Answers.Body: <p>AI is not exclusive to machine learning. Back in the early days of the AI, in the 1960's or thereabouts, they were programming rules-based systems. A lot of work was done on manipulating facts and using combinations of facts to derive new facts. In 1972 the <a href="https://en.wikipedia.org/wiki/Prolog" rel="nofollow noreferrer">Prolog</a> language was created which does exactly this - the programmer defines a bunch of rules and then the interpreter finds ways to answer queries using the rules. (E.g. &quot;Tom is a cat. All cats are animals. What animals exist?&quot; -&gt; &quot;Tom&quot; [but written in Prolog and not in English])</p>
  <p>There was also work on natural language processing - you can see e.g. <a href="https://en.wikipedia.org/wiki/SHRDLU" rel="nofollow noreferrer">SHRDLU</a>. It was like ChatGPT but it only knew about stacking blocks and it was written in 1968 using Lisp. <code>PUT THE BLUE CYLINDER ON THE RED CUBE. WHERE IS THE BLUE CYLINDER?</code>. Today we're quite impressed to see ChatGPT answer this, but it's also easy to see how it could be done simply by adding enough rules to the system. SHRDLU would not only answer it, but also do it with a robot arm. Oh look, they <a href="https://en.wikipedia.org/wiki/AARON" rel="nofollow noreferrer">also made DALL-E in 1985</a>.</p>
  <p>Nowadays, AI and Machine Learning are near-synonymous, because the other AI stuff - such as natural language processing - is no longer called &quot;AI&quot;.</p>
  <p>Your tag search system is not AI in any sense of the word - it's just a tag search system. Such rigid mechanical systems were never called AI.</p>
  
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Answers.Text: Do I understand you correctly: a system built by ONLY manually added rules can not be classified as a modern AI? (could be in the past, but not nowadays). The rules rather are being manually added to a modern AI on two cases only: 1) as algorithms before the training a model and 2) later when a programmer can add some rules directly to the model to improve it, correct? Hence, a modern AI is mostly built by machine learning instead of manually added rules. You may add it to your answer as a summary or takeaway
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Answers.Text: Okay, thanks again! What one more a little other question: you wrote natural language processing is just an AI stuff. Why? I read it's a [_"branch of artificial intelligence or AI"_](https://www.ibm.com/topics/natural-language-processing). I mean, is this a type of AI or just stuff, branch, subfield, component of AI etc?
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Answers.Body: <p>It seems to be a reasonable idea combining machine learning with predefined knowledge.</p>
  <p>A recent example of this symbiosis is <a href="https://writings.stephenwolfram.com/2023/03/chatgpt-gets-its-wolfram-superpowers/" rel="nofollow noreferrer">Wolfram plugin</a> to provide hard-coded mathematical and data information into the conversational capabilities of ChatGPT.</p>
  <p>This addition improves truthfulness in the enhanced hybrid (ML+handcrafted) AI system.</p>
  
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Answers.Text: I think Wolfram itself used the label "computational intelligence".
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Body: <p>I know AI is primarly training a machine by samples of input-output in order it would learn itself about relations between the input and the output.</p>
  <p>What if I manually add the relations? Is that still can be called a type of AI? If so, what type is that within the context of AI classifying?</p>
  <p>In other words, does manually bound inputs and outputs belong to some &quot;official&quot; sort of modern AI due to specific case(s) when we need such a manual binding instead of training a machine? Or AI is exclusively creating relations by machine learning only?</p>
  <p>For example, if I save some text notes (output) and add multiple tags manually to each of the notes in order to find a note in the future by a few tags inputted (input), is such a search system a type of AI? Or I can call it just &quot;intelligent&quot;, but not AI-like? Where is the &quot;official&quot; difference?</p>
  
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Comments.Text: @user253751 Thanks for the comment! I added an update to make it clearer
Comments.UserDisplayName: stkuser
Tags: <terminology><data-preprocessing><search>
Title: Is manual binding output to input also an AI?
UserDisplayName: stkuser
ThreadText: # Is manual binding output to input also an AI?
  
