Kyle Hill on How ChatGPT works internally

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Discussion Overview

The discussion centers around a video by Kyle Hill that explores the internal workings of ChatGPT, particularly focusing on the technical and conceptual challenges faced by the development team. Participants engage with the content of the video, discussing its relevance to the forum's guidelines on popular science and the nature of large language models (LLMs).

Discussion Character

  • Debate/contested
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • Some participants express concern about the appropriateness of discussing popular science content in the forum, questioning whether it aligns with forum guidelines.
  • Others argue that the video presents valuable insights into the technical challenges of LLMs and cites relevant academic sources, such as the GPT-3.5 paper.
  • A participant notes that the video provides a gentle introduction to the basics of LLMs without sensationalizing the technology.
  • One participant shares their perspective as a programmer, highlighting the informative nature of the video regarding GPT's non-sentience and the statistical methods used in its training.
  • Another post introduces a different video that discusses practical applications of ChatGPT, specifically the use of temperature settings to modify responses.

Areas of Agreement / Disagreement

Participants generally disagree on the appropriateness of discussing pop science in the forum, with some advocating for its relevance while others remain skeptical. The discussion on the technical aspects of ChatGPT appears to be more aligned, though no consensus is reached on the broader topic of popular science content.

Contextual Notes

Some participants reference the need for technical rigor in discussions, suggesting that videos may not always serve as reliable sources in technical forums. There is also an acknowledgment of the limitations of popular science narratives in accurately representing complex technologies.

Who May Find This Useful

Readers interested in the technical aspects of large language models, the development of AI technologies, and the intersection of popular science with technical discourse may find this discussion relevant.

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Kyle Hill gets into the internals of how ChatGPT works:

 
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Likes   Reactions: Demystifier, nsaspook, Tom.G and 2 others
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Not complaining but I thought we weren't allowed to discuss pop sci in the forum
 
Feynstein100 said:
Not complaining but I thought we weren't allowed to discuss pop sci in the forum
There are some PF forums where it may be appropriate, depending on the subject. I haven't watched the video above, but it sounds interesting. Posting videos as sources in the technical Physics and Math forums is almost never a good idea.
 
This guy is a more serious if not silly science reporter and has some really good video content. He gets into some of the conceptual and technical challenges faced by the GPT team to make it work well. He cites the GPT-3.5 paper and provides insight into how things are done.
 
It's a decent video that gently describes the basics of Large Language Models (LLMs) and how they function. It's not in the PopSci vein of "ChatGPT will end life as we know it!!!"
 
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As a programmer, this was along the lines of something I wanted to see. I posted an earlier one in another thread where the presenter went through the GPT paper looking for things. But I haven't seen a followup to it.

Kyle is very emphatic when he says GPT is not sentient and that it doesn't know what its generating and then goes to show the extensive training and statistical analysis being used to select the best choice of words which was quite enlightening for me.
 
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Here's another interesting video on using ChatGPT:



The presenter talks about using the temperature setting to change GPT responses and shows some related tools you can use to explore GPT models.
 

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