Answers.Body: <p>As far as I know, no &quot;true&quot; (i.e. as intellectual and physically capable as a human) artificial general intelligent system (AGI) has been implemented or is practically useful (this is confirmed by Ben Goertzel, who is one of the leading researchers in AGI [<a href="https://www.linkedin.com/pulse/sophias-ai-ben-goertzel/" rel="nofollow noreferrer">1</a>, <a href="https://www.youtube.com/watch?v=r4manxX5U-0&amp;ab_channel=TEDxTalks" rel="nofollow noreferrer">2</a>]).</p>
  <p>The closest to a practical AGI might be <a href="https://www.hansonrobotics.com/sophia/" rel="nofollow noreferrer">Sophia</a> (or similar robots), which may look like an AGI, but it lacks several capabilities that we humans have and its ability to adapt to new circumstances is limited. Sophia uses <a href="https://opencog.org/about/" rel="nofollow noreferrer">OpenCog</a> [<a href="https://www.linkedin.com/pulse/sophias-ai-ben-goertzel/" rel="nofollow noreferrer">1</a>], which is supposed to be a software framework to develop AGI. Sophia is used for the <a href="https://lovingai.org/" rel="nofollow noreferrer">loving AI project</a>.</p>
  <p>There are also <a href="https://ai.stackexchange.com/q/21427/2444">theoretical frameworks for AGI</a>, such as <a href="https://jan.leike.name/AIXI.html" rel="nofollow noreferrer">AIXI</a>, which, in any case, have several flaws, such as incomputability (in the case of AIXI). There are <a href="https://github.com/sgkasselau/pyaixi" rel="nofollow noreferrer">approximations of AIXI</a>, but these approximations can only be used to solve toy problems (such as tic-tac-toe), so they aren't really useful to solve complex real-world problems. However, it is possible that better approximations to AIXI and more theoretical frameworks for AGI will be developed that can deal with more complex problems.</p>
  <p>It's also important to note that, despite their success, AlphaGo and AlphaStar are <a href="https://en.wikipedia.org/wiki/Weak_AI" rel="nofollow noreferrer">narrow AI</a> systems, as they can only solve one specific problem (although the same approach can be adapted to solve very similar problems too, e.g. AlphaZero).</p>
  <p>If you want to know more about AGI, the <a href="http://www.scholarpedia.org/article/Main_Page" rel="nofollow noreferrer">Scholarpedia</a>'s article <a href="http://www.scholarpedia.org/article/Artificial_General_Intelligence" rel="nofollow noreferrer">Artificial General Intelligence</a>, curated by Ben Goertzel, provides a good overview of the AGI field, including but not restricted to definitions of AGI and approaches to the development of AGI systems, such as</p>
  <ul>
  <li><p>universal (<a href="https://jan.leike.name/AIXI.html" rel="nofollow noreferrer">AIXI</a> was created based on this approach),</p>
  </li>
  <li><p>symbolic (<a href="https://soar.eecs.umich.edu/" rel="nofollow noreferrer">Soar</a> was created based on this approach), which is based on the <a href="https://ai.stanford.edu/%7Enilsson/OnlinePubs-Nils/PublishedPapers/pssh.pdf" rel="nofollow noreferrer">physical symbol system hypothesis</a>,</p>
  </li>
  <li><p>emergentist (or sub-symbolic), which is based on the idea that general intelligence is expected to <em>emerge</em> from sub-symbolic dynamics (where a sub-symbolic system refers e.g. to an artificial neural network),</p>
  </li>
  <li><p>hybrid (e.g. <a href="https://en.wikipedia.org/wiki/CLARION_(cognitive_architecture)" rel="nofollow noreferrer">CLARION</a>), which is a combination of the universal, symbolic or sub-symbolic approaches.</p>
  </li>
  </ul>
  <p>You probably also want to take a look at <a href="https://ai.stackexchange.com/q/7431/2444">this question</a>, which has a few answers that mention a paper and book that you can read to know more about the AGI field. You may also be interested in <a href="https://ai.stackexchange.com/q/20180/2444">this related question</a> too.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-12-28T14:35:52.257Z
Answers.LastActivityDate: 2021-01-31T18:15:50.907Z
Answers.LastEditDate: 2021-01-31T18:15:50.907Z
Answers.UserDisplayName: nbro
Body: <p>I wish to compile a (somewhat) comprehensive list of AGI systems that have actually been created and tested (to whatever degrees of success) instead of those that simply advertise they are going to 'do' something about it or have patented theoretical concepts. </p>
  
