Body: <p>As a language model, <strong>ChatGPT</strong> generate responses based on patterns they have learned from the data they were trained on. However, it may not always provide a <em>perfect</em> or <em>complete answer</em> to <strong>novel</strong> or <strong>unexpected inputs</strong>, <code>indicating that it does not have a genuine understanding of the task or concept at hand</code>.</p>
  <blockquote>
  <p>The question then becomes whether inability of <strong>ChatGPT</strong> or other language based AI system to fully understand and respond to <strong>novel</strong> or <strong>unexpected inputs</strong> is a reflection of the <strong>inherent limitations</strong> of language as a medium for conveying meaning and understanding?</p>
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Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-12-17T22:54:17.177Z
Comments.Text: Do you have any examples in mind about your *novel* or *unexpected* inputs? Are they in the sense of purely syntactically technical/tricky or semantically philosophical?
Comments.UserDisplayName: cinch
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-12-17T23:08:39.543Z
Comments.Text: "No, I don't have any specific examples in mind. I was asking about ChatGPT's general ability to understand novel inputs, regardless of whether they are purely syntactically technical or semantically philosophical in nature. I was wondering if ChatGPT's limited understanding of novel inputs reveals limitations in language's ability to convey meaning more broadly."
Comments.UserDisplayName: Faizy
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-03-20T10:56:01.553Z
Comments.Text: There are people e.g. Yann Le Cun, who believe that language is not enough to provide a LLM or other system a world model. World models / task models / environment  models are important in logic to codify what you know to be able to make novel logical outcomes.
Comments.UserDisplayName: benbyford
Tags: <natural-language-processing><open-ai><gpt-3><chatgpt>
Title: Does ChatGPT's limited understanding of novel inputs reveal limitations in language's ability to convey meaning?
UserDisplayName: Faizy
ThreadText: # Does ChatGPT's limited understanding of novel inputs reveal limitations in language's ability to convey meaning?
  
  (Asked by: username_0 on 2022-12-17)
  
  As a language model, **ChatGPT** generate responses based on patterns they have learned from the data they were trained on. However, it may not always provide a *perfect* or *complete answer* to **novel** or **unexpected inputs**, `indicating that it does not have a genuine understanding of the task or concept at hand`.
  
  > The question then becomes whether inability of **ChatGPT** or other language based AI system to fully understand and respond to **novel** or **unexpected inputs** is a reflection of the **inherent limitations** of language as a medium for conveying meaning and understanding?
  
  **Tags:** natural-language-processing, open-ai, gpt-3, chatgpt
  
  > **Comments:**
  > **username_1**: Do you have any examples in mind about your *novel* or *unexpected* inputs? Are they in the sense of purely syntactically technical/tricky or semantically philosophical?  
  > **username_0**: "No, I don't have any specific examples in mind. I was asking about ChatGPT's general ability to understand novel inputs, regardless of whether they are purely syntactically technical or semantically philosophical in nature. I was wondering if ChatGPT's limited understanding of novel inputs reveals limitations in language's ability to convey meaning more broadly."  
  > **username_2**: There are people e.g. Yann Le Cun, who believe that language is not enough to provide a LLM or other system a world model. World models / task models / environment  models are important in logic to codify what you know to be able to make novel logical outcomes.  
  
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  ## 0 answers
  
  