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,^[73] a law of diminishing returns. The number of patents per thousand peaked in the period from 1850 to 1900, and has been declining since.^[65] The growth of complexity eventually becomes self-limiting, and leads to a widespread "general systems collapse".

Paul Allen认为，与加速回报相反的是复杂性制动器；^[74]科学在理解智力方面取得的进展越多，取得额外进展就越困难。一项对专利数量的研究表明，人类的创造力并没有表现出加速的回报，但事实上，正如Joseph Tainter在他的《复杂社会的崩溃》中所指出的那样，^[73][[收益递减]定律。每千件专利的数量在1850年至1900年期间达到顶峰，此后一直在下降。^[65]

↑ Cadwalladr, Carole (2014). "Are the robots about to rise? Google's new director of engineering thinks so…" The Guardian. Guardian News and Media Limited.
↑ "Collection of sources defining "singularity"". singularitysymposium.com. Retrieved 17 April 2019.
↑ ^3.0 ^3.1 Eden, Amnon H.; Moor, James H. (2012). Singularity hypotheses: A Scientific and Philosophical Assessment. Dordrecht: Springer. pp. 1–2. ISBN 9783642325601.
↑ The Technological Singularity by Murray Shanahan, (MIT Press, 2015), page 233
↑ ^5.0 ^5.1 引用错误：无效<ref>标签；未给name属性为mathematical的引用提供文字
↑ ^6.0 ^6.1 Chalmers, David (2010). "The singularity: a philosophical analysis". Journal of Consciousness Studies. 17 (9–10): 7–65.
↑ ^7.0 ^7.1 Vinge, Vernor. "The Coming Technological Singularity: How to Survive in the Post-Human Era", in Vision-21: Interdisciplinary Science and Engineering in the Era of Cyberspace, G. A. Landis, ed., NASA Publication CP-10129, pp. 11–22, 1993.
↑ Sparkes, Matthew (13 January 2015). "Top scientists call for caution over artificial intelligence". The Telegraph (UK). Retrieved 24 April 2015.
↑ "Hawking: AI could end human race". BBC. 2 December 2014. Retrieved 11 November 2017.
↑ Khatchadourian, Raffi (16 November 2015). "The Doomsday Invention". The New Yorker. Retrieved 31 January 2018.
↑ Müller, V. C., & Bostrom, N. (2016). "Future progress in artificial intelligence: A survey of expert opinion". In V. C. Müller (ed): Fundamental issues of artificial intelligence (pp. 555–572). Springer, Berlin. http://philpapers.org/rec/MLLFPI
↑ ^12.0 ^12.1 Ehrlich, Paul. The Dominant Animal: Human Evolution and the Environment
↑ ^13.0 ^13.1 Superbrains born of silicon will change everything. -{zh-cn:互联网档案馆; zh-tw:網際網路檔案館; zh-hk:互聯網檔案館;}-的存檔，存档日期August 1, 2010，.
↑ ^14.0 ^14.1 ^14.2 ^14.3 Yampolskiy, Roman V. "Analysis of types of self-improving software." Artificial General Intelligence. Springer International Publishing, 2015. 384-393.
↑ ^15.0 ^15.1 ^15.2 Eliezer Yudkowsky. General Intelligence and Seed AI-Creating Complete Minds Capable of Open-Ended Self-Improvement, 2001
↑ ^16.0 ^16.1 ^16.2 ^16.3 "What is the Singularity? | Singularity Institute for Artificial Intelligence". Singinst.org. Archived from the original on 2011-09-08. Retrieved 2011-09-09.
↑ David J. Chalmers (2016). "The Singularity". Science Fiction and Philosophy. John Wiley \& Sons, Inc. pp. 171–224. doi:10.1002/9781118922590.ch16. ISBN 9781118922590.
↑ Kaj Sotala and Roman Yampolskiy (2017). "Risks of the Journey to the Singularity". The Technological Singularity. The Frontiers Collection. Springer Berlin Heidelberg. pp. 11–23. doi:10.1007/978-3-662-54033-6_2. ISBN 978-3-662-54031-2.
↑ David J. Chalmers (2016). "The Singularity". Science Fiction and Philosophy. John Wiley \& Sons, Inc. pp. 171–224. doi:10.1002/9781118922590.ch16. ISBN 9781118922590.
↑ ^20.0 ^20.1 引用错误：无效<ref>标签；未给name属性为spectrum.ieee.org的引用提供文字
↑ ^21.0 ^21.1 引用错误：无效<ref>标签；未给name属性为ieee的引用提供文字
↑ ^22.0 ^22.1 ^22.2 引用错误：无效<ref>标签；未给name属性为Allen的引用提供文字
↑ ^23.0 ^23.1 Hanson, Robin (1998). "Some Skepticism". Retrieved April 8, 2020.
↑ ^24.0 ^24.1 David Chalmers John Locke Lecture, 10 May, Exam Schools, Oxford, Presenting a philosophical analysis of the possibility of a technological singularity or "intelligence explosion" resulting from recursively self-improving AI -{zh-cn:互联网档案馆; zh-tw:網際網路檔案館; zh-hk:互聯網檔案館;}-的存檔，存档日期2013-01-15..
↑ ^25.0 ^25.1 The Singularity: A Philosophical Analysis, David J. Chalmers
↑ ^26.0 ^26.1 "ITRS" (PDF). Archived from the original (PDF) on 2011-09-29. Retrieved 2011-09-09.
↑ Kulkarni, Ajit (2017-12-12). "Why Software Is More Important Than Hardware Right Now". Chronicled. Retrieved 2019-02-23.
↑ Kulkarni, Ajit (2017-12-12). "Why Software Is More Important Than Hardware Right Now". Chronicled. Retrieved 2019-02-23.
↑ Grace, Katja; Salvatier, John; Dafoe, Allan; Zhang, Baobao; Evans, Owain (24 May 2017). "When Will AI Exceed Human Performance? Evidence from AI Experts". arXiv:1705.08807 [cs.AI].
↑ Grace, Katja; Salvatier, John; Dafoe, Allan; Zhang, Baobao; Evans, Owain (24 May 2017). "When Will AI Exceed Human Performance? Evidence from AI Experts". arXiv:1705.08807 [cs.AI].
↑ ^31.0 ^31.1 Siracusa, John (2009-08-31). "Mac OS X 10.6 Snow Leopard: the Ars Technica review". Arstechnica.com. Retrieved 2011-09-09.
↑ ^32.0 ^32.1 Eliezer Yudkowsky, 1996 "Staring into the Singularity"
↑ ^33.0 ^33.1 "Tech Luminaries Address Singularity". IEEE Spectrum. 1 June 2008.
↑ Moravec, Hans (1999). Robot: Mere Machine to Transcendent Mind. Oxford U. Press. p. 61. ISBN 978-0-19-513630-2. https://books.google.com/books?id=fduW6KHhWtQC&pg=PA61.
↑ Moravec, Hans (1999). Robot: Mere Machine to Transcendent Mind. Oxford U. Press. p. 61. ISBN 978-0-19-513630-2. https://books.google.com/books?id=fduW6KHhWtQC&pg=PA61.
↑ ^36.0 ^36.1 引用错误：无效<ref>标签；未给name属性为google的引用提供文字
↑ 引用错误：无效<ref>标签；未给name属性为singularity2的引用提供文字
↑ ^38.0 ^38.1 "The World's Technological Capacity to Store, Communicate, and Compute Information", Martin Hilbert and Priscila López (2011), Science, 332(6025), 60–65; free access to the article through here: martinhilbert.net/WorldInfoCapacity.html
↑ The 21st Century Singularity and Global Futures. A Big History Perspective (Springer, 2020)
↑ The 21st Century Singularity and Global Futures. A Big History Perspective (Springer, 2020)
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↑ ^42.0 ^42.1 引用错误：无效<ref>标签；未给name属性为transformation的引用提供文字
↑ ^43.0 ^43.1 引用错误：无效<ref>标签；未给name属性为“Singularity的引用提供文字
↑ The Singularity Is Near
↑ 引用错误：无效<ref>标签；未给name属性为JoyFuture的引用提供文字
↑ ^46.0 ^46.1 Eliezer S. Yudkowsky. "Power of Intelligence". Yudkowsky. Retrieved 2011-09-09.
↑ ^47.0 ^47.1 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
↑ ^48.0 ^48.1 "Artificial General Intelligence: Now Is the Time". KurzweilAI. Retrieved 2011-09-09.
↑ ^49.0 ^49.1 Omohundro, Stephen M., "The Nature of Self-Improving Artificial Intelligence." Self-Aware Systems. 21 Jan. 2008. Web. 07 Jan. 2010.
↑ Barrat, James (2013). "6, "Four Basic Drives"". Our Final Invention (First ed.). New York: St. Martin's Press. pp. 78–98. ISBN 978-0312622374.
↑ Barrat, James (2013). "6, "Four Basic Drives"". Our Final Invention (First ed.). New York: St. Martin's Press. pp. 78–98. ISBN 978-0312622374.
↑ ^52.0 ^52.1 "Max More and Ray Kurzweil on the Singularity". KurzweilAI. Retrieved 2011-09-09.
↑ ^53.0 ^53.1 "Concise Summary | Singularity Institute for Artificial Intelligence". Singinst.org. Retrieved 2011-09-09.
↑ ^54.0 ^54.1 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.
↑ ^55.0 ^55.1 Shulman, Carl; Anders Sandberg (2010). Mainzer, Klaus (ed.). "Implications of a Software-Limited Singularity" (PDF). ECAP10: VIII European Conference on Computing and Philosophy. Retrieved 17 May 2014.
↑ ^56.0 ^56.1 Muehlhauser, Luke; Anna Salamon (2012). "Intelligence Explosion: Evidence and Import". In Amnon Eden. Singularity Hypotheses: A Scientific and Philosophical Assessment. Springer. http://intelligence.org/files/IE-EI.pdf.
↑ ^57.0 ^57.1 引用错误：无效<ref>标签；未给name属性为dreyfus的引用提供文字
↑ John R. Searle, “What Your Computer Can’t Know”, The New York Review of Books, 9 October 2014, p. 54.
↑ John R. Searle, “What Your Computer Can’t Know”, The New York Review of Books, 9 October 2014, p. 54.
↑ 引用错误：无效<ref>标签；未给name属性为thelightsinthetunnel的引用提供文字
↑ ^61.0 ^61.1 引用错误：无效<ref>标签；未给name属性为nytimes的引用提供文字
↑ 引用错误：无效<ref>标签；未给name属性为“thelightsinthetunnel”的引用提供文字
↑ 引用错误：无效<ref>标签；未给name属性为google13的引用提供文字
↑ ^64.0 ^64.1 ^64.2 引用错误：无效<ref>标签；未给name属性为Singularity Myth的引用提供文字
↑ ^65.0 ^65.1 ^65.2 引用错误：无效<ref>标签；未给name属性为technological14的引用提供文字
↑ ^66.0 ^66.1 引用错误：无效<ref>标签；未给name属性为cnet的引用提供文字
↑ 引用错误：无效<ref>标签；未给name属性为“google13”的引用提供文字
↑ 引用错误：无效<ref>标签；未给name属性为“technology14”的引用提供文字
↑ Nordhaus, William D. (2007). "Two Centuries of Productivity Growth in Computing". The Journal of Economic History. 67: 128–159. CiteSeerX 10.1.1.330.1871. doi:10.1017/S0022050707000058.
↑ Nordhaus, William D. (2007). "Two Centuries of Productivity Growth in Computing". The Journal of Economic History. 67: 128–159. CiteSeerX 10.1.1.330.1871. doi:10.1017/S0022050707000058.
↑ Schmidhuber, Jürgen. "New millennium AI and the convergence of history." Challenges for computational intelligence. Springer Berlin Heidelberg, 2007. 15–35.
↑ Schmidhuber, Jürgen. "New millennium AI and the convergence of history." Challenges for computational intelligence. Springer Berlin Heidelberg, 2007. 15–35.
↑ ^73.0 ^73.1 引用错误：无效<ref>标签；未给name属性为university的引用提供文字
↑ 引用错误：无效<ref>标签；未给name属性为“Allen”的引用提供文字

[1] Cadwalladr, Carole (2014). "Are the robots about to rise? Google's new director of engineering thinks so…" The Guardian. Guardian News and Media Limited.

[2] "Collection of sources defining "singularity"". singularitysymposium.com. Retrieved 17 April 2019.

[Singularity_hypotheses-3] 3.0 ^3.1 Eden, Amnon H.; Moor, James H. (2012). Singularity hypotheses: A Scientific and Philosophical Assessment. Dordrecht: Springer. pp. 1–2. ISBN 9783642325601.

[4] The Technological Singularity by Murray Shanahan, (MIT Press, 2015), page 233

[mathematical-5] 5.0 ^5.1 引用错误：无效<ref>标签；未给name属性为mathematical的引用提供文字

[chalmers-6] 6.0 ^6.1 Chalmers, David (2010). "The singularity: a philosophical analysis". Journal of Consciousness Studies. 17 (9–10): 7–65.

[vinge1993-7] 7.0 ^7.1 Vinge, Vernor. "The Coming Technological Singularity: How to Survive in the Post-Human Era", in Vision-21: Interdisciplinary Science and Engineering in the Era of Cyberspace, G. A. Landis, ed., NASA Publication CP-10129, pp. 11–22, 1993.

[8] Sparkes, Matthew (13 January 2015). "Top scientists call for caution over artificial intelligence". The Telegraph (UK). Retrieved 24 April 2015.

[9] "Hawking: AI could end human race". BBC. 2 December 2014. Retrieved 11 November 2017.

[newyorker-10] Khatchadourian, Raffi (16 November 2015). "The Doomsday Invention". The New Yorker. Retrieved 31 January 2018.

[11] Müller, V. C., & Bostrom, N. (2016). "Future progress in artificial intelligence: A survey of expert opinion". In V. C. Müller (ed): Fundamental issues of artificial intelligence (pp. 555–572). Springer, Berlin. http://philpapers.org/rec/MLLFPI

[Paul_Ehrlich_June_2008-12] 12.0 ^12.1 Ehrlich, Paul. The Dominant Animal: Human Evolution and the Environment

[businessweek-13] 13.0 ^13.1 Superbrains born of silicon will change everything. -{zh-cn:互联网档案馆; zh-tw:網際網路檔案館; zh-hk:互聯網檔案館;}-的存檔，存档日期August 1, 2010，.

[Yampolskiy.2C_Roman_V_2015-14] 14.0 ^14.1 ^14.2 ^14.3 Yampolskiy, Roman V. "Analysis of types of self-improving software." Artificial General Intelligence. Springer International Publishing, 2015. 384-393.

[ReferenceA-15] 15.0 ^15.1 ^15.2 Eliezer Yudkowsky. General Intelligence and Seed AI-Creating Complete Minds Capable of Open-Ended Self-Improvement, 2001

[singinst.org-16] 16.0 ^16.1 ^16.2 ^16.3 "What is the Singularity? | Singularity Institute for Artificial Intelligence". Singinst.org. Archived from the original on 2011-09-08. Retrieved 2011-09-09.

[17] David J. Chalmers (2016). "The Singularity". Science Fiction and Philosophy. John Wiley \& Sons, Inc. pp. 171–224. doi:10.1002/9781118922590.ch16. ISBN 9781118922590.

[18] Kaj Sotala and Roman Yampolskiy (2017). "Risks of the Journey to the Singularity". The Technological Singularity. The Frontiers Collection. Springer Berlin Heidelberg. pp. 11–23. doi:10.1007/978-3-662-54033-6_2. ISBN 978-3-662-54031-2.

[19] David J. Chalmers (2016). "The Singularity". Science Fiction and Philosophy. John Wiley \& Sons, Inc. pp. 171–224. doi:10.1002/9781118922590.ch16. ISBN 9781118922590.

[spectrum.ieee.org-20] 20.0 ^20.1 引用错误：无效<ref>标签；未给name属性为spectrum.ieee.org的引用提供文字

[ieee-21] 21.0 ^21.1 引用错误：无效<ref>标签；未给name属性为ieee的引用提供文字

[Allen-22] 22.0 ^22.1 ^22.2 引用错误：无效<ref>标签；未给name属性为Allen的引用提供文字

[hanson-23] 23.0 ^23.1 Hanson, Robin (1998). "Some Skepticism". Retrieved April 8, 2020.

[david_chalmers_singularity_lecture_resources_available-24] 24.0 ^24.1 David Chalmers John Locke Lecture, 10 May, Exam Schools, Oxford, Presenting a philosophical analysis of the possibility of a technological singularity or "intelligence explosion" resulting from recursively self-improving AI -{zh-cn:互联网档案馆; zh-tw:網際網路檔案館; zh-hk:互聯網檔案館;}-的存檔，存档日期2013-01-15..

[consc.net-25] 25.0 ^25.1 The Singularity: A Philosophical Analysis, David J. Chalmers

[itrs-26] 26.0 ^26.1 "ITRS" (PDF). Archived from the original (PDF) on 2011-09-29. Retrieved 2011-09-09.

[27] Kulkarni, Ajit (2017-12-12). "Why Software Is More Important Than Hardware Right Now". Chronicled. Retrieved 2019-02-23.

[28] Kulkarni, Ajit (2017-12-12). "Why Software Is More Important Than Hardware Right Now". Chronicled. Retrieved 2019-02-23.

[29] Grace, Katja; Salvatier, John; Dafoe, Allan; Zhang, Baobao; Evans, Owain (24 May 2017). "When Will AI Exceed Human Performance? Evidence from AI Experts". arXiv:1705.08807 [cs.AI].

