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2. Flux (text-to-image model) - Wikipedia

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

   Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.

3. Photo-text art - Wikipedia

   en.wikipedia.org/wiki/Photo-text_art

   Photo-text, also written as photo/text, is a hybrid form of artistic expression that combines photography and textual elements to convey a message or create a narrative. This combination allows for a multi-dimensional experience for the viewer.

4. Artificial intelligence art - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence_art

   An example of prompt usage for text-to-image generation, using Fooocus. Prompts for some text-to-image models can also include images and keywords and configurable parameters, such as artistic style, which is often used via keyphrases like "in the style of [name of an artist]" in the prompt [88] and/or selection of a broad aesthetic/art style.

5. Generative artificial intelligence - Wikipedia

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

   Producing high-quality visual art is a prominent application of generative AI. [53] 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).

6. ASCII art - Wikipedia

   en.wikipedia.org/wiki/Ascii_art

   ASCII art of a fish. ASCII art is a graphic design technique that uses computers for presentation and consists of pictures pieced together from the 95 printable (from a total of 128) characters defined by the ASCII Standard from 1963 and ASCII compliant character sets with proprietary extended characters (beyond the 128 characters of standard 7-bit ASCII).

7. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   DALL-E has three components: a discrete VAE, an autoregressive decoder-only Transformer (12 billion parameters) similar to GPT-3, and a CLIP pair of image encoder and text encoder. [22] The discrete VAE can convert an image to a sequence of tokens, and conversely, convert a sequence of tokens back to an image.