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  2. Artificial intelligence art - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_art

    Synthetic media, which includes AI art, was described in 2022 as a major technology-driven trend that will affect business in the coming years. [91] Harvard Kennedy School researchers voiced concerns about synthetic media serving as a vector for political misinformation soon after studying the proliferation of AI art on the X platform. [101]

  3. NovelAI - Wikipedia

    en.wikipedia.org/wiki/NovelAI

    For AI art generation, which generates images from text prompts, NovelAI uses a custom version of the source-available Stable Diffusion [2] [14] text-to-image diffusion model called NovelAI Diffusion, which is trained on a Danbooru-based [5] [1] [15] [16] dataset. NovelAI is also capable of generating a new image based on an existing image. [17]

  4. Generative artificial intelligence - Wikipedia

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

    Producing high-quality visual art is a prominent application of generative AI. [65] Generative AI systems trained on sets of images with text captions include Imagen , DALL-E , Midjourney , Adobe Firefly , FLUX.1 , Stable Diffusion and others (see Artificial intelligence art , Generative art , and Synthetic media ).

  5. Get unlimited AI art from this $59 WordPress plugin - AOL

    www.aol.com/unlimited-ai-art-59-wordpress...

    TL;DR: As of March 26, you can get a lifetime license to the DALL-E AI Image Generator and WordPress Plugin for only $59 instead of $299 — that's 80% in savings.Whether you’re writing a blog ...

  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. StyleGAN - Wikipedia

    en.wikipedia.org/wiki/StyleGAN

    Like SinGAN, it decomposes the generator as =, and the discriminator as =. During training, at first only G N , D N {\displaystyle G_{N},D_{N}} are used in a GAN game to generate 4x4 images. Then G N − 1 , D N − 1 {\displaystyle G_{N-1},D_{N-1}} are added to reach the second stage of GAN game, to generate 8x8 images, and so on, until we ...

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