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第83行： − 超级智能、超智能或超人智能是一种假想的智能体。它拥有的智能远远超过最聪明、最有天赋的人类大脑的智能。“超级智能”也可以指这种智能体所拥有的智能的形式或程度。John von Neumann，Vernor Vinge和Ray Kurzweil 从技术创造超级智能的角度定义了这个概念。他们认为，现在的人类很难或不可能预测人类在后奇点世界的生活会是什么样子<ref name="vinge1993"/><ref name="singularity"/>+ 第93行：
第93行： − 一些作家writers更宽泛地使用“奇点”的概念，用来指代任何我们社会中由新技术带来的剧烈变化，如分子纳米技术，<ref name="hplusmagazine"/><ref name="yudkowsky.net"/><ref name="agi-conf"/> 尽管Vinge和其他作家明确指出，如果没有超级智能，这些改变就不能算作真正的奇点。<ref name="vinge1993" />+ − 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，唯一的区别是这个机器运行得更快.<ref>{{cite book |doi=10.1007/978-3-662-54033-6_2 |year=2017 |publisher=Springer Berlin Heidelberg |pages=11–23 |author=Kaj Sotala and Roman Yampolskiy |title=The Technological Singularity |chapter=Risks of the Journey to the Singularity |series=The Frontiers Collection |isbn=978-3-662-54031-2 |conference=The Frontiers Collection }}</ref> 。例如，与人类相比，它信息处理的速度提高了一百万倍，一个主观年将在30个物理秒内过去。<ref name="singinst.org"/>这种在信息处理上的差异可能会导致奇点。.<ref>{{cite book |doi=10.1002/9781118922590.ch16 |year=2016 |publisher=John Wiley \& Sons, Inc |pages=171–224 |author=David J. Chalmers |title=Science Fiction and Philosophy |chapter=The Singularity |isbn=9781118922590 |conference=Science Fiction and Philosophy }}</ref>+ 第104行：
第104行： − 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。<ref name="spectrum.ieee.org"/><ref name="ieee"/><ref name="Allen"/>+ − 大多数创造超人或跨人类头脑的方法分为两类：人脑的智能增强和人工智能。据推测，智能增强的方法很多，包括生物工程、基因工程、益智药物、AI 助手、直接脑机接口和思维上传。因为人们正在探索通向智能爆炸的多种途径，这使得奇点出现的可能更大；奇点不发生，所有这些都必将失败。<ref name="singinst.org">{{cite web|url=http://singinst.org/overview/whatisthesingularity |title=What is the Singularity? | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110908014050/http://singinst.org/overview/whatisthesingularity/ |archivedate=2011-09-08 }}</ref>+ 第116行：
第116行： − 智能爆炸是否发生取决于三个因素。第一个加速因素是以前的每一次改进都使新的智能增强成为可能。相反，随着智能的进步，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。平均而言，每一次改进都应该至少带来一次改进，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。+ − + − 2017年，一项对2015年 NeurIPS 和 ICML 机器学习会议上发表论文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% 的人认为“有可能” ，21% 的人认为“可能性中等” ，24% 的人认为“不太可能” ，26% 的人认为“非常不可能”。<ref>{{cite arxiv|last1=Grace|first1=Katja|last2=Salvatier|first2=John|last3=Dafoe|first3=Allan|last4=Zhang|first4=Baobao|last5=Evans|first5=Owain|title=When Will AI Exceed Human Performance? Evidence from AI Experts|eprint=1705.08807|date=24 May 2017|class=cs.AI}}</ref>+ 第130行：
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第140行： − 马丁 · 福特Martin Ford的《隧道中的灯光: 自动化，加速技术和未来经济The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future》+ − +
无编辑摘要
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.
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.
