Body: <p>What subjects was ChatGPT trained on the most quantatively?
  It was trained on fiction and non-fiction books, wiki, and general web crawling.</p>
  <p>A bit of detective work tells me that compared to physics, GPT-3 knows:</p>
  <pre><code>12 times more about the color blue, 
  9 times more about the USA
  7 times more about hands
  6 times more about sport, 
  5 times more about covid, purple and china
  4 times more about hair, and america
  2 times more about tea and coffee
  ...
  It's as familiar with physics as it is with bread, sauce, beer, basketball, cheese, wine, 
  </code></pre>
  <p>Specifically, I wanted to know what % of ChatGPT's knowledge is about science, physics, chemistry, fiction, non-fiction, religion, wine etc.</p>
  <p>I found <a href="https://en.wikipedia.org/wiki/Wikipedia:Size_of_Wikipedia#/media/File:Size_of_English_Wikipedia_(1000_vol).svg" rel="nofollow noreferrer">this ratio of subject matters on wiki</a>. See also <a href="https://www.google.com/search?q=breakdown%20of%20Wikipedia%27s%20topic%20areas&amp;sxsrf=AJOqlzVWxRKXApiLv64qSHrbIor3i3ZlWg:1673460424318&amp;source=lnms&amp;tbm=isch&amp;sa=X&amp;ved=2ahUKEwiO6YvxjcD8AhVd_rsIHa6eCr0Q_AUoAXoECAEQAw&amp;biw=1366&amp;bih=646&amp;dpr=1.88#imgrc=BXngbqU0tur3yM" rel="nofollow noreferrer">here</a>.
  Also for <a href="https://www.shorttails.io/interactive-map-of-reddit-and-subreddit-similarity-calculator/" rel="nofollow noreferrer">reddit by subject matter</a>, it seams that less than 0.1% of commentators are on science topics.
  So I looked on the web, from a general crawl I found this is the ratio of thing ChatGPT knows about (list).</p>
  <p>I find that kindof weird and I wonder if there is a better way of finding what volume of words the web, wikipedia and contemporary book shops have, which would be reflected in GPT3.</p>
  <blockquote>
  <p>A LIST OF INTERNET TOPICS BY HITS:  physics 1.9 billion  electron 0.6
  billion chemistry 4 bn biology 3  voltage .6 android 13 apples 8 sauce
  2 toothpaste .2 president 3.3 cars 13 bn chevrolet .5 jeep .7
  volkswagen .6 sugar 4 computer 9 blender .5 microphone 1 b television
  3.7 hair 9bn cats 5bn dogs 5 horses 2.5 bn w0od 3.8 fantasy 2.1 harry potter 0.6 fiction 2.7 einstein .3 security 10 bn purple 10 pink 12
  violet 1.3
  4.2bn sport 12bn music 9bn football 4 basketball 1.6 tea 4.2 coffee 4.2 bread 2bn glass 5.7 soil 1.2 aluminium .5 rap 1.4 blue 25bn country 10bn beer 2 russia 2.7 france 7.5 italy 5.5 USA 18bn america
  9.2 england 6.4 africa 7bn japan 8.7 china 10 salad 1.5 keyboard 2.5 forum 6.5 printer 1.2 hands 15bn feet 4.7 box 1bn jeans 4bn depression
  4bn religion 3.7 islam 2.5 piano 1.6 guitar 1.5 chair 2.5 atlantic 1.1
  robot 1.9 maps 11bn clothes 6.6 roof 1.9 spices 1.6 shoes 3.7 camera
  7.7 tomato 1.6 solar 1.8 wheels 2.6 wine 2.8 cheese 2.1 market 6.9 covid 11bn</p>
  </blockquote>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-01-22T09:59:47.893Z
Comments.Text: Did you asked Chatgpt about your question ?
Comments.UserDisplayName: Ptit Xav
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-01-22T16:36:43.913Z
Comments.Text: Yes I did, it wasn't trained on text with specific information about it's training data, so the only way to ask it is through some tricks... I think there are also some censored topics, because I had a response like "ChatGPT was not able to load the module that you requested" the session stopped loading new input fields.... added the maths ratio of it's traning sources and their content of i.e. science (Reddit is 0.01% science) so I think it way less than 0.5% sciences.
Comments.UserDisplayName: bandybabboon
Tags: <gpt><chatgpt>
Title: What subjects was ChatGPT trained on the most? Science/history/movies/reddit posts/wikipedia/books/news?
UserDisplayName: bandybabboon
ThreadText: # What subjects was ChatGPT trained on the most? Science/history/movies/reddit posts/wikipedia/books/news?
  
