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A Zalgo-text effect applied to the words "ZALGO TEXT" Zalgo text, also known as cursed text or glitch text, is digital text that has been modified with numerous combining characters, Unicode symbols used to add diacritics above or below letters, to appear frightening or glitchy.
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. [130]
The generation effect is typically achieved in cognitive psychology experiments by asking participants to generate words from word fragments. [2] This effect has also been demonstrated using a variety of other materials, such as when generating a word after being presented with its antonym, [3] synonym, [1] picture, [4] arithmetic problems, [2] [5] or keyword in a paragraph. [6]
A character generator, often abbreviated as CG, is a device or software that produces static or animated text (such as news crawls and credits rolls) for keying into a video stream. Modern character generators are computer-based, and they can generate graphics as well as text.
The Postmodernism Generator is a computer program that automatically produces "close imitations" of postmodernist writing. It was written in 1996 by Andrew C. Bulhak of Monash University using the Dada Engine, a system for generating random text from recursive grammars. [1] A free version is also hosted online.
Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...
A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .
Filler text (also placeholder text or dummy text) is text that shares some characteristics of a real written text, but is random or otherwise generated. It may be used to display a sample of fonts , generate text for testing, or to spoof an e-mail spam filter .