如果一种超人类智能被发明出来。无论是通过人类智能的放大还是通过人工智能，它将带来比现在的人类更强的问题解决和发明创造能力。这种人工智能被称为<font color="#ff8000">种子人工智能 Seed AI</font>。因为如果人工智能的工程能力能够与它的人类创造者相匹敌或超越，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。这种自我递归式改进的迭代可以加速，以至于在物理定律或理论计算设定的任何上限之前产生巨大的质变。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。
如果一种超人类智能被发明出来。无论是通过人类智能的放大还是通过人工智能，它将带来比现在的人类更强的问题解决和发明创造能力。这种人工智能被称为<font color="#ff8000">种子人工智能 Seed AI</font>。因为如果人工智能的工程能力能够与它的人类创造者相匹敌或超越，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。这种自我递归式改进的迭代可以加速，以至于在物理定律或理论计算设定的任何上限之内发生巨大的质变。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。
==智能爆炸==
==智能爆炸==
A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical [[intelligent agent|agent]] that possesses intelligence far surpassing that of the brightest and most gifted human minds. "Superintelligence" may also refer to the form or degree of intelligence possessed by such an agent. [[John von Neumann]], [[Vernor Vinge]] and [[Ray Kurzweil]] define the concept in terms of the technological creation of super intelligence. They argue that it is difficult or impossible for present-day humans to predict what human beings' lives would be like in a post-singularity world.<ref name="vinge1993"/><ref name="singularity"/>
A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical [[intelligent agent|agent]] that possesses intelligence far surpassing that of the brightest and most gifted human minds. "Superintelligence" may also refer to the form or degree of intelligence possessed by such an agent. [[John von Neumann]], [[Vernor Vinge]] and [[Ray Kurzweil]] define the concept in terms of the technological creation of super intelligence. They argue that it is difficult or impossible for present-day humans to predict what human beings' lives would be like in a post-singularity world.<ref name="vinge1993"/><ref name="singularity"/>
超级智能、超智能或超人智能是一种假想的智能体。它拥有的智能远远超过最聪明、最有天赋的人类大脑的智能。“超级智能”也可以指这种智能体所拥有的智能的形式或程度。约翰·冯·诺依曼 John von Neumann，Vernor Vinge 和 Ray Kurzweil 从技术创造超级智能的角度定义了这个概念。他们认为，现在的人类很难或不可能预测人类在后奇点世界的生活会是什么样子<ref name="vinge1993"/><ref name="singularity"/>
Some writers use "the singularity" in a broader way to refer to any radical changes in our society brought about by new technologies such as [[molecular nanotechnology]],<ref name="hplusmagazine"/><ref name="yudkowsky.net"/><ref name="agi-conf"/> although Vinge and other writers specifically state that without superintelligence, such changes would not qualify as a true singularity.<ref name="vinge1993" />
Some writers use "the singularity" in a broader way to refer to any radical changes in our society brought about by new technologies such as [[molecular nanotechnology]],<ref name="hplusmagazine"/><ref name="yudkowsky.net"/><ref name="agi-conf"/> although Vinge and other writers specifically state that without superintelligence, such changes would not qualify as a true singularity.<ref name="vinge1993" />
一些作家更宽泛地使用“奇点”的概念，用来指代任何我们社会中由新技术带来的剧烈变化，如分子纳米技术，<ref name="hplusmagazine"/><ref name="yudkowsky.net"/><ref name="agi-conf"/> 尽管 Vernor Vinge 和其他作家明确指出，如果没有超级智能，这些改变就不能算作真正的奇点。<ref name="vinge1993" />
===速度超智能===
===速度超智能===
A speed superintelligence describes an AI that can do everything that a human can do, where the only difference is that the machine runs faster.<ref>{{cite book |doi=10.1007/978-3-662-54033-6_2 |year=2017 |publisher=Springer Berlin Heidelberg |pages=11–23 |author=Kaj Sotala and Roman Yampolskiy |title=The Technological Singularity |chapter=Risks of the Journey to the Singularity |series=The Frontiers Collection |isbn=978-3-662-54031-2 |conference=The Frontiers Collection }}</ref> 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.<ref name="singinst.org"/> Such a difference in information processing speed could drive the singularity.<ref>{{cite book |doi=10.1002/9781118922590.ch16 |year=2016 |publisher=John Wiley \& Sons, Inc |pages=171–224 |author=David J. Chalmers |title=Science Fiction and Philosophy |chapter=The Singularity |isbn=9781118922590 |conference=Science Fiction and Philosophy }}</ref>
