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  2. Wikipedia:Random - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Random

    Wikipedia:Random page patrol; Wikipedia:Random pages test; Wikipedia:Wiki-Link Game – fun with the Random article feature; Wikipedia:Enhanced Random Article – custom script; randomlink.js – tool to follow a random link or go to a random page in a category, list or WikiProject; Special:RandomInCategory; Template:Random page in category

  3. Lavarand - Wikipedia

    en.wikipedia.org/wiki/Lavarand

    It was covered under the now-expired U.S. patent 5,732,138, titled "Method for seeding a pseudo-random number generator with a cryptographic hash of a digitization of a chaotic system." by Landon Curt Noll, Robert G. Mende, and Sanjeev Sisodiya. From 1997 to 2001, [2] there was a website at lavarand.sgi.com demonstrating the technique.

  4. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

  5. 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.

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

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

    Ideogram was founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho to develop a better text-to-image model. [3]It was first released with its 0.1 model on August 22, 2023, [4] after receiving $16.5 million in seed funding, which itself was led by Andreessen Horowitz and Index Ventures.

  7. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    The second row is the same generator with a seed of 3, which produces a cycle of length 2. Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation.