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	<title>Artificial general intelligence - Revision history</title>
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	<updated>2026-04-25T03:40:29Z</updated>
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		<id>https://wikimd.org/index.php?title=Artificial_general_intelligence&amp;diff=5604367&amp;oldid=prev</id>
		<title>Prab: CSV import</title>
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		<updated>2024-04-14T21:57:16Z</updated>

		<summary type="html">&lt;p&gt;CSV import&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;[[File:Estimations_of_Human_Brain_Emulation_Required_Performance.svg|left|thumb]] &amp;#039;&amp;#039;&amp;#039;Artificial General Intelligence&amp;#039;&amp;#039;&amp;#039; (&amp;#039;&amp;#039;&amp;#039;AGI&amp;#039;&amp;#039;&amp;#039;), also known as &amp;#039;&amp;#039;&amp;#039;strong AI&amp;#039;&amp;#039;&amp;#039; or &amp;#039;&amp;#039;&amp;#039;full AI&amp;#039;&amp;#039;&amp;#039;, is the hypothetical ability of an [[artificial intelligence]] system to understand, learn, and apply vast amounts of knowledge from various domains to the same extent as a human being. Unlike narrow AI, which is designed to perform a specific task with human-like capabilities, AGI can theoretically perform any intellectual task that a human being can. This includes the ability to reason, solve problems, make judgments under uncertainty, plan, learn, integrate prior knowledge in decision-making, and communicate in natural language.&lt;br /&gt;
&lt;br /&gt;
==Definition and Goals==&lt;br /&gt;
The goal of AGI research is to create a machine with the ability to reason, use strategy, solve puzzles, make judgments, plan, learn, and communicate in natural language. AGI would be capable of abstract thinking and possess common sense, social intelligence, and emotional intelligence. It is expected to perform any intellectual task that a human can do, and potentially even surpass human intelligence.&lt;br /&gt;
&lt;br /&gt;
==Approaches to AGI==&lt;br /&gt;
Several approaches have been proposed to achieve AGI, with no consensus on which method is most likely to succeed. These include:&lt;br /&gt;
&lt;br /&gt;
* [[Neural networks]] and [[deep learning]], which attempt to mimic the structure and function of the human brain to some extent.&lt;br /&gt;
* Symbolic AI, which involves the manipulation of symbols to represent concepts and relationships.&lt;br /&gt;
* Hybrid approaches, which combine elements of neural networks, symbolic AI, and other methodologies.&lt;br /&gt;
* Developmental robotics, which focuses on developing AGI through the lens of learning and development in a manner similar to human children.&lt;br /&gt;
&lt;br /&gt;
==Challenges==&lt;br /&gt;
The development of AGI poses significant technical and ethical challenges. These include:&lt;br /&gt;
&lt;br /&gt;
* The [[AI alignment problem]], which concerns how to align the goals of AGI systems with human values and ethics.&lt;br /&gt;
* The control problem, which deals with how to ensure that AGI systems remain under human control and do not act against human interests.&lt;br /&gt;
* Concerns about [[AI safety]], including the risk of unintended consequences from AGI actions.&lt;br /&gt;
* The potential for significant social and economic disruptions, including impacts on employment and privacy.&lt;br /&gt;
&lt;br /&gt;
==Ethical and Societal Implications==&lt;br /&gt;
The prospect of AGI raises profound ethical and societal questions. These include:&lt;br /&gt;
&lt;br /&gt;
* The potential for AGI to benefit humanity by solving complex problems in areas such as medicine, climate change, and scientific research.&lt;br /&gt;
* The risk of creating entities that could outperform humans in most cognitive tasks, leading to issues of power, control, and inequality.&lt;br /&gt;
* The need for a framework to ensure the responsible development and deployment of AGI, including considerations of transparency, accountability, and fairness.&lt;br /&gt;
&lt;br /&gt;
==Current Status==&lt;br /&gt;
As of now, AGI remains a theoretical concept, with no existing systems demonstrating AGI capabilities. Research in AI is primarily focused on narrow AI applications, although interest in AGI continues to grow. Breakthroughs in machine learning, computational power, and understanding of human cognition may pave the way for advances towards AGI in the future.&lt;br /&gt;
&lt;br /&gt;
==See Also==&lt;br /&gt;
* [[Artificial intelligence]]&lt;br /&gt;
* [[Machine learning]]&lt;br /&gt;
* [[Deep learning]]&lt;br /&gt;
* [[AI alignment]]&lt;br /&gt;
* [[AI safety]]&lt;br /&gt;
&lt;br /&gt;
[[Category:Artificial intelligence]]&lt;br /&gt;
[[Category:Future technology]]&lt;br /&gt;
&lt;br /&gt;
{{AI-stub}}&lt;/div&gt;</summary>
		<author><name>Prab</name></author>
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