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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.
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.
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.
Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [ 129 ] and reweighting training data.
Users reported that it generated images of white historical figures like the Founding Fathers, Nazi soldiers, and Vikings as other races, and that it refused to process prompts such as "happy white people" and "ideal nuclear family". [112] [113] Google later apologized for "missing the mark" and took Gemini's image generator offline for updates ...
The software's name is a portmanteau of the names of animated robot Pixar character WALL-E and the Catalan surrealist artist Salvador Dalí. [ 15 ] [ 5 ] In February 2024, OpenAI began adding watermarks to DALL-E generated images, containing metadata in the C2PA (Coalition for Content Provenance and Authenticity) standard promoted by the ...
As the Feb. 6 NBA trade deadline approaches, teams and players are gearing up for the possibility of changes. Trade targets can often be broken up into three categories.
An autostereogram is a two-dimensional (2D) image that can create the optical illusion of a three-dimensional (3D) scene. Autostereograms use only one image to accomplish the effect while normal stereograms require two. The 3D scene in an autostereogram is often unrecognizable until it is viewed properly, unlike typical stereograms.