Maximize ChatGPT Output: Easy Word Count Fix

Last updated: Jun 22, 2023

The video is about testing different methods to understand why ChatGPT does not follow word count commands and how to manage and tackle the issue.

The video is about testing different methods to maximize the word count output of ChatGPT, a language model AI, when given specific commands. The speaker demonstrates how ChatGPT often fails to follow commands for longer word counts and proposes hypotheses for why this happens. The speaker then tests different methods to see if they can increase the word count output and shares their findings.

  • The video tests different methods to understand why ChatGPT does not follow word count commands.
  • The main problem is that ChatGPT does not obey word count commands.
  • The presenter tests five different methods to tackle the problem.
  • The sweet spot for word count in ChatGPT is around 1000 words.
  • Chegebd understands tokens better than numbers.
  • Direct requests are another way to bypass word count commands.
  • GBD4 passes AI detection better than GBD3.5.
  • Writing in steps will most often than not return a lengthy response.
  • There are a couple of ways to do priming.

????Maximize ChatGPT Output: Easy Word Count Fix - YouTube

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Introduction

  • The video is about testing different methods to understand why ChatGPT does not follow word count commands and how to manage and tackle the issue.
  • The video is a live testing video where the presenter has quite a few hypotheses which he wants to test.
  • The main question in question is why is ChatGPT not following the word count commands.
  • Whenever you're trying to direct ChatGPT into a specific word count territory, it just doesn't obey for some reason.
  • The larger the word count that we're expecting of ChatGPT, the worst result we get.
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The Problem

  • ChatGPT does not follow the word count commands.
  • Whenever you're trying to direct ChatGPT into a specific word count territory, it just doesn't obey for some reason.
  • The larger the word count that we're expecting of ChatGPT, the worst result we get.
  • The presenter will be using ChatGPT 3.5 to exemplify the problem he's having.
  • The presenter will be prompting video to write on a certain topic and he has chosen a topic that by default is inherently long.
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The Testing

  • The presenter will be testing five different methods to tackle the problem.
  • There will be secret number one and secret number two, which are pretty plain but if you want to know how he tackles long-form copy using one command only, you'd better stick to the end.
  • The presenter will be starting a new chat each time just to avoid any prior knowledge that the AI has of what he wants to do.
  • The initial goal was 500 words and it returned back 581.
  • The presenter will be revealing why he thinks ChatGPT miscalculates severely the word counts that its outputs versus what he wants it to do.
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????Maximize ChatGPT Output: Easy Word Count Fix - YouTube

The Results

  • The first time the presenter asked ChatGPT to write an article, it actually exceeded the word count.
  • The presenter thinks that ChatGPT miscalculates severely the word counts that its outputs versus what he wants it to do.
  • The word count output would depend on the topic.
  • The presenter tested for 650 words and got back 581 words.
  • The presenter tested for 1000 words and got back 650 words more or less.
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Word Count Sweet Spot

  • The sweet spot for word count in ChatGPT is around 1000 words.
  • JJ Jupiteri seems to adhere to this word count the most.
  • Asking for anything 500 and below will result in an overestimation of word counts.
  • Asking for something like 2000 words will create a very short output.
  • Word count commands do not work well with ChatGPT.
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Tokens vs. Words

  • Chegebd understands tokens better than numbers.
  • Tokens are a common knowledge, where talking is half a word.
  • Writing a 2000 token article gets closer to 1000 words.
  • Word count commands do not work well with tokens either.
  • Asking for 3000 tokens was a fluke and did not work.
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Direct Request

  • Direct requests are another way to bypass word count commands.
  • Direct requests involve copying the initial command.
  • Word count commands still do not work well with direct requests.
  • It is necessary to move around the commands to make them work.
  • ChatGPT does not understand word count commands well.
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Long Form Copy

  • The biggest difference between GBD3.5 and GBD4 is formatting.
  • GBD4 uses formatting whenever an article is written.
  • GBD3.5 does not use formatting unless specifically asked to.
  • GBD4 passes AI detection better than GBD3.5.
  • There is not much difference between GBD3.5 and GBD4 as a reader.
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Testing Different Methods