[30] Grace, Katja; Salvatier, John; Dafoe, Allan; Zhang, Baobao; Evans, Owain (24 May 2017). "When Will AI Exceed Human Performance? Evidence from AI Experts". arXiv:1705.08807 [cs.AI].

[arstechnica-31] 31.0 ^31.1 Siracusa, John (2009-08-31). "Mac OS X 10.6 Snow Leopard: the Ars Technica review". Arstechnica.com. Retrieved 2011-09-09.

[singularity6-32] 32.0 ^32.1 Eliezer Yudkowsky, 1996 "Staring into the Singularity"

[Hawkins-33] 33.0 ^33.1 "Tech Luminaries Address Singularity". IEEE Spectrum. 1 June 2008.

[34] Moravec, Hans (1999). Robot: Mere Machine to Transcendent Mind. Oxford U. Press. p. 61. ISBN 978-0-19-513630-2. https://books.google.com/books?id=fduW6KHhWtQC&pg=PA61.

[35] Moravec, Hans (1999). Robot: Mere Machine to Transcendent Mind. Oxford U. Press. p. 61. ISBN 978-0-19-513630-2. https://books.google.com/books?id=fduW6KHhWtQC&pg=PA61.

[google-36] 36.0 ^36.1 引用错误：无效<ref>标签；未给name属性为google的引用提供文字

[singularity2-37] 引用错误：无效<ref>标签；未给name属性为singularity2的引用提供文字

[HilbertLopez2011-38] 38.0 ^38.1 "The World's Technological Capacity to Store, Communicate, and Compute Information", Martin Hilbert and Priscila López (2011), Science, 332(6025), 60–65; free access to the article through here: martinhilbert.net/WorldInfoCapacity.html

[39] The 21st Century Singularity and Global Futures. A Big History Perspective (Springer, 2020)

[40] The 21st Century Singularity and Global Futures. A Big History Perspective (Springer, 2020)

[singularity3-41] 引用错误：无效<ref>标签；未给name属性为singularity3的引用提供文字

[transformation-42] 42.0 ^42.1 引用错误：无效<ref>标签；未给name属性为transformation的引用提供文字

[.E2.80.9CSingularity-43] 43.0 ^43.1 引用错误：无效<ref>标签；未给name属性为“Singularity的引用提供文字

[44] The Singularity Is Near

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[yudkowsky-46] 46.0 ^46.1 Eliezer S. Yudkowsky. "Power of Intelligence". Yudkowsky. Retrieved 2011-09-09.

[selfawaresystems-47] 47.0 ^47.1 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

[kurzweilai-48] 48.0 ^48.1 "Artificial General Intelligence: Now Is the Time". KurzweilAI. Retrieved 2011-09-09.

[selfawaresystems.com-49] 49.0 ^49.1 Omohundro, Stephen M., "The Nature of Self-Improving Artificial Intelligence." Self-Aware Systems. 21 Jan. 2008. Web. 07 Jan. 2010.

[50] Barrat, James (2013). "6, "Four Basic Drives"". Our Final Invention (First ed.). New York: St. Martin's Press. pp. 78–98. ISBN 978-0312622374.

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[kurzweilai.net-52] 52.0 ^52.1 "Max More and Ray Kurzweil on the Singularity". KurzweilAI. Retrieved 2011-09-09.

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[Singularity_Myth-64] 64.0 ^64.1 ^64.2 引用错误：无效<ref>标签；未给name属性为Singularity Myth的引用提供文字