  (Asked by: username_0 on 2023-01-11)
  
  What subjects was ChatGPT trained on the most quantatively?
  It was trained on fiction and non-fiction books, wiki, and general web crawling.
  
  A bit of detective work tells me that compared to physics, GPT-3 knows:
  
  ```
  12 times more about the color blue, 
  9 times more about the USA
  7 times more about hands
  6 times more about sport, 
  5 times more about covid, purple and china
  4 times more about hair, and america
  2 times more about tea and coffee
  ...
  It's as familiar with physics as it is with bread, sauce, beer, basketball, cheese, wine, 
  
  ```
  
  Specifically, I wanted to know what % of ChatGPT's knowledge is about science, physics, chemistry, fiction, non-fiction, religion, wine etc.
  
  I found [this ratio of subject matters on wiki](https://en.wikipedia.org/wiki/Wikipedia:Size_of_Wikipedia#/media/File:Size_of_English_Wikipedia_(1000_vol).svg). See also [here](https://www.google.com/search?q=breakdown%20of%20Wikipedia%27s%20topic%20areas&sxsrf=AJOqlzVWxRKXApiLv64qSHrbIor3i3ZlWg:1673460424318&source=lnms&tbm=isch&sa=X&ved=2ahUKEwiO6YvxjcD8AhVd_rsIHa6eCr0Q_AUoAXoECAEQAw&biw=1366&bih=646&dpr=1.88#imgrc=BXngbqU0tur3yM).
  Also for [reddit by subject matter](https://www.shorttails.io/interactive-map-of-reddit-and-subreddit-similarity-calculator/), it seams that less than 0.1% of commentators are on science topics.
  So I looked on the web, from a general crawl I found this is the ratio of thing ChatGPT knows about (list).
  
  I find that kindof weird and I wonder if there is a better way of finding what volume of words the web, wikipedia and contemporary book shops have, which would be reflected in GPT3.
  
  > A LIST OF INTERNET TOPICS BY HITS: physics 1.9 billion electron 0.6
  > billion chemistry 4 bn biology 3 voltage .6 android 13 apples 8 sauce
  > 2 toothpaste .2 president 3.3 cars 13 bn chevrolet .5 jeep .7
  > volkswagen .6 sugar 4 computer 9 blender .5 microphone 1 b television
  > 3.7 hair 9bn cats 5bn dogs 5 horses 2.5 bn w0od 3.8 fantasy 2.1 harry potter 0.6 fiction 2.7 einstein .3 security 10 bn purple 10 pink 12
  > violet 1.3
  > 4.2bn sport 12bn music 9bn football 4 basketball 1.6 tea 4.2 coffee 4.2 bread 2bn glass 5.7 soil 1.2 aluminium .5 rap 1.4 blue 25bn country 10bn beer 2 russia 2.7 france 7.5 italy 5.5 USA 18bn america
  > 9.2 england 6.4 africa 7bn japan 8.7 china 10 salad 1.5 keyboard 2.5 forum 6.5 printer 1.2 hands 15bn feet 4.7 box 1bn jeans 4bn depression
  > 4bn religion 3.7 islam 2.5 piano 1.6 guitar 1.5 chair 2.5 atlantic 1.1
  > robot 1.9 maps 11bn clothes 6.6 roof 1.9 spices 1.6 shoes 3.7 camera
  > 7.7 tomato 1.6 solar 1.8 wheels 2.6 wine 2.8 cheese 2.1 market 6.9 covid 11bn
  
  **Tags:** gpt, chatgpt
  
  > **Comments:**
  > **username_1**: Did you asked Chatgpt about your question ?  
  > **username_0**: Yes I did, it wasn't trained on text with specific information about it's training data, so the only way to ask it is through some tricks... I think there are also some censored topics, because I had a response like "ChatGPT was not able to load the module that you requested" the session stopped loading new input fields.... added the maths ratio of it's traning sources and their content of i.e. science (Reddit is 0.01% science) so I think it way less than 0.5% sciences.  
  
  ---
  
  ## 0 answers
  
  