A speed superintelligence describes an AI that can do everything that a human can do, where the only difference is that the machine runs faster.<ref>{{cite book |doi=10.1007/978-3-662-54033-6_2 |year=2017 |publisher=Springer Berlin Heidelberg |pages=11–23 |author=Kaj Sotala and Roman Yampolskiy |title=The Technological Singularity |chapter=Risks of the Journey to the Singularity |series=The Frontiers Collection |isbn=978-3-662-54031-2 |conference=The Frontiers Collection }}</ref> 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.<ref name="singinst.org"/> Such a difference in information processing speed could drive the singularity.<ref>{{cite book |doi=10.1002/9781118922590.ch16 |year=2016 |publisher=John Wiley \& Sons, Inc |pages=171–224 |author=David J. Chalmers |title=Science Fiction and Philosophy |chapter=The Singularity |isbn=9781118922590 |conference=Science Fiction and Philosophy }}</ref>
<font color="#ff8000">速度超级智能 speed superintelligence </font>描述了一个人工智能，它可以做任何人类能做的事情，唯一的区别是这个机器运行得更快.<ref>{{cite book |doi=10.1007/978-3-662-54033-6_2 |year=2017 |publisher=Springer Berlin Heidelberg |pages=11–23 |author=Kaj Sotala and Roman Yampolskiy |title=The Technological Singularity |chapter=Risks of the Journey to the Singularity |series=The Frontiers Collection |isbn=978-3-662-54031-2 |conference=The Frontiers Collection }}</ref> 。例如，与人类相比，它信息处理的速度提高了一百万倍，一个主观年将在30个物理秒内过去。<ref name="singinst.org"/>这种在信息处理速度上的差异可能会导致奇点。.<ref>{{cite book |doi=10.1002/9781118922590.ch16 |year=2016 |publisher=John Wiley \& Sons, Inc |pages=171–224 |author=David J. Chalmers |title=Science Fiction and Philosophy |chapter=The Singularity |isbn=9781118922590 |conference=Science Fiction and Philosophy }}</ref>
==合理性==
==合理性==
Many prominent technologists and academics dispute the plausibility of a technological singularity, including [[Paul Allen]], [[Jeff Hawkins]], [[John Henry Holland|John Holland]], [[Jaron Lanier]], and [[Gordon Moore]], whose [[Moore's law|law]] is often cited in support of the concept.<ref name="spectrum.ieee.org"/><ref name="ieee"/><ref name="Allen"/>
Many prominent technologists and academics dispute the plausibility of a technological singularity, including [[Paul Allen]], [[Jeff Hawkins]], [[John Henry Holland|John Holland]], [[Jaron Lanier]], and [[Gordon Moore]], whose [[Moore's law|law]] is often cited in support of the concept.<ref name="spectrum.ieee.org"/><ref name="ieee"/><ref name="Allen"/>
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。<ref name="spectrum.ieee.org"/><ref name="ieee"/><ref name="Allen"/>
Most proposed methods for creating superhuman or [[transhuman]] minds fall into one of two categories: intelligence amplification of human brains and artificial intelligence. The speculated ways to produce intelligence augmentation are many, and include [[bioengineering]], [[genetic engineering]], [[nootropic]] drugs, AI assistants, direct [[brain–computer interface]]s and [[mind uploading]]. Because multiple paths to an intelligence explosion are being explored, it makes a singularity more likely; for a singularity to not occur they would all have to fail.<ref name="singinst.org">{{cite web|url=http://singinst.org/overview/whatisthesingularity |title=What is the Singularity? | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110908014050/http://singinst.org/overview/whatisthesingularity/ |archivedate=2011-09-08 }}</ref>
Most proposed methods for creating superhuman or [[transhuman]] minds fall into one of two categories: intelligence amplification of human brains and artificial intelligence. The speculated ways to produce intelligence augmentation are many, and include [[bioengineering]], [[genetic engineering]], [[nootropic]] drugs, AI assistants, direct [[brain–computer interface]]s and [[mind uploading]]. Because multiple paths to an intelligence explosion are being explored, it makes a singularity more likely; for a singularity to not occur they would all have to fail.<ref name="singinst.org">{{cite web|url=http://singinst.org/overview/whatisthesingularity |title=What is the Singularity? | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110908014050/http://singinst.org/overview/whatisthesingularity/ |archivedate=2011-09-08 }}</ref>