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@@ 第533行： / 第533行： @@
 {{Harvtxt|Berglas|2008}} 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.<ref name="nickbostrom8">Nick Bostrom, [http://www.nickbostrom.com/ethics/ai.html "Ethical Issues in Advanced Artificial Intelligence"], in ''Cognitive, Emotive and Ethical Aspects of Decision Making in Humans and in Artificial Intelligence'', Vol. 2, ed. I. Smit et al., Int. Institute of Advanced Studies in Systems Research and Cybernetics, 2003, pp. 12–17</ref><ref name="singinst">[[Eliezer Yudkowsky]]: [http://singinst.org/upload/artificial-intelligence-risk.pdf Artificial Intelligence as a Positive and Negative Factor in Global Risk] {{webarchive|url=https://web.archive.org/web/20120611190606/http://singinst.org/upload/artificial-intelligence-risk.pdf |date=2012-06-11 }}. Draft for a publication in ''Global Catastrophic Risk'' from August 31, 2006, retrieved July 18, 2011 (PDF file)</ref><ref name="singinst9">[http://www.singinst.org/blog/2007/06/11/the-stamp-collecting-device/ The Stamp Collecting Device, Nick Hay]</ref> [[Anders Sandberg]] has also elaborated on this scenario, addressing various common counter-arguments.<ref name="aleph">[http://www.aleph.se/andart/archives/2011/02/why_we_should_fear_the_paperclipper.html 'Why we should fear the Paperclipper'], 2011-02-14 entry of Sandberg's blog 'Andart'</ref> AI researcher [[Hugo de Garis]] suggests that artificial intelligences may simply eliminate the human race [[instrumental convergence|for access to scarce resources]],<ref name="selfawaresystems.com" /><ref name="selfawaresystems10">[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> and humans would be powerless to stop them.<ref name="forbes">de Garis, Hugo. [https://www.forbes.com/2009/06/18/cosmist-terran-cyborgist-opinions-contributors-artificial-intelligence-09-hugo-de-garis.html "The Coming Artilect War"], Forbes.com, 22 June 2009.</ref> Alternatively, AIs developed under evolutionary pressure to promote their own survival could outcompete humanity.<ref name="nickbostrom7" />
-{Harvtxt|Berglas|2008}声称人工智能对人类友好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。<ref name="nickbostrom8">Nick Bostrom, [http://www.nickbostrom.com/ethics/ai.html "Ethical Issues in Advanced Artificial Intelligence"], in ''Cognitive, Emotive and Ethical Aspects of Decision Making in Humans and in Artificial Intelligence'', Vol. 2, ed. I. Smit et al., Int. Institute of Advanced Studies in Systems Research and Cybernetics, 2003, pp. 12–17</ref><ref name="singinst">[[Eliezer Yudkowsky]]: [http://singinst.org/upload/artificial-intelligence-risk.pdf Artificial Intelligence as a Positive and Negative Factor in Global Risk] {{webarchive|url=https://web.archive.org/web/20120611190606/http://singinst.org/upload/artificial-intelligence-risk.pdf |date=2012-06-11 }}Draft for a publication in ''Global Catastrophic Risk'' from August 31, 2006, retrieved July 18, 2011 (PDF file)</ref><ref name="singinst9">[http://www.singinst.org/blog/2007/06/11/the-stamp-collecting-device/ The Stamp Collecting Device, Nick Hay]</ref>[[Anders Sandberg]]也详细阐述了这种情况，讨论了各种常见的反驳意见。<ref name="aleph">[http://www.aleph.se/andart/archives/2011/02/why_we_should_fear_the_paperclipper.html 'Why we should fear the Paperclipper'], 2011-02-14 entry of Sandberg's blog 'Andart'</ref>人工智能研究人员[[Hugo de Garis]]认为，人工智能可能会简单地消灭人类[[工具性融合|获取稀缺资源]]，<ref name="selfawaresystems.com" /><ref name="selfawaresystems10">[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>人类将无力阻止它们。<ref name="forbes">de Garis, Hugo. [https://www.forbes.com/2009/06/18/cosmist-terran-cyborgist-opinions-contributors-artificial-intelligence-09-hugo-de-garis.html "The Coming Artilect War"], Forbes.com, 22 June 2009.</ref>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。<ref name="nickbostrom7" />
+{{Harvtxt|Berglas|2008}}声称没有直接的进化动机促使人工智能对人类友好。进化并不倾向于产生人类所重视的结果，也没有理由期望一个任意的优化过程会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不是其创造者意图的方式行动。<ref name="nickbostrom8">Nick Bostrom, [http://www.nickbostrom.com/ethics/ai.html "Ethical Issues in Advanced Artificial Intelligence"], in ''Cognitive, Emotive and Ethical Aspects of Decision Making in Humans and in Artificial Intelligence'', Vol. 2, ed. I. Smit et al., Int. Institute of Advanced Studies in Systems Research and Cybernetics, 2003, pp. 12–17</ref><ref name="singinst">[[Eliezer Yudkowsky]]: [http://singinst.org/upload/artificial-intelligence-risk.pdf Artificial Intelligence as a Positive and Negative Factor in Global Risk] {{webarchive|url=https://web.archive.org/web/20120611190606/http://singinst.org/upload/artificial-intelligence-risk.pdf |date=2012-06-11 }}2006年8月31日“全球灾难性风险”出版物草稿，2011年7月18日检索（PDF文件）</ref><ref name="singinst9">[http://www.singinst.org/blog/2007/06/11/the-stamp-collecting-device/ The Stamp Collecting Device, Nick Hay]</ref>[[Anders Sandberg]]也详细阐述了这种情况，讨论了各种常见的反驳意见。<ref name="aleph">[http://www.aleph.se/andart/archives/2011/02/why_we_should_fear_the_paperclipper.html 'Why we should fear the Paperclipper'], 2011-02-14 entry of Sandberg's blog 'Andart'</ref>人工智能研究人员[[Hugo de Garis]]认为，人工智能可能会简单地消灭人类[[工具性融合|获取稀缺资源]]，<ref name="selfawaresystems.com" /><ref name="selfawaresystems10">[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>人类将无力阻止它们。<ref name="forbes">de Garis, Hugo. [https://www.forbes.com/2009/06/18/cosmist-terran-cyborgist-opinions-contributors-artificial-intelligence-09-hugo-de-garis.html "The Coming Artilect War"], Forbes.com, 22 June 2009.</ref>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。<ref name="nickbostrom7" />
 {{Reflist
@@ 第551行： / 第551行： @@
 {{quote|When we create the first superintelligent entity, we might make a mistake and give it goals that lead it to annihilate humankind, assuming its enormous intellectual advantage gives it the power to do so. For example, we could mistakenly elevate a subgoal to the status of a supergoal. We tell it to solve a mathematical problem, and it complies by turning all the matter in the solar system into a giant calculating device, in the process killing the person who asked the question.}}
-{{引用}当我们创建第一个超级智能实体时，我们可能会犯一个错误，给它目标，导致它毁灭人类，假设它巨大的智力优势赋予它这样做的力量。例如，我们可能会错误地将子目标提升为超级目标。我们告诉它去解决一个数学问题，然后它将太阳系中的所有物质变成一个巨大的计算装置，在这个过程中杀死了提出这个问题的人
+{{引用}当我们创建第一个超级智能实体时，我们可能会犯一个错误，给它目标，导致它毁灭人类，假设它巨大的智力优势赋予它这样做的力量。例如，我们可能会错误地将子目标提升为超级目标。我们告诉它去解决一个数学问题，然后它将太阳系中的所有物质变成一个巨大的计算装置，在这个过程中杀死了提出这个问题的人。}}
@@ 第557行： / 第557行： @@