  • The video is about testing different methods to understand why ChatGPT does not follow word count commands and how to manage and tackle the issue.
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Writing in Steps

  • Writing in steps will most often than not return a lengthy response.
  • It is almost 1200 words.
  • It somewhat worked, although it came almost 900 to 800 words short of the targets.
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Writing in Paragraphs

  • Writing in paragraphs is not sufficient.
  • It is more like an outline.
  • Chegebra is horrible with the word count.
  • It was close to finishing the whole thing and 600 words, so it was an epic fail.
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Priming Techniques

  • There are a couple of ways to do priming.
  • The first priming technique would be just having a nice little chat with Chad.
  • The second priming technique would be to use a prompt like "I want you to write about how to mine crypto at home using 20 let's say 200 words paragraphs."
  • The paragraphs are slightly longer than the previous version.
  • This time around, the video will let it finish.
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Testing ChatGPT's Word Count Commands

  • Chagibidi is capable of following commands.
  • Chubby can write a 2000-word article based on the topic discussed with it.
  • Using steps in the prompt can convert to a longer workout.
  • Priming in a certain manner does not work.
  • Assuming a role of a prolific writer who likes very detailed paragraphs can produce less than 600 words.
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Maximizing ChatGPT Output

  • ChatGPT is not doing what you want because it is not a calculator, it is a predictive model.
  • Exhaust the topic using predictive modeling.
  • If the model thinks the topic has been addressed sufficiently, it will limit the word count.
  • If the model thinks it's a five-paragraph topic, it will write five paragraphs word by word.
  • Using a lazy prompt can still produce unexpected results.
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Managing ChatGPT's Word Count

  • Use a more specific prompt to get the desired word count.
  • Use a more detailed prompt to exhaust the topic.
  • Use a predictive model to limit the word count.
  • Use a calculator to check the word count.
  • Use a speed typing course to improve typing skills.
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Tackling ChatGPT's Word Count Issue

  • Understand that ChatGPT is a predictive model, not a calculator.
  • Use a more specific and detailed prompt to get the desired word count.
  • Use a predictive model to limit the word count.
  • Use a calculator to check the word count.
  • Improve typing skills to increase productivity.
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Effect of Topic on Output Length

  • ChatGPT produces shorter content for shallow or small topics.
  • For robust topics, ChatGPT produces longer content.
  • ChatGPT predicts the next word based on the first one, which affects word count.
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Using Outlines to Maximize Output

  • Providing a detailed outline generally results in longer outputs.
  • Outlines help ChatGPT understand the structure of the content.
  • Outlines should be detailed and contain FAQs to elongate the outline.
  • Providing a word count in the outline gives ChatGPT a point of reference.
  • ChatGPT may not understand the notion of the workout yet.
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Testing the Prompt Library

  • Writing paragraph by paragraph is the only way to write a long article, according to most ChatGPT users.
  • The prompt library contains a chain or sequence prompt that produces a number of questions, which serve as the outline.
  • The prompt library's chain or sequence prompt treats every question as a separate article.
  • Editing is required to remove fluff and improve the output.
  • The prompt library's chain or sequence prompt is effective in producing longer outputs.
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Conclusion

  • Providing a detailed outline and using the prompt library's chain or sequence prompt can help maximize ChatGPT output.
  • ChatGPT's output length is affected by the topic and the level of detail in the outline.
  • ChatGPT may not understand the concept of word count yet.
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Maximizing ChatGPT Output

  • The video tests different methods to understand why ChatGPT does not follow word count commands.
  • The issue is tackled by experimenting with different prompts and outlines.
  • Two secrets to maximizing output are revealed: using a specific outline and adding more context to the prompt.
  • One method involves using a specific outline with a clear structure and subheadings to guide the AI's response.
  • Another method involves adding more context to the prompt, such as providing examples or asking specific questions, to encourage the AI to generate more detailed responses.
  • The final output produced by the AI is a very long and detailed article, with a word count of 30,100 words.

Watch the video on YouTube:
????Maximize ChatGPT Output: Easy Word Count Fix - YouTube

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