Answers.Body: <p>The availability of large data sets.</p>
  <p>In symbolic/rule-based AI, the 'knowledge' has to be hand-coded, usually by experts. This is expensive and limited to small-scale problems only.</p>
  <p>In statistical AI/Machine Learning approaches, this is replaced by training a system on data. With very large amounts of data it is possible to achieve results that are not possible with rule-based approaches. In the past, such data sets were usually not available.</p>
  <p>However, this also means that the AI system has become somewhat of a black box, as it is not possible (at least not easily) <em>why</em> the system has behaved in a particular way.</p>
  <p>So in areas where this is important (eg banking and finance), rule-based approaches are still valuable.</p>
  
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Answers.CreationDate: 2022-09-13T15:30:06.233Z
Answers.Text: What about Fuzzy logic?
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Answers.CreationDate: 2022-09-13T16:23:03.127Z
Answers.Text: Fuzzy logic is basically a different way to express rule-based information.
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Body: <p>What is the fundamental reason that statistics-based AI (e.g., ML and Neural Net) has become more popular than other forms of AI, e.g., Fuzzy Logic and rules-based AI (e.g., Prolog)?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-11-27T04:21:47.137Z
Comments.Text: Isn't statistics itself rule based from the point of view of human understanding? For example, does cross-validation count as some kind of rule?
Comments.UserDisplayName: cinch
Tags: <fuzzy-logic><statistics>
Title: Why has statistics-based AI become more popular than other forms of AI?
UserDisplayName: user366312
ThreadText: # Why has statistics-based AI become more popular than other forms of AI?
  
  (Asked by: username_0 on 2022-09-11)
  
  What is the fundamental reason that statistics-based AI (e.g., ML and Neural Net) has become more popular than other forms of AI, e.g., Fuzzy Logic and rules-based AI (e.g., Prolog)?
  
  **Tags:** fuzzy-logic, statistics
  > **Comments:**
  > **username_1**: Isn't statistics itself rule based from the point of view of human understanding? For example, does cross-validation count as some kind of rule?  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2022-09-13. Score: 5 | Accepted answer
  
  The availability of large data sets.
  
  In symbolic/rule-based AI, the 'knowledge' has to be hand-coded, usually by experts. This is expensive and limited to small-scale problems only.
  
  In statistical AI/Machine Learning approaches, this is replaced by training a system on data. With very large amounts of data it is possible to achieve results that are not possible with rule-based approaches. In the past, such data sets were usually not available.
  
  However, this also means that the AI system has become somewhat of a black box, as it is not possible (at least not easily) *why* the system has behaved in a particular way.
  
  So in areas where this is important (eg banking and finance), rule-based approaches are still valuable.
  
  > **Comments:**
  > **username_0**: What about Fuzzy logic?  
  > **username_2**: Fuzzy logic is basically a different way to express rule-based information.  
  
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