 According to [[Eliezer Yudkowsky]], a significant problem in AI safety is that unfriendly artificial intelligence is likely to be much easier to create than friendly AI. While both require large advances in recursive optimisation process design, friendly AI also requires the ability to make goal structures invariant under self-improvement (or the AI could transform itself into something unfriendly) and a goal structure that aligns with human values and does not automatically destroy the human race. An unfriendly AI, on the other hand, can optimize for an arbitrary goal structure, which does not need to be invariant under self-modification.<ref name="singinst12">[http://singinst.org/upload/CEV.html Coherent Extrapolated Volition, Eliezer S. Yudkowsky, May 2004 ] {{webarchive|url=https://web.archive.org/web/20100815055725/http://singinst.org/upload/CEV.html |date=2010-08-15 }}</ref> {{harvtxt|Bill Hibbard|2014}} proposes an AI design that avoids several dangers including self-delusion,<ref name="JAGI2012">{{Citation| journal=Journal of Artificial General Intelligence| year=2012| volume=3| issue=1| title=Model-Based Utility Functions| first=Bill| last=Hibbard| postscript=.| doi=10.2478/v10229-011-0013-5| page=1|arxiv = 1111.3934 |bibcode = 2012JAGI....3....1H | s2cid=8434596}}</ref> unintended instrumental actions,<ref name="selfawaresystems"/><ref name="AGI-12a">[http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_56.pdf  Avoiding Unintended AI Behaviors.] Bill Hibbard. 2012 proceedings of the Fifth Conference on Artificial General Intelligence, eds. Joscha Bach, Ben Goertzel and Matthew Ikle. [http://intelligence.org/2012/12/19/december-2012-newsletter/ This paper won the Machine Intelligence Research Institute's 2012 Turing Prize for the Best AGI Safety Paper].</ref> and corruption of the reward generator.<ref name="AGI-12a"/> He also discusses social impacts of AI<ref name="JET2008">{{Citation| url=http://jetpress.org/v17/hibbard.htm| journal=Journal of Evolution and Technology| year=2008| volume=17| title=The Technology of Mind and a New Social Contract| first=Bill| last=Hibbard| postscript=.}}</ref> and testing AI.<ref name="AGI-12b">[http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_57.pdf  Decision Support for Safe AI Design|.] Bill Hibbard. 2012 proceedings of the Fifth Conference on Artificial General Intelligence, eds. Joscha Bach, Ben Goertzel and Matthew Ikle.</ref> 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.
-根据[[Eliezer Yudkowsky]]，人工智能安全的一个重要问题是，不友好的人工智能可能比友好的人工智能更容易创建。虽然两者都需要递归优化过程设计的巨大进步，但友好的人工智能也需要能够使目标结构在自我改进下保持不变（或者人工智能可以将自己转变成不友好的东西），以及一个与人类价值观相一致且不会自动毁灭人类的目标结构。另一方面，一个不友好的人工智能可以针对任意的目标结构进行优化，而目标结构不需要在自我修改下保持不变。<ref name="singinst12">[http://singinst.org/upload/CEV.html Coherent Extrapolated Volition, Eliezer S. Yudkowsky, May 2004 ] {{webarchive|url=https://web.archive.org/web/20100815055725/http://singinst.org/upload/CEV.html |date=2010-08-15 }}</ref>{{harvxt | Bill Hibbard | 2014}提出了一种避免包括自欺欺人在内的危险的人工智能设计，<ref name="JAGI2012">{{Citation| journal=Journal of Artificial General Intelligence| year=2012| volume=3| issue=1| title=Model-Based Utility Functions| first=Bill| last=Hibbard| postscript=.| doi=10.2478/v10229-011-0013-5| page=1|arxiv = 1111.3934 |bibcode = 2012JAGI....3....1H | s2cid=8434596}}</ref>意外的工具性行为，<ref name="selfawaresystems"/><ref name="AGI-12a">[http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_56.pdf  Avoiding Unintended AI Behaviors.] Bill Hibbard. 2012 proceedings of the Fifth Conference on Artificial General Intelligence, eds. Joscha Bach, Ben Goertzel and Matthew Ikle. [http://intelligence.org/2012/12/19/december-2012-newsletter/ This paper won the Machine Intelligence Research Institute's 2012 Turing Prize for the Best AGI Safety Paper].</ref> 以及奖励机制的腐败。<ref name="AGI-12a"/>他还讨论了人工智能的社会影响<ref name="JET2008">{{Citation| url=http://jetpress.org/v17/hibbard.htm| journal=Journal of Evolution and Technology| year=2008| volume=17| title=The Technology of Mind and a New Social Contract| first=Bill| last=Hibbard| postscript=.}}</ref>和测试人工智能。<ref name="AGI-12b">[http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_57.pdf  Decision Support for Safe AI Design|.] Bill Hibbard. 2012 proceedings of the Fifth Conference on Artificial General Intelligence, eds. Joscha Bach, Ben Goertzel and Matthew Ikle.</ref>他在2001年出版的新书“[[超级智能机器]]”提倡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。
+按照[[Eliezer Yudkowsky]]的观点，人工智能安全的一个重要问题是，不友好的人工智能可能比友好的人工智能更容易创建。虽然两者都需要递归优化过程设计的巨大进步，但友好的人工智能也需要能够使目标结构在自我改进下保持不变（或者人工智能可以将自己转变成不友好的东西），以及一个与人类价值观相一致且不会自动毁灭人类的目标结构。另一方面，一个不友好的人工智能可以针对任意的目标结构进行优化，而目标结构不需要在自我修改下保持不变。<ref name="singinst12">[http://singinst.org/upload/CEV.html Coherent Extrapolated Volition, Eliezer S. Yudkowsky, May 2004 ] {{webarchive|url=https://web.archive.org/web/20100815055725/http://singinst.org/upload/CEV.html |date=2010-08-15 }}</ref>{{harvxt | Bill Hibbard | 2014}提出了一种避免包括自欺欺人在内的危险的人工智能设计，<ref name="JAGI2012">{{Citation| journal=Journal of Artificial General Intelligence| year=2012| volume=3| issue=1| title=Model-Based Utility Functions| first=Bill| last=Hibbard| postscript=.| doi=10.2478/v10229-011-0013-5| page=1|arxiv = 1111.3934 |bibcode = 2012JAGI....3....1H | s2cid=8434596}}</ref>意外的工具性行为，<ref name="selfawaresystems"/><ref name="AGI-12a">[http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_56.pdf  Avoiding Unintended AI Behaviors.] Bill Hibbard. 2012 proceedings of the Fifth Conference on Artificial General Intelligence, eds. Joscha Bach, Ben Goertzel and Matthew Ikle. [http://intelligence.org/2012/12/19/december-2012-newsletter/ This paper won the Machine Intelligence Research Institute's 2012 Turing Prize for the Best AGI Safety Paper].</ref> 以及奖励机制的腐败。<ref name="AGI-12a"/>他还讨论了人工智能的社会影响<ref name="JET2008">{{Citation| url=http://jetpress.org/v17/hibbard.htm| journal=Journal of Evolution and Technology| year=2008| volume=17| title=The Technology of Mind and a New Social Contract| first=Bill| last=Hibbard| postscript=.}}</ref>和人工智能测试。<ref name="AGI-12b">[http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_57.pdf  Decision Support for Safe AI Design|.] Bill Hibbard. 2012 proceedings of the Fifth Conference on Artificial General Intelligence, eds. Joscha Bach, Ben Goertzel and Matthew Ikle.</ref>他在2001年出版的新书“[[超级智能机器]]”提倡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。
 ===Next step of sociobiological evolution社会生物进化的下一步===
@@ 第575行： / 第575行： @@
 While the technological singularity is usually seen as a sudden event, some scholars argue the current speed of change already fits this description.{{citation needed|date=April 2018}}
-虽然技术奇点通常被视为一个突发事件，但一些学者认为目前的变化速度已经符合这种描述
+虽然技术奇点通常被视为一个突发事件，但一些学者认为目前的变化速度已经符合这种描述。{{citation needed|date=April 2018}}
 In addition, some argue that we are already in the midst of a [[The Major Transitions in Evolution|major evolutionary transition]] that merges technology, biology, and society. Digital technology has infiltrated the fabric of human society to a degree of indisputable and often life-sustaining dependence.
+此外，有人认为，我们已经处在一个融合了技术、生物学和社会的[[进化中的突变|进化突变]]的中间。数字技术已经渗透到人类社会的结构中，达到了无可争辩的程度，而且常常是维持生命的依赖。
-此外，有人认为，我们已经处在一个融合了技术、生物学和社会的[[进化中的主要转变|主要进化转变]]的中间。数字技术已经渗透到人类社会的结构中，达到了无可争辩的程度，而且常常是维持生命的依赖。
 A 2016 article in ''[[Trends in Ecology & Evolution]]'' argues that "humans already embrace fusions of biology and technology. We spend most of our waking time communicating through digitally mediated channels... we trust [[artificial intelligence]] with our lives through [[Anti-lock braking system|antilock braking in cars]] and [[autopilot]]s in planes... With one in three marriages in America beginning online, digital algorithms are also taking a role in human pair bonding and reproduction".
+年发表在“[[Trends in Ecology&Evolution]]”的一篇文章认为，“人类已经接受了生物和技术的融合。我们醒着的大部分时间都是通过数字媒介渠道进行交流的。。。我们相信[[人工智能]]通过[[防抱死制动系统|汽车中的防抱死制动]]和飞机上的[[自动驾驶仪]]来生活。。。在美国，三分之一的婚姻都是在网络上开始的，数字算法也在人类配对和繁殖中发挥了作用”。
