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In 2017, researchers Feng Liu, Yong Shi and Ying Liu conducted intelligence tests on publicly available and freely accessible weak AI such as Google AI or Apple's Siri and others. At the maximum, these AI reached a value of about 47, which corresponds approximately to a six-year-old child in first grade. An adult comes to about 100 on average. Similar tests had been carried out in 2014, with the IQ score reaching a maximum value of 27.

In 2017, researchers Feng Liu, Yong Shi and Ying Liu conducted intelligence tests on publicly available and freely accessible weak AI such as Google AI or Apple's Siri and others. At the maximum, these AI reached a value of about 47, which corresponds approximately to a six-year-old child in first grade. An adult comes to about 100 on average. Similar tests had been carried out in 2014, with the IQ score reaching a maximum value of 27.

2017年，研究人员 Feng Liu，Yong Shi 和 Ying Liu 对公开的和可自由访问的弱智能进行了智能测试，如谷歌人工智能或苹果的 Siri 等。在最大值，这些 AI 达到了约47，这大约相当于一个六岁的儿童在一年级。一个成年人平均体重约为100磅。2014年也进行了类似的测试，智商分数达到了最高值27。

2017年，研究人员 Feng Liu，Yong Shi 和 Ying Liu 对公开的和可自由访问的弱智能进行了智能测试，如谷歌人工智能或苹果的 Siri 等。在最大值，这些人工智能达到了约47，这大约相当于一个的六岁儿童。一个成年人平均智商为100。2014年也进行了类似的测试，智商分数的最高值达到了27。

In 2019, video game programmer and aerospace engineer John Carmack announced plans to research AGI.

In 2019, video game programmer and aerospace engineer John Carmack announced plans to research AGI.

2019年，游戏程序师和航空工程师 John Carmack 宣布了研究 AGI 的计划。

2019年，游戏程序师和航空工程师约翰·卡迈克(John Carmack)宣布了研究通用人工智能的计划。

==Processing power needed to simulate a brain ==

==Processing power needed to simulate a brain 模拟人脑所需要的处理能力==

===Whole brain emulation===

===Whole brain emulation 全脑模拟===

{{main|Mind uploading}}

{{main|Mind uploading}}

A popular discussed approach to achieving general intelligent action is whole brain emulation. A low-level brain model is built by scanning and mapping a biological brain in detail and copying its state into a computer system or another computational device. The computer runs a simulation model so faithful to the original that it will behave in essentially the same way as the original brain, or for all practical purposes, indistinguishably.<ref name=Roadmap>

A popular discussed approach to achieving general intelligent action is whole brain emulation. A low-level brain model is built by scanning and mapping a biological brain in detail and copying its state into a computer system or another computational device. The computer runs a simulation model so faithful to the original that it will behave in essentially the same way as the original brain, or for all practical purposes, indistinguishably.<ref name=Roadmap>

实现一般智能行为的一种流行的讨论方法是全脑模拟。一个低层次的大脑模型是通过扫描和绘制生物大脑的详细情况，并将其状态复制到计算机系统或其他计算设备中来建立的。计算机运行的模拟模型如此忠实于原始模型，以至于它的行为在本质上与原始大脑相同，或者对于所有的实际目的，难以区分。 参考名称路线图

实现通用智能行为的一种流行的讨论方法是全脑模拟。一个低层次的大脑模型是通过扫描和绘制生物大脑的详细情况，并将其状态复制到计算机系统或其他计算设备中来建立的。计算机运行的模拟模型无比忠实于原始模型，以至于它的行为在本质，或者对于所有的实际目的上与原始大脑相同，难以区分。 参考名称路线图

{{Harvnb|Sandberg|Boström|2008}}. "The basic idea is to take a particular brain, scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain."</ref> Whole brain emulation is discussed in [[computational neuroscience]] and [[neuroinformatics]], in the context of [[brain simulation]] for medical research purposes. It is discussed in [[artificial intelligence]] research{{sfn|Goertzel|2007}} as an approach to strong AI. [[Neuroimaging]] technologies that could deliver the necessary detailed understanding are improving rapidly, and [[futurist]] Ray Kurzweil in the book ''The Singularity Is Near''<ref name=K/> predicts that a map of sufficient quality will become available on a similar timescale to the required computing power.

