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How does DALL-E work?
To create DALL-E images, GPT-3, a model based on the Transformer deep neural network architecture, is used. This model is responsible for accurately interpreting the data received from the user's query. The CLIP (Contrastive Language-Image Pre-training) model is used to process this data and transform it into a visual product. CLIP is trained on millions of images and their associated captions, analyzing their relationship. Thus, CLIP "understands" the user's live language and uses it to find relevant source images.

In addition, DALL-E uses the GLIDE model, which converts the concept into a final low- israel rcs data resolution image, as well as a neural network that scales and adds detail to the image.


What is the difference between the DALL-E versions?
An improved version of the original DALL-E, known as DALL-E 2, was introduced on April 6, 2022. Unlike its predecessor, this updated model demonstrated significant improvements in generating realistic images that more accurately match the user's prompts. The resolution of these images has also increased by 4 times. DALL-E 2 understands live speech better and is able to work with more complex questions. Among the advantages of the model are: