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  2. Adobe Firefly - Wikipedia

    en.wikipedia.org/wiki/Adobe_Firefly

    Sensei has been used to power a variety of features in Adobe's creative software, such as object selection in Photoshop and image auto-enhancement in Lightroom. Firefly expanded its capabilities to Illustrator, Premiere Pro, and Express, particularly for generating photos, videos and audio to enhance or alter specific parts of the media.

  3. Ideogram (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

    Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The model is capable of generating legible text in the images compared to other text-to-image models. [1] [2]

  4. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    AI generated images have become much more advanced. In 2021, the release of DALL-E, a transformer-based pixel generative model, followed by Midjourney and Stable Diffusion marked the emergence of practical high-quality artificial intelligence art from natural language prompts.

  5. Do AI-generated images reinforce gender and racial ... - AOL

    www.aol.com/ai-generated-images-reinforce-gender...

    AI image generators have the ability to generate visual content from text descriptions. Anyone can enter a prompt—from detailed descriptions to simple keywords—and the AI generator brings ...

  6. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E was revealed by OpenAI in a blog post on 5 January 2021, and uses a version of GPT-3 [5] modified to generate images.. On 6 April 2022, OpenAI announced DALL-E 2, a successor designed to generate more realistic images at higher resolutions that "can combine concepts, attributes, and styles". [6]

  7. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    The generator is decomposed into a pyramid of generators =, with the lowest one generating the image () at the lowest resolution, then the generated image is scaled up to (()), and fed to the next level to generate an image (+ (())) at a higher resolution, and so on. The discriminator is decomposed into a pyramid as well.

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