{{Harvnb|Sandberg|Boström|2008}}. "The basic idea is to take a particular brain, scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain."</ref> Whole brain emulation is discussed in [[computational neuroscience]] and [[neuroinformatics]], in the context of [[brain simulation]] for medical research purposes. It is discussed in [[artificial intelligence]] research{{sfn|Goertzel|2007}} as an approach to strong AI. [[Neuroimaging]] technologies that could deliver the necessary detailed understanding are improving rapidly, and [[futurist]] Ray Kurzweil in the book ''The Singularity Is Near''<ref name=K/> predicts that a map of sufficient quality will become available on a similar timescale to the required computing power.

. "The basic idea is to take a particular brain, scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain."</ref> Whole brain emulation is discussed in computational neuroscience and neuroinformatics, in the context of brain simulation for medical research purposes. It is discussed in artificial intelligence research as an approach to strong AI. Neuroimaging technologies that could deliver the necessary detailed understanding are improving rapidly, and futurist Ray Kurzweil in the book The Singularity Is Near predicts that a map of sufficient quality will become available on a similar timescale to the required computing power.

."The basic idea is to take a particular brain, scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain."</ref> Whole brain emulation is discussed in computational neuroscience and neuroinformatics, in the context of brain simulation for medical research purposes. It is discussed in artificial intelligence research as an approach to strong AI. Neuroimaging technologies that could deliver the necessary detailed understanding are improving rapidly, and futurist Ray Kurzweil in the book The Singularity Is Near predicts that a map of sufficient quality will become available on a similar timescale to the required computing power.

.“基本思想是，取一个特定的大脑，详细地扫描其结构，并构建一个与原始大脑如此忠实的软件模型，以至于在适当的硬件上运行时，它基本上与原始大脑的行为方式相同。整个大脑模拟在计算神经科学和神经信息学医学期刊上讨论过，这是为了医学研究的大脑模拟。它是人工智能研究中讨论的一种强人工智能的方法。神经成像技术可以提供必要的详细的理解正在迅速提高，未来学家 Ray Kurzweil 在《奇点迫近书中预测，一张具有足够质量的地图将在类似的时间尺度上达到所需的计算能力。

“基本思路是，取一个特定的大脑，详细地扫描其结构，并构建一个无比还原的原始大脑的软件模型，以至于在适当的硬件上运行时，它基本上与原始大脑的行为方式相同。基于医学研究的大脑模拟背景下，全脑模拟在计算神经科学和神经信息学医学期刊上被讨论过。它是人工智能研究中讨论的一种强人工智能的方法。可提供必要详细的理解的神经成像技术正在迅速提高，未来学家雷·库兹韦尔(Ray Kurzweil)在《奇点临近》书中预测，一张质量足够高的地图将在类似的时间尺度上达到所需的计算能力。

