Answers.Body: <blockquote>
  <p>DALL·E is a 12-billion parameter version of GPT-3 trained to generate images from text descriptions</p>
  </blockquote>
  <p>should be the same data they used to train the GPT-3</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-21T05:26:31.890Z
Answers.Text: but what did they use as output for their input text
Answers.UserDisplayName: Gavin
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-21T10:19:12.360Z
Answers.Text: they are mapping text to images. so their dataset should have a pairs of text and image and their model trained on mapping these pairs.
Answers.UserDisplayName: Thulfiqar
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-21T03:27:58.750Z
Answers.LastActivityDate: 2021-01-21T03:27:58.750Z
Answers.UserDisplayName: Thulfiqar
Body: <p>Dall-E, it can generate many imaginative images from the description, even some peculiar images, how did they actually create this kind of dataset to train this AI , because there is not much of that kind of data which include weird images and descriptive text, how did they create this massive dataset. Does anyone have any idea?</p>
  <p>If you have no idea what I am talking about, please refer to this link: <a href="https://openai.com/blog/dall-e/" rel="nofollow noreferrer">https://openai.com/blog/dall-e/</a>.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-21T12:09:14.207Z
Comments.Text: Have you read the article that you're linking us to, i.e. https://openai.com/blog/dall-e/? It says they are using a smaller version of GPT-3. They even say that they use a dataset of descriptions and image pairs. I didn't fully read it, but this already looks like a partial answer to your question. So, what's your question?
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-21T14:30:49.040Z
Comments.Text: yes, it gets clearer for me when I read deeper into it, and I don't quite understand how this data is obtained and reformatted for training to make this AI working. thank you
Comments.UserDisplayName: Gavin
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-21T14:32:02.743Z
Comments.Text: Ok, then edit your post to ask specifically that (although that will actually and partially invalidate the current answer below), i.e. how exactly is the dataset of text-images created? How many images does it contain? What are the sizes of these images, etc? Or whatever you are really insterested in. Because, otherwise, this post doesn't make much sense, given that the answer to the current question can be found in the article that you're linking to and suggesting us to read in order to be familiar with Dall-E (which you supposedly were).
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-22T12:22:07.050Z
Comments.Text: That edit didn't really improve the post. Please, read my comments above again.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-11-18T03:46:03.133Z
Comments.Text: Some answers here point to DALL-E using the same dataset as GPT-3, but that doesn't answer HOW the dataset was created or anything about the images used in the dataset to train DALL-E. At some point, an image dataset was needed to train an AI, either one that generated more images for DALL-E to learn from, or directly to train DALL-E.
Comments.UserDisplayName: Forestrf
Tags: <natural-language-processing><datasets><generative-adversarial-networks><image-generation><natural-language-understanding>
Title: What dataset might Elon Musk's Dall-E have used?
UserDisplayName: Gavin
ThreadText: # What dataset might Elon Musk's Dall-E have used?
  
  (Asked by: username_0 on 2021-01-21)
  
  Dall-E, it can generate many imaginative images from the description, even some peculiar images, how did they actually create this kind of dataset to train this AI , because there is not much of that kind of data which include weird images and descriptive text, how did they create this massive dataset. Does anyone have any idea?
  
  If you have no idea what I am talking about, please refer to this link: <https://openai.com/blog/dall-e/>.
  
  **Tags:** natural-language-processing, datasets, generative-adversarial-networks, image-generation, natural-language-understanding
  > **Comments:**
  > **username_1**: Have you read the article that you're linking us to, i.e. https://openai.com/blog/dall-e/? It says they are using a smaller version of GPT-3. They even say that they use a dataset of descriptions and image pairs. I didn't fully read it, but this already looks like a partial answer to your question. So, what's your question?  
  > **username_0**: yes, it gets clearer for me when I read deeper into it, and I don't quite understand how this data is obtained and reformatted for training to make this AI working. thank you  
  > **username_1**: Ok, then edit your post to ask specifically that (although that will actually and partially invalidate the current answer below), i.e. how exactly is the dataset of text-images created? How many images does it contain? What are the sizes of these images, etc? Or whatever you are really insterested in. Because, otherwise, this post doesn't make much sense, given that the answer to the current question can be found in the article that you're linking to and suggesting us to read in order to be familiar with Dall-E (which you supposedly were).  
  > **username_1**: That edit didn't really improve the post. Please, read my comments above again.  
  > **username_2**: Some answers here point to DALL-E using the same dataset as GPT-3, but that doesn't answer HOW the dataset was created or anything about the images used in the dataset to train DALL-E. At some point, an image dataset was needed to train an AI, either one that generated more images for DALL-E to learn from, or directly to train DALL-E.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_3 on 2021-01-21. Score: 1
  
  > DALL·E is a 12-billion parameter version of GPT-3 trained to generate images from text descriptions
  
  should be the same data they used to train the GPT-3
  
  > **Comments:**
  > **username_0**: but what did they use as output for their input text  
  > **username_3**: they are mapping text to images. so their dataset should have a pairs of text and image and their model trained on mapping these pairs.  
  
  ---
  
  