大多数创造超人或超越人类智能的方法分为两类：人脑的智能增强和人工智能。据推测，智能增强的方法很多，包括生物工程、基因工程、益智药物、AI 助手、直接脑机接口和思维上传。因为人们正在探索通向智能爆炸的多种途径，这使得奇点出现的可能性变得更大；如果奇点不发生，所有这些方法都必将失败。<ref name="singinst.org">{{cite web|url=http://singinst.org/overview/whatisthesingularity |title=What is the Singularity? | Singularity Institute for Artificial Intelligence |publisher=Singinst.org |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110908014050/http://singinst.org/overview/whatisthesingularity/ |archivedate=2011-09-08 }}</ref>
[[Robin Hanson]] expressed skepticism of human intelligence augmentation, writing that once the "low-hanging fruit" of easy methods for increasing human intelligence have been exhausted, further improvements will become increasingly difficult to find.<ref name="hanson">{{cite web |url=https://mason.gmu.edu/~rhanson/vc.html#hanson |title=Some Skepticism |date=1998 |first=Robin |last=Hanson |author-link=Robin Hanson |accessdate=April 8, 2020}}</ref> Despite all of the speculated ways for amplifying human intelligence, non-human artificial intelligence (specifically seed AI) is the most popular option among the hypotheses that would advance the singularity.{{citation needed|date=July 2012}}
[[Robin Hanson]] expressed skepticism of human intelligence augmentation, writing that once the "low-hanging fruit" of easy methods for increasing human intelligence have been exhausted, further improvements will become increasingly difficult to find.<ref name="hanson">{{cite web |url=https://mason.gmu.edu/~rhanson/vc.html#hanson |title=Some Skepticism |date=1998 |first=Robin |last=Hanson |author-link=Robin Hanson |accessdate=April 8, 2020}}</ref> Despite all of the speculated ways for amplifying human intelligence, non-human artificial intelligence (specifically seed AI) is the most popular option among the hypotheses that would advance the singularity.{{citation needed|date=July 2012}}
Whether or not an intelligence explosion occurs depends on three factors.<ref name="david_chalmers_singularity_lecture_resources_available">David Chalmers John Locke Lecture, 10 May, Exam Schools, Oxford, [http://www.fhi.ox.ac.uk/news/2010/david_chalmers_singularity_lecture_resources_available Presenting a philosophical analysis of the possibility of a technological singularity or "intelligence explosion" resulting from recursively self-improving AI] {{webarchive|url=https://web.archive.org/web/20130115205558/http://www.fhi.ox.ac.uk/news/2010/david_chalmers_singularity_lecture_resources_available |date=2013-01-15 }}.</ref> The first accelerating factor is the new intelligence enhancements made possible by each previous improvement. Contrariwise, as the intelligences become more advanced, further advances will become more and more complicated, possibly overcoming the advantage of increased intelligence. Each improvement should beget at least one more improvement, on average, for movement towards singularity to continue. Finally, the laws of physics will eventually prevent any further improvements.
Whether or not an intelligence explosion occurs depends on three factors.<ref name="david_chalmers_singularity_lecture_resources_available">David Chalmers John Locke Lecture, 10 May, Exam Schools, Oxford, [http://www.fhi.ox.ac.uk/news/2010/david_chalmers_singularity_lecture_resources_available Presenting a philosophical analysis of the possibility of a technological singularity or "intelligence explosion" resulting from recursively self-improving AI] {{webarchive|url=https://web.archive.org/web/20130115205558/http://www.fhi.ox.ac.uk/news/2010/david_chalmers_singularity_lecture_resources_available |date=2013-01-15 }}.</ref> The first accelerating factor is the new intelligence enhancements made possible by each previous improvement. Contrariwise, as the intelligences become more advanced, further advances will become more and more complicated, possibly overcoming the advantage of increased intelligence. Each improvement should beget at least one more improvement, on average, for movement towards singularity to continue. Finally, the laws of physics will eventually prevent any further improvements.