  <p>For the purposes of this question, we can use the following <a href="https://en.wikipedia.org/wiki/Artificial_general_intelligence" rel="nofollow noreferrer">definition of AGI</a>:</p>
  
  <blockquote>
    <p>Artificial general intelligence (AGI) is the intelligence of a machine that can understand or learn any intellectual task that a human being can</p>
  </blockquote>
  
Tags: <reference-request><agi><research><state-of-the-art>
Title: Which AGI systems have already been implemented and tested?
UserDisplayName: Code Monkey
ThreadText: # Which AGI systems have already been implemented and tested?
  
  (Asked by: username_0 on 2019-12-28)
  
  I wish to compile a (somewhat) comprehensive list of AGI systems that have actually been created and tested (to whatever degrees of success) instead of those that simply advertise they are going to 'do' something about it or have patented theoretical concepts.
  
  For the purposes of this question, we can use the following [definition of AGI](https://en.wikipedia.org/wiki/Artificial_general_intelligence):
  
  > Artificial general intelligence (AGI) is the intelligence of a machine that can understand or learn any intellectual task that a human being can
  
  **Tags:** reference-request, agi, research, state-of-the-art
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-12-28. Score: 5
  
  As far as I know, no "true" (i.e. as intellectual and physically capable as a human) artificial general intelligent system (AGI) has been implemented or is practically useful (this is confirmed by Ben Goertzel, who is one of the leading researchers in AGI [[1](https://www.linkedin.com/pulse/sophias-ai-ben-goertzel/), [2](https://www.youtube.com/watch?v=r4manxX5U-0&ab_channel=TEDxTalks)]).
  
  The closest to a practical AGI might be [Sophia](https://www.hansonrobotics.com/sophia/) (or similar robots), which may look like an AGI, but it lacks several capabilities that we humans have and its ability to adapt to new circumstances is limited. Sophia uses [OpenCog](https://opencog.org/about/) [[1](https://www.linkedin.com/pulse/sophias-ai-ben-goertzel/)], which is supposed to be a software framework to develop AGI. Sophia is used for the [loving AI project](https://lovingai.org/).
  
  There are also [theoretical frameworks for AGI](https://ai.stackexchange.com/q/21427/2444), such as [AIXI](https://jan.leike.name/AIXI.html), which, in any case, have several flaws, such as incomputability (in the case of AIXI). There are [approximations of AIXI](https://github.com/sgkasselau/pyaixi), but these approximations can only be used to solve toy problems (such as tic-tac-toe), so they aren't really useful to solve complex real-world problems. However, it is possible that better approximations to AIXI and more theoretical frameworks for AGI will be developed that can deal with more complex problems.
  
  It's also important to note that, despite their success, AlphaGo and AlphaStar are [narrow AI](https://en.wikipedia.org/wiki/Weak_AI) systems, as they can only solve one specific problem (although the same approach can be adapted to solve very similar problems too, e.g. AlphaZero).
  
  If you want to know more about AGI, the [Scholarpedia](http://www.scholarpedia.org/article/Main_Page)'s article [Artificial General Intelligence](http://www.scholarpedia.org/article/Artificial_General_Intelligence), curated by Ben Goertzel, provides a good overview of the AGI field, including but not restricted to definitions of AGI and approaches to the development of AGI systems, such as
  
  * universal ([AIXI](https://jan.leike.name/AIXI.html) was created based on this approach),
  * symbolic ([Soar](https://soar.eecs.umich.edu/) was created based on this approach), which is based on the [physical symbol system hypothesis](https://ai.stanford.edu/%7Enilsson/OnlinePubs-Nils/PublishedPapers/pssh.pdf),
  * emergentist (or sub-symbolic), which is based on the idea that general intelligence is expected to *emerge* from sub-symbolic dynamics (where a sub-symbolic system refers e.g. to an artificial neural network),
  * hybrid (e.g. [CLARION](https://en.wikipedia.org/wiki/CLARION_(cognitive_architecture))), which is a combination of the universal, symbolic or sub-symbolic approaches.
  
  You probably also want to take a look at [this question](https://ai.stackexchange.com/q/7431/2444), which has a few answers that mention a paper and book that you can read to know more about the AGI field. You may also be interested in [this related question](https://ai.stackexchange.com/q/20180/2444) too.
  
  
  ---
  
  