===Early estimates ===

===Early estimates 初步预测===

[[File:Estimations of Human Brain Emulation Required Performance.svg|thumb|right|400px|Estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil, and [[Anders Sandberg]] and [[Nick Bostrom]]), along with the fastest supercomputer from [[TOP500]] mapped by year. Note the logarithmic scale and exponential trendline, which assumes the computational capacity doubles every 1.1 years. Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg, Bostrom report is less certain about where [[consciousness]] arises.{{sfn|Sandberg|Boström|2008}}]] For low-level brain simulation, an extremely powerful computer would be required. The [[human brain]] has a huge number of [[synapses]]. Each of the 10¹¹ (one hundred billion) [[neurons]] has on average 7,000 synaptic connections (synapses) to other neurons. It has been estimated that the brain of a three-year-old child has about 10¹⁵ synapses (1 quadrillion). This number declines with age, stabilizing by adulthood. Estimates vary for an adult, ranging from 10¹⁴ to 5×10¹⁴ synapses (100 to 500 trillion).{{sfn|Drachman|2005}} An estimate of the brain's processing power, based on a simple switch model for neuron activity, is around 10¹⁴ (100 trillion) synaptic updates per second ([[SUPS]]).{{sfn|Russell|Norvig|2003}} In 1997, Kurzweil looked at various estimates for the hardware required to equal the human brain and adopted a figure of 10¹⁶ computations per second (cps).<ref>In "Mind Children" {{Harvnb|Moravec|1988|page=61}} 10¹⁵ cps is used. More recently, in 1997, <{{cite web|url=http://www.transhumanist.com/volume1/moravec.htm |title=Archived copy |accessdate=23 June 2006 |url-status=dead |archiveurl=https://web.archive.org/web/20060615031852/http://transhumanist.com/volume1/moravec.htm |archivedate=15 June 2006 }}> Moravec argued for 10⁸ MIPS which would roughly correspond to 10¹⁴ cps.  Moravec talks in terms of MIPS, not "cps", which is a non-standard term Kurzweil introduced.</ref> (For comparison, if a "computation" was equivalent to one "[[FLOPS|floating point operation]]" –  a measure used to rate current [[supercomputer]]s – then 10¹⁶ "computations" would be equivalent to 10 [[Peta-|petaFLOPS]], [[FLOPS#Performance records|achieved in 2011]]). He used this figure to predict the necessary hardware would be available sometime between 2015 and 2025, if the exponential growth in computer power at the time of writing continued.

[[File:Estimations of Human Brain Emulation Required Performance.svg|thumb|right|400px|Estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil, and [[Anders Sandberg]] and [[Nick Bostrom]]), along with the fastest supercomputer from [[TOP500]] mapped by year. Note the logarithmic scale and exponential trendline, which assumes the computational capacity doubles every 1.1 years. Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg, Bostrom report is less certain about where [[consciousness]] arises.{{sfn|Sandberg|Boström|2008}}]] For low-level brain simulation, an extremely powerful computer would be required. The [[human brain]] has a huge number of [[synapses]]. Each of the 10¹¹ (one hundred billion) [[neurons]] has on average 7,000 synaptic connections (synapses) to other neurons. It has been estimated that the brain of a three-year-old child has about 10¹⁵ synapses (1 quadrillion). This number declines with age, stabilizing by adulthood. Estimates vary for an adult, ranging from 10¹⁴ to 5×10¹⁴ synapses (100 to 500 trillion).{{sfn|Drachman|2005}} An estimate of the brain's processing power, based on a simple switch model for neuron activity, is around 10¹⁴ (100 trillion) synaptic updates per second ([[SUPS]]).{{sfn|Russell|Norvig|2003}} In 1997, Kurzweil looked at various estimates for the hardware required to equal the human brain and adopted a figure of 10¹⁶ computations per second (cps).<ref>In "Mind Children" {{Harvnb|Moravec|1988|page=61}} 10¹⁵ cps is used. More recently, in 1997, <{{cite web|url=http://www.transhumanist.com/volume1/moravec.htm |title=Archived copy |accessdate=23 June 2006 |url-status=dead |archiveurl=https://web.archive.org/web/20060615031852/http://transhumanist.com/volume1/moravec.htm |archivedate=15 June 2006 }}> Moravec argued for 10⁸ MIPS which would roughly correspond to 10¹⁴ cps.  Moravec talks in terms of MIPS, not "cps", which is a non-standard term Kurzweil introduced.</ref> (For comparison, if a "computation" was equivalent to one "[[FLOPS|floating point operation]]" –  a measure used to rate current [[supercomputer]]s – then 10¹⁶ "computations" would be equivalent to 10 [[Peta-|petaFLOPS]], [[FLOPS#Performance records|achieved in 2011]]). He used this figure to predict the necessary hardware would be available sometime between 2015 and 2025, if the exponential growth in computer power at the time of writing continued.