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This is a list of disclosed AI generated images that are used in Wikipedia articles, for purposes other than explaining or demonstrating AI. These uses might need to be reviewed to make sure they are appropriate. No on-wiki discussion or consensus has determined to what extent AI images are acceptable, except in the context of upscaling ...
Some exceptions are if the text contains phrases like "as an AI model" or "as of my last knowledge update" and if the editor copy-pasted the prompt used to generate the text together with the AI response. Other indications include the presence of fake references or other obvious AI hallucinations. AI content sometimes takes a promotional tone ...
Terms proposed included "AI garbage", "AI pollution", and "AI-generated dross". [5] Early uses of the term "slop" as a descriptor for low-grade AI material apparently came in reaction to the release of AI image generators in 2022. [7] Its early use has been noted among 4chan, Hacker News and YouTube commentators as a form of in-group slang. [7]
Right now, AI-generated images still usually have a strange, hyperreal quality and inconsistencies in the things they depict, including garbled text, awkward transitions between objects, and ...
Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI).. However, the reliability of such software is a topic of debate, [1] and there are concerns about the potential misapplication of AI detection software by educators.
The vast majority of the synthetic images do not indicate in the posts or on the pages that they are AI-generated, even though Meta requires users to label AI-generated content on its platforms ...
Despite the many promises of generative AI’s future potential emanating from the tech industry, the gaffes from Meta’s AI image generator are the latest in a spate of incidents that show how ...
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.