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Developed by OpenAI, DALL-E is an AI program trained to generate images from text descriptions. It was originally launched back in January of 2021, but now the second generation of the artificial ...
DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E, and pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
DALL-E is an artificial intelligence art generator that creates images from detailed text descriptions that a user types into a text box.
It consists of two subcorpora; one contains the English originals and the other their Arabic translations. As for the English subcorpus, it contains 3,794,677 word tokens, with 78,606 word types. The Arabic subcorpus has a slightly fewer word tokens (3,755,741), yet differs greatly in terms of the number of word types, which is 143,727.
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
Any fears that OpenAI had lost its magic after November’s crisis over the firing (and subsequent rehiring) of Sam Altman look like they can now be emphatically put to bed.
In 2021, using the influential large language generative pre-trained transformer models that are used in GPT-2 and GPT-3, OpenAI released a series of images created with the text-to-image AI model DALL-E 1. [50] It was an autoregressive generative model with essentially the same architecture as GPT-3.
Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [231] DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images.