-年发表在“[[Trends in Ecology&Evolution]]”的一篇文章认为，“人类已经接受了生物和技术的融合。我们醒着的大部分时间都是通过数字媒介渠道进行交流的。。。我们相信[[人工智能]]通过[[防抱死制动系统|汽车中的防抱死制动]]和飞机上的[[自动驾驶仪]]来生活。。。在美国，三分之一的婚姻都是在网络上开始的，数字算法也在人类配对和繁殖中发挥了作用。
@@ 第600行： / 第593行： @@
 The digital information created by humans has reached a similar magnitude to biological information in the biosphere. Since the 1980s, the quantity of digital information stored has doubled about every 2.5 years, reaching about 5 [[zettabyte]]s in 2014 (5{{e|21}} bytes).{{Citation needed|date=April 2019}}
+人类创造的数字信息已经达到了与生物圈中生物信息相似的程度。自20世纪80年代以来，存储的数字信息量大约每2.5年翻一番，2014年达到约5[[zettabyte]]（5{e | 21}}字节）。{{Citation needed|date=April 2019}}
-人类创造的数字信息已经达到了与生物圈中生物信息相似的程度。自20世纪80年代以来，存储的数字信息量大约每2.5年翻一番，2014年达到约5[[zettabyte]]（5{e | 21}}字节）
@@ 第610行： / 第599行： @@
 在生物学方面，地球上有72亿人，每个人的基因组有62亿个核苷酸。由于一个字节可以编码四个核苷酸对，地球上每个人类的个体基因组可以编码大约1{e | 19}字节。2014年，数字领域存储的信息是这个数字领域的500倍（见图）。据估计，地球上所有细胞所含的DNA总量约为5.3{e | 37}碱基对，相当于1.325{e | 37}字节的信息。
 If growth in digital storage continues at its current rate of 30–38% compound annual growth per year,<ref name="HilbertLopez2011" /> it will rival the total information content contained in all of the DNA in all of the cells on Earth in about 110 years. This would represent a doubling of the amount of information stored in the biosphere across a total time period of just 150 years".<ref name="InfoBiosphere2016">{{Cite journal |url=http://escholarship.org/uc/item/38f4b791 |doi=10.1016/j.tree.2015.12.013|pmid=26777788|title=Information in the Biosphere: Biological and Digital Worlds|journal=Trends in Ecology & Evolution|volume=31|issue=3|pages=180–189|year=2016|last1=Kemp|first1=D. J.|last2=Hilbert|first2=M.|last3=Gillings|first3=M. R.}}</ref>
@@ 第627行： / 第613行： @@
 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.<ref name="nytimes july09" />
-年2月，在[[人工智能促进协会]]（AAAI）的主持下，[[Eric Horvitz]]在加利福尼亚州太平洋格罗夫的Asilomar主持了一次由主要计算机科学家、人工智能研究人员和机器人学家组成的会议。其目的是讨论机器人能够自给自足并能够做出自己决定的假设可能性的潜在影响。他们讨论了计算机和机器人能够在多大程度上获得[[自主]]，以及在多大程度上可以利用这些能力构成威胁或危险
+年2月，在[[人工智能促进协会]]（AAAI）的主持下，[[Eric Horvitz]]在加利福尼亚州太平洋格罗夫的Asilomar主持了一次由主要计算机科学家、人工智能研究人员和机器人学家组成的会议。其目的是讨论机器人能够自给自足并能够做出自己决定的假设可能性的潜在影响。他们讨论了计算机和机器人能够在多大程度上获得[[自主]]，以及在多大程度上可以利用这些能力构成威胁或危险。<ref name="nytimes july09" />
@@ 第634行： / 第620行： @@
-有些机器被编程成各种形式的半自治，包括定位自己的电源和选择用武器攻击的目标的能力。此外，有些[计算机病毒]可以逃避消除，根据与会科学家的说法，可以说已经达到了机器智能的“蟑螂”阶段。与会者指出，科幻小说中描述的自我意识可能不太可能，但也存在其他潜在的危险和陷阱。<ref name=“nytimes july09”>[https://www.nytimes.com/2009/07/26/science/26robot.html？_r=1&ref=todayspaper科学家担心机器可能会比人聪明]作者：JOHN MARKOFF，纽约时报，2009年7月26日。</ref>
+有些机器被编程成各种形式的半自治，包括定位自己的电源和选择用武器攻击的目标的能力。此外，有些[计算机病毒]可以逃避消除，根据与会科学家的说法，可以说已经达到了机器智能的“蟑螂”阶段。与会者指出，科幻小说中描述的自我意识可能不太可能，但也存在其他潜在的危险和陷阱。<ref name="nytimes july09">[https://www.nytimes.com/2009/07/26/science/26robot.html?_r=1&ref=todayspaper Scientists Worry Machines May Outsmart Man] By JOHN MARKOFF, NY Times, July 26, 2009.</ref>
@@ 第641行： / 第626行： @@
-弗兰克·S·罗宾逊预言，一旦人类实现了具有人类智能的机器，科学技术问题将以远远优于人类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，使人类的能力相形见绌？|magazine=[[The Humanist]]|日期=2013年6月27日|网址=https://thehumanist.com/magazine/july-august-2013/features/the-human-future-upgrade-or-replacement}}</ref>罗宾逊还讨论了在这样一次情报爆炸之后，未来可能会有多大的不同。其中一个例子就是太阳能，地球接收到的太阳能远远多于人类捕获的太阳能，因此捕捉更多的太阳能将为文明发展带来巨大的希望。
+弗兰克·S·罗宾逊预言，一旦人类实现了具有人类智能的机器，科学技术问题将以远远优于人类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，使人类的能力相形见绌？<ref name=":0">{{cite magazine |last=Robinson |first=Frank S. |title=The Human Future: Upgrade or Replacement? |magazine=[[The Humanist]] |date=27 June 2013 |url=https://thehumanist.com/magazine/july-august-2013/features/the-human-future-upgrade-or-replacement}}</ref>罗宾逊还讨论了在这样一次情报爆炸之后，未来可能会有多大的不同。其中一个例子就是太阳能，地球接收到的太阳能远远多于人类捕获的太阳能，因此捕捉更多的太阳能将为文明发展带来巨大的希望。
 ==Hard vs. soft takeoff硬起飞与软起飞==
@@ 第647行： / 第632行： @@
 [[File:Recursive self-improvement.svg|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).<ref name="yudkowsky-global-risk">[[Eliezer Yudkowsky]]. "Artificial intelligence as a positive and negative factor in global risk." Global catastrophic risks (2008).</ref>]]
-[[文件：Recursive self-improvement.svg|thumb |直立=1.6 |在这个示例递归自我改进场景中，修改人工智能体系结构的人可以每三年将其性能提高一倍，例如，30代人，然后用尽所有可行的改进（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减半，并且它在6年内将所有30代可行的代都推进（右图）。<ref name=“yudkowsky global risk”>[[Eliezer yudkowsky]]”人工智能作为全球风险的积极和消极因素〉，《全球灾难性风险》（2008年）。</ref>]]
+[[文件：Recursive self-improvement.svg|thumb |直立=1.6 |在这个示例递归自我改进场景中，修改人工智能体系结构的人可以每三年将其性能提高一倍，例如，30代人，然后用尽所有可行的改进（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减半，并且它在6年内将所有30代可行的代都推进（右图）。<ref name="yudkowsky-global-risk">[[Eliezer Yudkowsky]]. "Artificial intelligence as a positive and negative factor in global risk." Global catastrophic risks (2008).</ref>]]
 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.<ref>Bugaj, Stephan Vladimir, and Ben Goertzel. "Five ethical imperatives and their implications for human-AGI interaction." Dynamical Psychology (2007).</ref><ref>Sotala, Kaj, and Roman V. Yampolskiy. "Responses to catastrophic AGI risk: a survey." Physica Scripta 90.1 (2014): 018001.</ref>
+在一个艰难的情况下，一个AGI迅速自我完善，“掌控”了世界（也许在几个小时内），对于人为引起的重大错误纠正或AGI目标的逐步调整来说，太快了。在软起飞的情况下，AGI仍然比人类强大得多，但以一种类似人类的速度（也许是几十年的数量级），在一个时间尺度上，持续的人类互动和纠正可以有效地指导AGI的发展。<ref>Bugaj、Stephan Vladimir和Ben Goertzel。”五项伦理要求及其对人类AGI互动的影响〉，《动力心理学》（2007年）。</ref><ref>Sotala, Kaj, and Roman V. Yampolskiy. "Responses to catastrophic AGI risk: a survey." Physica Scripta 90.1 (2014): 018001.</ref>
-在一个艰难的情况下，一个AGI迅速自我完善，“掌控”了世界（也许在几个小时内），对于人为引起的重大错误纠正或AGI目标的逐步调整来说，太快了。在软起飞的情况下，AGI仍然比人类强大得多，但以一种类似人类的速度（也许是几十年的数量级），在一个时间尺度上，持续的人类互动和纠正可以有效地指导AGI的发展。<ref>Bugaj、Stephan Vladimir和Ben Goertzel。”五项伦理要求及其对人类AGI互动的影响〉，《动力心理学》（2007年）。</ref><ref>索塔拉、卡吉和罗曼诉扬波尔斯基对灾难性AGI风险的反应：一项调查。“Physica Scripta 90.1（2014）：018001。</ref>
 [[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]].<ref name=Naam2014Further>{{cite web|last=Naam|first=Ramez|title=The Singularity Is Further Than It Appears|url=http://www.antipope.org/charlie/blog-static/2014/02/the-singularity-is-further-tha.html|accessdate=16 May 2014|year=2014}}</ref> 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."<ref name=Naam2014Ascend>{{cite web|last=Naam|first=Ramez|title=Why AIs Won't Ascend in the Blink of an Eye - Some Math|url=http://www.antipope.org/charlie/blog-static/2014/02/why-ais-wont-ascend-in-blink-of-an-eye.html|accessdate=16 May 2014|year=2014}}</ref>
-[[Ramez Naam]]反对硬起飞。他指出，我们已经看到企业等超级智能体的递归自我改进。例如，[[Intel]]拥有“数万人的集体脑力，可能还有数百万个CPU核心。。。设计更好的CPU！”然而，这并没有导致一个艰难的起飞；相反，它以[[摩尔定律]]的形式实现了软起飞=http://www.antipope.org/charlie/blog-static/2014/02/the-singularity-is-further-tha.html|accessdate=2014年5月16日|年=2014}</ref>Naam进一步指出高智商的复杂性可能比线性复杂得多，因此，“创造一个智慧的头脑2可能比创造一个智慧的头脑1”的难度要“多”一倍多。”<ref name=Naam2014Ascend>{{cite web|last=Naam|first=Ramez|title=Why AIs Won't Ascend in the Blink of an Eye - Some Math|url=http://www.antipope.org/charlie/blog-static/2014/02/why-ais-wont-ascend-in-blink-of-an-eye.html|accessdate=16 May 2014|year=2014}}</ref>
+[[Ramez Naam]]反对硬起飞。他指出，我们已经看到企业等超级智能体的递归自我改进。例如，[[Intel]]拥有“数万人的集体脑力，可能还有数百万个CPU核心。。。设计更好的CPU！”然而，这并没有导致一个艰难的起飞；相反，它以[[摩尔定律]]的形式实现了软起飞<ref name=Naam2014Further>{{cite web|last=Naam|first=Ramez|title=The Singularity Is Further Than It Appears|url=http://www.antipope.org/charlie/blog-static/2014/02/the-singularity-is-further-tha.html|accessdate=16 May 2014|year=2014}}</ref> Naam进一步指出高智商的复杂性可能比线性复杂得多，因此，“创造一个智慧的头脑2可能比创造一个智慧的头脑1”的难度要“多”一倍多。”<ref name=Naam2014Ascend>{{cite web|last=Naam|first=Ramez|title=Why AIs Won't Ascend in the Blink of an Eye - Some Math|url=http://www.antipope.org/charlie/blog-static/2014/02/why-ais-wont-ascend-in-blink-of-an-eye.html|accessdate=16 May 2014|year=2014}}</ref>
 [[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.<ref name=Hall2008>{{cite journal|last=Hall|first=J. Storrs|title=Engineering Utopia|journal=Artificial General Intelligence, 2008: Proceedings of the First AGI Conference|date=2008|pages=460–467|url=http://www.agiri.org/takeoff_hall.pdf|accessdate=16 May 2014}}</ref>
-[[J.Storrs Hall]]认为，“许多更常见的夜间硬起飞场景都是循环的——它们似乎在自我提升过程的“起点”假设了超人类能力”，以便人工智能能够实现起飞所需的戏剧性的领域总体改进。霍尔认为，一个初出茅庐的人工智能与其靠自己不断地自我改进硬件、软件和基础设施，不如专注于一个它最有效的领域，然后在市场上购买剩余的组件，因为市场上产品的质量不断提高，而人工智能也在不断提高很难跟上世界其他地区使用的尖端技术。<ref name=Hall2008>{cite journal | last=Hall | first=J.Storrs | title=Engineering Utopia|journal=Artificial General Intelligence，2008年：第一届AGI会议记录|日期=2008 |页=460–467 |网址=http://www.agiri.org/takeng_hall.pdf|accessdate=2014年5月16日}</ref>
+[[J.Storrs Hall]]认为，“许多更常见的夜间硬起飞场景都是循环的——它们似乎在自我提升过程的“起点”假设了超人类能力”，以便人工智能能够实现起飞所需的戏剧性的领域总体改进。霍尔认为，一个初出茅庐的人工智能与其靠自己不断地自我改进硬件、软件和基础设施，不如专注于一个它最有效的领域，然后在市场上购买剩余的组件，因为市场上产品的质量不断提高，而人工智能也在不断提高很难跟上世界其他地区使用的尖端技术。<ref name=Hall2008>{{cite journal|last=Hall|first=J. Storrs|title=Engineering Utopia|journal=Artificial General Intelligence, 2008: Proceedings of the First AGI Conference|date=2008|pages=460–467|url=http://www.agiri.org/takeoff_hall.pdf|accessdate=16 May 2014}}</ref>
 [[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".<ref name="Goertzel2014">{{cite news|last1=Goertzel|first1=Ben|title=Superintelligence — Semi-hard Takeoff Scenarios|url=http://hplusmagazine.com/2014/09/26/superintelligence-semi-hard-takeoff-scenarios/|accessdate=25 October 2014|agency=h+ Magazine|date=26 Sep 2014}}</ref>
+[[Ben Goertzel]]同意霍尔的建议，即一个新的人类级别的人工智能将很好地利用其智能来积累财富。人工智能的天赋可能会激励公司和政府将其软件分散到整个社会。戈尔策尔对5分钟的艰难起飞持怀疑态度，但他推测，从人类到超人的水平，以5年的速度起飞是合理的。Goerzel将这种情况称为“半硬起飞”。<ref name="Goertzel2014">{{cite news|last1=Goertzel|first1=Ben|title=Superintelligence — Semi-hard Takeoff Scenarios|url=http://hplusmagazine.com/2014/09/26/superintelligence-semi-hard-takeoff-scenarios/|accessdate=25 October 2014|agency=h+ Magazine|date=26 Sep 2014}}</ref>
-[[Ben Goertzel]]同意霍尔的建议，即一个新的人类级别的人工智能将很好地利用其智能来积累财富。人工智能的天赋可能会激励公司和政府将其软件分散到整个社会。戈尔策尔对5分钟的艰难起飞持怀疑态度，但他推测，从人类到超人的水平，以5年的速度起飞是合理的。Goerzel将这种情况称为“半硬起飞”。<ref name=“Goertzel2014”>{cite news | last1=Goertzel | first1=Ben | title=superiintelligence-Semi-hard-tacking Scenarios | url=http://hplusmagazine.com/2014/09/26/superintelligence-semi-hard-takeoff-scenarios/|accessdate=2014年10月25日|机构=h+杂志|日期=2014年9月26日}</ref>
 [[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."<ref name=More>{{cite web|last1=More|first1=Max|title=Singularity Meets Economy|url=http://hanson.gmu.edu/vc.html#more|accessdate=10 November 2014}}</ref>
+[[Max More]]不同意这一观点，他认为，如果只有少数超快人类水平的人工智能，它们不会从根本上改变世界，因为它们仍将依赖于其他人来完成任务，并且仍然会受到人类认知的限制。即使所有的超高速人工智能都致力于智能增强，但目前还不清楚为什么它们在产生超人类智能方面比现有的人类认知科学家做得更好，尽管进展速度会加快。更进一步指出，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、缓慢的人类系统进行接触，以完成对世界的物理影响。”合作、组织和将想法付诸实际变革的需要将确保所有旧规则不会在一夜之间甚至几年内被废除。”<ref name=More>{{cite web|last1=More|first1=Max|title=Singularity Meets Economy|url=http://hanson.gmu.edu/vc.html#more|accessdate=10 November 2014}}</ref>
-[[Max More]]不同意这一观点，他认为，如果只有少数超快人类水平的人工智能，它们不会从根本上改变世界，因为它们仍将依赖于其他人来完成任务，并且仍然会受到人类认知的限制。即使所有的超高速人工智能都致力于智能增强，但目前还不清楚为什么它们在产生超人类智能方面比现有的人类认知科学家做得更好，尽管进展速度会加快。更进一步指出，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、缓慢的人类系统进行接触，以完成对世界的物理影响。”合作、组织和将想法付诸实际变革的需要将确保所有旧规则不会在一夜之间甚至几年内被废除。”
 == Immortality 永生==
@@ 第683行： / 第661行： @@
 In his 2005 book, ''[[The Singularity is Near]]'', [[Ray Kurzweil|Kurzweil]] suggests that medical advances would allow people to protect their bodies from the effects of aging, making the [[Life extension|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.<ref>''The Singularity Is Near'', p.&nbsp;215.</ref> 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.<ref>''The Singularity is Near'', p.&nbsp;216.</ref>
-在他2005年出版的《奇点就在眼前》一书中，他指出，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，从而延长寿命。Kurzweil认为，医学的技术进步将使我们能够不断地修复和更换我们身体中有缺陷的部件，从而将寿命延长到不确定的年龄。<ref>“奇点就在附近”，第215页。</ref>Kurzweil通过讨论当前的生物工程进展进一步支持了他的论点。Kurzweil建议[[体细胞基因疗法]；在合成具有特定遗传信息的病毒之后，下一步将把这项技术应用到基因治疗中，用合成的基因取代人类的DNA。<ref>“奇点就在附近”，第216页。</ref>
+在他2005年出版的《奇点就在眼前》一书中，他指出，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，从而延长寿命。Kurzweil认为，医学的技术进步将使我们能够不断地修复和更换我们身体中有缺陷的部件，从而将寿命延长到不确定的年龄。<ref>''The Singularity Is Near'', p.&nbsp;215.</ref>Kurzweil通过讨论当前的生物工程进展进一步支持了他的论点。Kurzweil建议[[体细胞基因疗法]；在合成具有特定遗传信息的病毒之后，下一步将把这项技术应用到基因治疗中，用合成的基因取代人类的DNA。<ref>''The Singularity is Near'', p.&nbsp;216.</ref>
 [[K. Eric Drexler]], one of the founders of [[nanotechnology]], postulated cell repair devices, including ones operating within cells and utilizing as yet hypothetical [[biological machine]]s, in his 1986 book ''[[Engines of Creation]]''.
 [[K.Eric Drexler]]，[[纳米技术]]的创始人之一，在他1986年的著作“[[创造的引擎]]”中，假设了细胞修复设备，包括在细胞内运行并利用目前假设的[[生物机器]]的设备。
@@ 第697行： / 第673行： @@
-据[[Richard Feynman]]所说，是他的前研究生和合作者[[Albert Hibbs]]最初向他建议（大约在1959年）费曼理论微型机械的“医学”用途。Hibbs认为，有一天，某些修理机器的尺寸可能会缩小到理论上可能（正如费曼所说的那样）“[[分子机器|生物|吞下医生]”。这个想法被纳入了费曼1959年的文章“[[在底部有很多空间]]”http://www.its.caltech.edu/~feynman/pluntity.html|title=底部有足够的空间| first=Richard P.| last=Feynman | author link=Richard Feynman | date=1959年12月| url status=dead |存档url=https://web.archive.org/web/2010021190050/http://www.its.caltech.edu/~feynman/pluntity.html|存档日期=2010-02-11}}</ref>
+据[[Richard Feynman]]所说，是他的前研究生和合作者[[Albert Hibbs]]最初向他建议（大约在1959年）费曼理论微型机械的“医学”用途。Hibbs认为，有一天，某些修理机器的尺寸可能会缩小到理论上可能（正如费曼所说的那样）“[[分子机器|生物|吞下医生]”。这个想法被纳入了费曼1959年的文章“[[在底部有很多空间]]”。<ref>{{cite web|url = http://www.its.caltech.edu/~feynman/plenty.html|title = There's Plenty of Room at the Bottom|first = Richard P.|last = Feynman |author-link = Richard Feynman|date = December 1959|url-status = dead|archive-url = https://web.archive.org/web/20100211190050/http://www.its.caltech.edu/~feynman/plenty.html|archive-date = 2010-02-11}}</ref>
 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".<ref>{{cite book |title = You Are Not a Gadget: A Manifesto |last = Lanier |first = Jaron |author-link = Jaron Lanier |publisher = [[Alfred A. Knopf]] |year = 2010 |isbn = 978-0307269645 |location = New York, NY |page = [https://archive.org/details/isbn_9780307269645/page/26 26] |url-access = registration |url = https://archive.org/details/isbn_9780307269645 }}</ref>
+除了仅仅延长物质身体的运行寿命之外，[[Jaron Lanier]]还主张一种称为“数字提升”的不朽形式，即“人死在肉体上，被上传到电脑里，保持清醒”。<ref>{{cite book |title = You Are Not a Gadget: A Manifesto |last = Lanier |first = Jaron |author-link = Jaron Lanier |publisher = [[Alfred A. Knopf]] |year = 2010 |isbn = 978-0307269645 |location = New York, NY |page = [https://archive.org/details/isbn_9780307269645/page/26 26] |url-access = registration |url = https://archive.org/details/isbn_9780307269645 }}</ref>
-除了仅仅延长物质身体的运行寿命之外，[[Jaron Lanier]]还主张一种称为“数字提升”的不朽形式，即“人死在肉体上，被上传到电脑里，保持清醒”。
 ==History of the concept概念史==
@@ 第710行： / 第684行： @@