智能爆炸是否发生取决于三个因素。第一个加速因素是过去的每一次改进都使新的智能增强成为可能。相反，随着智能的进步，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。平均而言，每一次改进都应该至少带来一次改进，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。
There are two logically independent, but mutually reinforcing, causes of intelligence improvements: increases in the speed of computation, and improvements to the [[algorithm]]s used.<ref name="consc.net">[http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis, David J. Chalmers]</ref> The former is predicted by [[Moore's law|Moore's Law]] and the forecasted improvements in hardware,<ref name="itrs">{{cite web |url=http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |title=ITRS |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110929173755/http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |archivedate=2011-09-29 }}</ref> and is comparatively similar to previous technological advances. But there are some AI researchers{{who|date=March 2017}} who believe software is more important than hardware.<ref>{{Cite web|url=https://blog.chronicled.com/why-software-is-more-important-than-hardware-right-now-6a4b58feaa7c|title=Why Software Is More Important Than Hardware Right Now|last=Kulkarni|first=Ajit|date=2017-12-12|website=Chronicled|access-date=2019-02-23}}</ref>{{citation needed|date=July 2012}}
There are two logically independent, but mutually reinforcing, causes of intelligence improvements: increases in the speed of computation, and improvements to the [[algorithm]]s used.<ref name="consc.net">[http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis, David J. Chalmers]</ref> The former is predicted by [[Moore's law|Moore's Law]] and the forecasted improvements in hardware,<ref name="itrs">{{cite web |url=http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |title=ITRS |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110929173755/http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |archivedate=2011-09-29 }}</ref> and is comparatively similar to previous technological advances. But there are some AI researchers{{who|date=March 2017}} who believe software is more important than hardware.<ref>{{Cite web|url=https://blog.chronicled.com/why-software-is-more-important-than-hardware-right-now-6a4b58feaa7c|title=Why Software Is More Important Than Hardware Right Now|last=Kulkarni|first=Ajit|date=2017-12-12|website=Chronicled|access-date=2019-02-23}}</ref>{{citation needed|date=July 2012}}
智能改进有两个逻辑上独立但又相互加强的原因：计算速度的提高和使用的算法的改进。<ref name="consc.net">[http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis, David J. Chalmers]</ref>前者由摩尔定律和硬件方面的预测改进进行预测，<ref name="itrs">{{cite web |url=http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |title=ITRS |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110929173755/http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |archivedate=2011-09-29 }}</ref>与以前的技术进步比较相似。但也有一些人工智能研究人员认为软件比硬件更重要<ref>{{Cite web|url=https://blog.chronicled.com/why-software-is-more-important-than-hardware-right-now-6a4b58feaa7c|title=Why Software Is More Important Than Hardware Right Now|last=Kulkarni|first=Ajit|date=2017-12-12|website=Chronicled|access-date=2019-02-23}}</ref>{{citation needed|date=July 2012}}
智能改进有两个逻辑上独立但又相互加强的原因：计算速度的提高和使用的算法的改进。<ref name="consc.net">[http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis, David J. Chalmers]</ref>前者由摩尔定律和硬件方面的改进进行预测，<ref name="itrs">{{cite web |url=http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |title=ITRS |accessdate=2011-09-09 |url-status=dead |archiveurl=https://web.archive.org/web/20110929173755/http://www.itrs.net/Links/2007ITRS/ExecSum2007.pdf |archivedate=2011-09-29 }}</ref>与以前的技术进步比较相似。但也有一些人工智能研究人员认为软件比硬件更重要<ref>{{Cite web|url=https://blog.chronicled.com/why-software-is-more-important-than-hardware-right-now-6a4b58feaa7c|title=Why Software Is More Important Than Hardware Right Now|last=Kulkarni|first=Ajit|date=2017-12-12|website=Chronicled|access-date=2019-02-23}}</ref>{{citation needed|date=July 2012}}