  (Asked by: username_0 on 2023-03-28)
  
  I know AI is primarly training a machine by samples of input-output in order it would learn itself about relations between the input and the output.
  
  What if I manually add the relations? Is that still can be called a type of AI? If so, what type is that within the context of AI classifying?
  
  In other words, does manually bound inputs and outputs belong to some "official" sort of modern AI due to specific case(s) when we need such a manual binding instead of training a machine? Or AI is exclusively creating relations by machine learning only?
  
  For example, if I save some text notes (output) and add multiple tags manually to each of the notes in order to find a note in the future by a few tags inputted (input), is such a search system a type of AI? Or I can call it just "intelligent", but not AI-like? Where is the "official" difference?
  
  **Tags:** terminology, data-preprocessing, search
  > **Comments:**
  > **username_0**: @user253751 Thanks for the comment! I added an update to make it clearer  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2023-03-30. Score: 1 | Accepted answer
  
  AI is not exclusive to machine learning. Back in the early days of the AI, in the 1960's or thereabouts, they were programming rules-based systems. A lot of work was done on manipulating facts and using combinations of facts to derive new facts. In 1972 the [Prolog](https://en.wikipedia.org/wiki/Prolog) language was created which does exactly this - the programmer defines a bunch of rules and then the interpreter finds ways to answer queries using the rules. (E.g. "Tom is a cat. All cats are animals. What animals exist?" -> "Tom" [but written in Prolog and not in English])
  
  There was also work on natural language processing - you can see e.g. [SHRDLU](https://en.wikipedia.org/wiki/SHRDLU). It was like ChatGPT but it only knew about stacking blocks and it was written in 1968 using Lisp. `PUT THE BLUE CYLINDER ON THE RED CUBE. WHERE IS THE BLUE CYLINDER?`. Today we're quite impressed to see ChatGPT answer this, but it's also easy to see how it could be done simply by adding enough rules to the system. SHRDLU would not only answer it, but also do it with a robot arm. Oh look, they [also made DALL-E in 1985](https://en.wikipedia.org/wiki/AARON).
  
  Nowadays, AI and Machine Learning are near-synonymous, because the other AI stuff - such as natural language processing - is no longer called "AI".
  
  Your tag search system is not AI in any sense of the word - it's just a tag search system. Such rigid mechanical systems were never called AI.
  
  > **Comments:**
  > **username_0**: Do I understand you correctly: a system built by ONLY manually added rules can not be classified as a modern AI? (could be in the past, but not nowadays). The rules rather are being manually added to a modern AI on two cases only: 1) as algorithms before the training a model and 2) later when a programmer can add some rules directly to the model to improve it, correct? Hence, a modern AI is mostly built by machine learning instead of manually added rules. You may add it to your answer as a summary or takeaway  
  > **username_0**: Okay, thanks again! What one more a little other question: you wrote natural language processing is just an AI stuff. Why? I read it's a [_"branch of artificial intelligence or AI"_](https://www.ibm.com/topics/natural-language-processing). I mean, is this a type of AI or just stuff, branch, subfield, component of AI etc?  
  
  ---
  
  ### Answer by username_2 on 2023-03-31. Score: 0
  
  It seems to be a reasonable idea combining machine learning with predefined knowledge.
  
  A recent example of this symbiosis is [Wolfram plugin](https://writings.stephenwolfram.com/2023/03/chatgpt-gets-its-wolfram-superpowers/) to provide hard-coded mathematical and data information into the conversational capabilities of ChatGPT.
  
  This addition improves truthfulness in the enhanced hybrid (ML+handcrafted) AI system.
  
  > **Comments:**
  > **username_2**: I think Wolfram itself used the label "computational intelligence".  
  
  ---
  
  