Introducing DALL·E: Inspired by GPT-3 and Image-GPT from OpenAI

OpenAI successfully trained a network that can generate images from text captions. It is very similar to GPT-3 and Image GPT and produces amazing results.

DALL-E is a new neural network developed by OpenAI based on GPT-3.
In fact, it’s a smaller version of GPT-3 using 12-billion parameters instead of 175 billion. But it has been specifically trained to generate images from text descriptions, using a dataset of text-image pairs instead of a very broad dataset like GPT-3. It can create images from text captions using natural language, just like GPT-3 creates websites and stories.

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openai successfully trained a network

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able to generate images from text

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captions

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it's very similar to gpt3 and image gpt

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and produces amazing results let's see

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what it's really capable of

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dolly is a new neural network developed

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by openai based on gpt3

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in fact it's a smaller version of gpt3

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using

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12 billion parameters instead of 175

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billion parameters

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but it has been specifically trained to

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generate images from text descriptions

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using a data set of text image pairs

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instead of very broad

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data set like gpt3 it can generate

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images from text captions

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using natural language just like gpt3

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can create

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websites and stories it's a continuation

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of msgpt and gpt3 that i both covered in

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previous videos if you haven't watched

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them yet

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dolly is very similar to gpt3 in the way

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that it's also a transformer language

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model

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receiving text and images as inputs to

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output a final transformed

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image in many forms it can edit

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attributes of specific objects

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in images as you can see here or even

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control multiple objects and their

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attributes at the same time

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this is a very complicated task since

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the network has to understand the

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relation between the objects

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and create an image based on its

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understanding

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just take this example feeding to the

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network an emoji

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of a baby penguin wearing a blue hat

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red gloves green shirt and yellow pens

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all these components need to be

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understood the objects colors and even

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the location of the objects

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meaning that the gloves need to be both

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red and on the hands on the penguin

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the same thing for the rest and the

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results are very impressive considering

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the complexity of the task

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we can just see another more simple

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example where we just fed

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a small red block sitting on a large

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green block

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to the network now it just needs to know

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that there are two blocks

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their colors and one being smaller and

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the other bigger

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this seems very simple to us but it

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needs a really high level of

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understanding to be able to achieve this

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it is still

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not perfect as you can see but we are

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getting pretty close

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dolly is also able to change the

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viewpoint of a scene

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for example here we send an extreme

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close-up view of an eagle

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on a mountain and these are the results

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here we just changed the eagle for a fox

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and this is what is generated

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of course a simple caption can produce

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an infinitude of plausible images

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nobody knows what you have in mind if

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you think of a painting of a fox

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sitting in a field at sunrise there are

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many variables

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such as the fox itself its colors where

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it is looking at

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its position and we are not even talking

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about the background and the style of

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the painting

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fortunately since it is very similar to

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gpt3 we can

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add details to the input text and

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generate something much closer to what

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we expected

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just as you can see here with different

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styles of paintings

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it can also generate images using

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objects that are not related to each

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other

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like creating a realistic avocado chair

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or generate original and unseen

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illustrations

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like a new emoji in short they described

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dolly as a simple

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decoder only transformer if you are not

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familiar with transformers you should

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definitely watch the video i made

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covering them

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as i mentioned it receives both the text

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and an image as inputs

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in the form of tokens just like gpt3 to

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produce a transformed image

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it uses self-attention as i described in

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a previous video to understand the

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context of the text

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and sparse attention for the images

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there are not many details about how it

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works or how exactly it was trained

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but they will be publishing a paper

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explaining their approach

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in short this daily network shows that

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manipulating visual concepts

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through language is now within reach and

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i am excited to read their occurring

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paper

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of course this was just an overview of

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this new openai network

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called dolly i strongly invite you to

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follow openai's news

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about the upcoming paper for a better

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technical understanding

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or just subscribe to my channel i will

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be sure to cover it as soon as it's

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released

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