A 2017 email survey of authors with publications at the 2015 [[Conference on Neural Information Processing Systems|NeurIPS]] and [[International Conference on Machine Learning|ICML]] machine learning conferences asked about the chance of an intelligence explosion. Of the respondents, 12% said it was "quite likely", 17% said it was "likely", 21% said it was "about even", 24% said it was "unlikely" and 26% said it was "quite unlikely".<ref>{{cite arxiv|last1=Grace|first1=Katja|last2=Salvatier|first2=John|last3=Dafoe|first3=Allan|last4=Zhang|first4=Baobao|last5=Evans|first5=Owain|title=When Will AI Exceed Human Performance? Evidence from AI Experts|eprint=1705.08807|date=24 May 2017|class=cs.AI}}</ref>
A 2017 email survey of authors with publications at the 2015 [[Conference on Neural Information Processing Systems|NeurIPS]] and [[International Conference on Machine Learning|ICML]] machine learning conferences asked about the chance of an intelligence explosion. Of the respondents, 12% said it was "quite likely", 17% said it was "likely", 21% said it was "about even", 24% said it was "unlikely" and 26% said it was "quite unlikely".<ref>{{cite arxiv|last1=Grace|first1=Katja|last2=Salvatier|first2=John|last3=Dafoe|first3=Allan|last4=Zhang|first4=Baobao|last5=Evans|first5=Owain|title=When Will AI Exceed Human Performance? Evidence from AI Experts|eprint=1705.08807|date=24 May 2017|class=cs.AI}}</ref>
在2017年，一项对2015年 NeurIPS 和 ICML 机器学习会议上发表论文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% 的人认为“有可能” ，21% 的人认为“可能性中等” ，24% 的人认为“不太可能” ，26% 的人认为“非常不可能”。<ref>{{cite arxiv|last1=Grace|first1=Katja|last2=Salvatier|first2=John|last3=Dafoe|first3=Allan|last4=Zhang|first4=Baobao|last5=Evans|first5=Owain|title=When Will AI Exceed Human Performance? Evidence from AI Experts|eprint=1705.08807|date=24 May 2017|class=cs.AI}}</ref>
===速度改进 ===
===速度改进 ===
Both for human and artificial intelligence, hardware improvements increase the rate of future hardware improvements. Simply put,<ref name="arstechnica">{{cite web|last=Siracusa |first=John |url=https://arstechnica.com/apple/reviews/2009/08/mac-os-x-10-6.ars/8 |title=Mac OS X 10.6 Snow Leopard: the Ars Technica review |publisher=Arstechnica.com |date=2009-08-31 |accessdate=2011-09-09}}</ref> [[Moore's Law]] suggests that if the first doubling of speed took 18 months, the second would take 18 subjective months; or 9 external months, whereafter, four months, two months, and so on towards a speed singularity.<ref name="singularity6">Eliezer Yudkowsky, 1996 [http://www.yudkowsky.net/obsolete/singularity.html "Staring into the Singularity"]</ref> An upper limit on speed may eventually be reached, although it is unclear how high this would be. Jeff Hawkins has stated that a self-improving computer system would inevitably run into upper limits on computing power: "in the end there are limits to how big and fast computers can run. We would end up in the same place; we'd just get there a bit faster. There would be no singularity."<ref name="Hawkins">{{cite magazine |url=https://spectrum.ieee.org/computing/hardware/tech-luminaries-address-singularity |title=Tech Luminaries Address Singularity |date=1 June 2008 |magazine=[[IEEE Spectrum]]}}</ref>
Both for human and artificial intelligence, hardware improvements increase the rate of future hardware improvements. Simply put,<ref name="arstechnica">{{cite web|last=Siracusa |first=John |url=https://arstechnica.com/apple/reviews/2009/08/mac-os-x-10-6.ars/8 |title=Mac OS X 10.6 Snow Leopard: the Ars Technica review |publisher=Arstechnica.com |date=2009-08-31 |accessdate=2011-09-09}}</ref> [[Moore's Law]] suggests that if the first doubling of speed took 18 months, the second would take 18 subjective months; or 9 external months, whereafter, four months, two months, and so on towards a speed singularity.<ref name="singularity6">Eliezer Yudkowsky, 1996 [http://www.yudkowsky.net/obsolete/singularity.html "Staring into the Singularity"]</ref> An upper limit on speed may eventually be reached, although it is unclear how high this would be. Jeff Hawkins has stated that a self-improving computer system would inevitably run into upper limits on computing power: "in the end there are limits to how big and fast computers can run. We would end up in the same place; we'd just get there a bit faster. There would be no singularity."<ref name="Hawkins">{{cite magazine |url=https://spectrum.ieee.org/computing/hardware/tech-luminaries-address-singularity |title=Tech Luminaries Address Singularity |date=1 June 2008 |magazine=[[IEEE Spectrum]]}}</ref>