 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.<ref>{{Cite journal|last=Prasad|first=Mahendra|year=2019|title=Nicolas de Condorcet and the First Intelligence Explosion Hypothesis|journal=AI Magazine|volume=40|issue=1|pages=29–33|doi=10.1609/aimag.v40i1.2855}}</ref>
+Mahendra Prasad在“[[人工智能杂志]]”上发表的一篇论文断言，18世纪的数学家[[Marquis de Condorcet]]是第一个对智能爆炸及其对人类影响进行假设和数学建模的人。<ref>{{Cite journal|last=Prasad|first=Mahendra|year=2019|title=Nicolas de Condorcet and the First Intelligence Explosion Hypothesis|journal=AI Magazine|volume=40|issue=1|pages=29–33|doi=10.1609/aimag.v40i1.2855}}</ref>
 An early description of the idea was made in [[John Wood Campbell Jr.]]'s 1932 short story "The last evolution".
@@ 第718行： / 第692行： @@
 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."<ref name=mathematical/>
-乌兰姆在1958年为【【约翰·冯·诺依曼】】写的讣告中，回忆了与冯·诺依曼的一次对话：“技术的不断进步和人类生活方式的变化，这使我们似乎接近了种族历史上某些基本的奇点，超出了这些奇点，人类的事务就不能继续下去了。”名称=数学/>
+乌兰姆在1958年为【【约翰·冯·诺依曼】】写的讣告中，回忆了与冯·诺依曼的一次对话：“技术的不断进步和人类生活方式的变化，这使我们似乎接近了种族历史上某些基本的奇点，超出了这些奇点，人类的事务就不能继续下去了。”<ref name=mathematical/>
 In 1965, Good wrote his essay postulating an "intelligence explosion" of recursive self-improvement of a machine intelligence.
-年，古德写了一篇文章，假设机器智能的递归自我改进是“智能爆炸”。
+年，古德写了一篇文章，假设机器智能的自我改进迭代是“智能爆炸”。
 In 1981, [[Stanisław Lem]] published his [[science fiction]] novel ''[[Golem XIV]]''. It describes a military AI computer (Golem XIV) who obtains consciousness and starts to increase his own intelligence, moving towards personal technological singularity. Golem XIV was originally created to aid its builders in fighting wars, but as its intelligence advances to a much higher level than that of humans, it stops being interested in the military requirement because it finds them lacking internal logical consistency.
@@ 第729行： / 第703行： @@
 In 1983, [[Vernor Vinge]] greatly popularized Good's intelligence explosion in a number of writings, first addressing the topic in print in the January 1983 issue of ''[[Omni (magazine)|Omni]]'' magazine. In this op-ed piece, Vinge seems to have been the first to use the term "singularity" in a way that was specifically tied to the creation of intelligent machines:<ref name="google4"/><ref name="technological"/>
-Mahendra Prasad的一篇论文，发表在“[[AI Magazine]]”上，断言18世纪的数学家[[Marquis de Condorcet]]是第一个假设和数学模拟智能爆炸及其对人类的影响的人杂志|卷=40 |问题=1 |页=29–33 | doi=10.1609/aimag.v40i1.2855}</ref>
 年，[[Vernor Vinge]]在许多著作中极大地普及了Good的智能爆炸，第一次在1983年1月出版的“[[Omni（magazine）| Omni]]”杂志上发表了这一主题。在这篇评论文章中，文奇似乎是第一个使用“奇点”一词的人，这种用法与智能机器的创造有着特别的联系：<ref name=“google4”/><ref name=“technology”/>
 {{quote|We will soon create intelligences greater than our own. When this happens, human history will have reached a kind of singularity, an intellectual transition as impenetrable as the knotted space-time at the center of a black hole, and the world will pass far beyond our understanding. This singularity, I believe, already haunts a number of science-fiction writers. It makes realistic extrapolation to an interstellar future impossible. To write a story set more than a century hence, one needs a nuclear war in between ... so that the world remains intelligible.}}
-{{我们很快就会创造出比我们自己更强大的智能。当这种情况发生时，人类历史将达到一种奇点，一种如同黑洞中心打结的时空一样难以逾越的知识转变，世界将远远超出我们的理解。我相信，这种奇点已经困扰了许多科幻作家。这使得对星际未来的现实推断变得不可能。要写一个多世纪以来的故事，就需要一场核战争。。。这样世界就可以理解了
+{{我们很快就会创造出比我们自己更强大的智能。当这种情况发生时，人类历史将达到一种奇点，一种如同黑洞中心打结的时空一样难以逾越的知识转变，世界将远远超出我们的理解。我相信，这种奇点已经困扰了许多科幻作家。这使得对星际未来的现实推断变得不可能。要写一个多世纪以来的故事，就需要一场核战争。。。这样世界就可以理解了。}}
-}}
-}}
 In 1985, in "The Time Scale of Artificial Intelligence", artificial intelligence researcher [[Ray Solomonoff]] articulated mathematically the related notion of what he called an "infinity point": if a research community of human-level self-improving AIs take four years to double their own speed, then two years, then one year and so on, their capabilities increase infinitely in finite time.<ref name=chalmers /><ref name="std"/>
@@ 第755行： / 第723行： @@
 In 2000, [[Bill Joy]], a prominent technologist and a co-founder of [[Sun Microsystems]], voiced concern over the potential dangers of the singularity.<ref name="JoyFuture"/>
+在2000年，[[Bill Joy]]，一位著名的技术专家和[[Sun Microsystems]]的联合创始人，表达了对奇点的潜在危险的担忧。<ref name="JoyFuture"/>
-在2000年，[[Bill Joy]]，一位著名的技术专家和[[Sun Microsystems]]的联合创始人，表达了对奇点的潜在危险的担忧
 In 2005, Kurzweil published ''[[The Singularity is Near]]''. Kurzweil's publicity campaign included an appearance on ''[[The Daily Show with Jon Stewart]]''.<ref name="episode"/>
-年，库兹韦尔发表了“[[奇点就在附近]]”。库兹韦尔的宣传活动包括在“[[The Daily Show with Jon Stewart]]”上露面<ref name="episode"/>
+年，库兹韦尔发表了“[[奇点临近]]”。库兹韦尔的宣传活动在“[[乔恩·斯图尔特的每日秀]]”上露面<ref name="episode"/>
 | first = I. J.
@@ 第770行： / 第736行： @@
 In 2007, [[Eliezer Yudkowsky]] suggested that many of the varied definitions that have been assigned to "singularity" are mutually incompatible rather than mutually supporting.<ref name="yudkowsky.net"/><ref>Sandberg, Anders. "An overview of models of technological singularity." Roadmaps to AGI and the Future of AGI Workshop, Lugano, Switzerland, March. Vol. 8. 2010.</ref> 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.<ref name="yudkowsky.net"/>
-年，[[Eliezer Yudkowsky]]指出，许多被赋予“奇点”的不同定义是相互不相容的，而不是相互支持的yudkowsky.net网站“/><ref>桑德伯格，安德斯。”技术奇点模型概述〉《AGI路线图和AGI研讨会的未来》，瑞士卢加诺，3月。第八卷。2010年。</ref>例如，Kurzweil推断了当前的技术发展轨迹，而这些都是由于I.J.Good提出的智能的不连续上升和Vinge关于不可预测性的论文的矛盾。
+年，[[Eliezer Yudkowsky]]指出，许多被赋予“奇点”的不同定义是相互不相容的，而不是相互支持的<ref name="yudkowsky.net"/><ref>Sandberg, Anders. "An overview of models of technological singularity." Roadmaps to AGI and the Future of AGI Workshop, Lugano, Switzerland, March. Vol. 8. 2010.</ref>例如，Kurzweil推断了当前的技术发展轨迹，而这些都是在自我完善的人工智能或超人智能的到来之后，尤德科夫斯基认为，这代表着一种紧张关系，既有I.J.古德提出的智力不连续上升，也有文奇关于不可预测性的论文。<ref name="yudkowsky.net"/>
 | last = Good
@@ 第784行： / 第750行： @@
 In 2009, Kurzweil and [[X-Prize]] founder [[Peter Diamandis]] announced the establishment of [[Singularity University]], a nonaccredited private institute whose stated mission is "to educate, inspire and empower leaders to apply exponential technologies to address humanity's grand challenges."<ref name="singularityu"/> Funded by [[Google]], [[Autodesk]], [[ePlanet Ventures]], and a group of [[High tech|technology industry]] leaders, Singularity University is based at [[NASA]]'s [[Ames Research Center]] in [[Mountain View, California|Mountain View]], [[California]]. The not-for-profit organization runs an annual ten-week graduate program during summer that covers ten different technology and allied tracks, and a series of executive programs throughout the year.
-年，Kurzweil和[[X-Prize]]的创始人[[Peter Diamandis]]宣布成立[[Singularity University]]，这是一所未经认可的私立学院，其宣称的使命是“教育、激励和授权领导者应用指数技术应对人类的重大挑战。”，奇点大学的[[Autodesk]]、[[ePlanet Ventures]]和一组[[高科技|技术产业]]领导者，总部位于[[NASA]]]的[[Ames研究中心]]，位于[[加利福尼亚州]的[[Mountain View，California]]。这家非营利组织在夏季每年夏季举办为期十周的研究生课程，涵盖十种不同的技术和相关领域，并全年举办一系列高管课程。
+年，Kurzweil和[[X-Prize]]的创始人[[Peter Diamandis]]宣布成立[[奇点大学]]，这是一所未经认可的私立学院，其宣称的使命是“教育、激励和授权领导者应用指数技术应对人类的重大挑战。”<ref name="singularityu"/>奇点大学由[[Google]]、[[Autodesk]]、[[ePlanet Ventures]]和一群[[高科技 | 技术产业]]的领导团队资助，总部设在[[NASA]]的[[Ames Research Center]]，位于[[Mountain View，California]]的[[California]]。这家非营利组织在夏季每年夏季举办为期十周的研究生课程，涵盖十种不同的技术和相关领域，并全年举办一系列高管课程。
 | chapter = Speculations Concerning the First Ultraintelligent Machine