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，<ref name="arstechnica">{{cite web|last=Siracusa |first=John |url=https://arstechnica.com/apple/reviews/2009/08/mac-os-x-10-6.ars/8 |title=Mac OS X 10.6 Snow Leopard: the Ars Technica review |publisher=Arstechnica.com |date=2009-08-31 |accessdate=2011-09-09}}</ref>Moore's Law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<ref name="singularity6">Eliezer Yudkowsky, 1996 [http://www.yudkowsky.net/obsolete/singularity.html "Staring into the Singularity"]</ref> 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。”<ref name="Hawkins">{{cite magazine |url=https://spectrum.ieee.org/computing/hardware/tech-luminaries-address-singularity |title=Tech Luminaries Address Singularity |date=1 June 2008 |magazine=[[IEEE Spectrum]]}}</ref>
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，<ref name="arstechnica">{{cite web|last=Siracusa |first=John |url=https://arstechnica.com/apple/reviews/2009/08/mac-os-x-10-6.ars/8 |title=Mac OS X 10.6 Snow Leopard: the Ars Technica review |publisher=Arstechnica.com |date=2009-08-31 |accessdate=2011-09-09}}</ref>摩尔定律认为，如果第一次速度翻倍需要18个月，第二次则需要18个月；或者额外的9个月，之后，4个月、2个月，以此类推，走向速度奇点<ref name="singularity6">Eliezer Yudkowsky, 1996 [http://www.yudkowsky.net/obsolete/singularity.html "Staring into the Singularity"]</ref> 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，计算机的规模和速度都是有限的。我们最终会在停留在同一个地方；我们只会更快到达那里。不会有奇点。”<ref name="Hawkins">{{cite magazine |url=https://spectrum.ieee.org/computing/hardware/tech-luminaries-address-singularity |title=Tech Luminaries Address Singularity |date=1 June 2008 |magazine=[[IEEE Spectrum]]}}</ref>
It is difficult to directly compare [[silicon]]-based hardware with [[neuron]]s. But {{Harvtxt|Berglas|2008}} 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.
It is difficult to directly compare [[silicon]]-based hardware with [[neuron]]s. But {{Harvtxt|Berglas|2008}} 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。
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，而且这种能力似乎只需要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。
====指数增长====
====指数增长====
Martin Ford in The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future
Martin Ford in The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future
马丁·福特 Martin Ford 的《隧道中的灯光: 自动化，加速技术和未来经济 The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future》
[[Image:PPTMooresLawai.jpg|thumb|Ray Kurzweil writes that, due to [[paradigm shift]]s, a trend of exponential growth extends [[Moore's law]] from [[integrated circuits]] to earlier [[transistor]]s, [[vacuum tube]]s, [[relay]]s, and [[electromechanics|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.|链接=Special:FilePath/PPTMooresLawai.jpg]]
[[Image:PPTMooresLawai.jpg|thumb|Ray Kurzweil writes that, due to [[paradigm shift]]s, a trend of exponential growth extends [[Moore's law]] from [[integrated circuits]] to earlier [[transistor]]s, [[vacuum tube]]s, [[relay]]s, and [[electromechanics|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.|链接=Special:FilePath/PPTMooresLawai.jpg]]
[[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]]
[[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]]
[[File:Moore's Law over 120 Years.png|thumb|left|An updated version of Moore's law over 120 Years (based on [[Ray Kurzweil|Kurzweil's]] [[c:File:PPTMooresLawai.jpg|graph]]). The 7 most recent data points are all [[Nvidia GPUs|NVIDIA GPUs]].|链接=Special:FilePath/Moore's_Law_over_120_Years.png]]
[[File:Moore's Law over 120 Years.png|thumb|left|An updated version of Moore's law over 120 Years (based on [[Ray Kurzweil|Kurzweil's]] [[c:File:PPTMooresLawai.jpg|graph]]). The 7 most recent data points are all [[Nvidia GPUs|NVIDIA GPUs]].|链接=Special:FilePath/Moore's_Law_over_120_Years.png]]