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Once a Markov chain is learned on a text corpus, it can then be used as a probabilistic text generator. [28] [29] The terms generative AI planning or generative planning were used in the 1980s and 1990s to refer to AI planning systems, especially computer-aided process planning, used to generate sequences of actions to reach a specified goal.
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List of Generation Z slang. Appearance. "If You Know You Know" redirects here. For the Pusha T song, see If You Know You Know (song). The following is a list of slang that is used or popularized by Generation Z (Gen Z), generally those born between the late 1990s and early 2010s in the Western world.
Postmodernism Generator. An example of a randomly generated title. 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]
Artificial intelligence art is visual artwork created through the use of an artificial intelligence (AI) program. [ 1 ] Artists began to create artificial intelligence art in the mid to late 20th century, when the discipline was founded. Throughout its history, artificial intelligence art has raised many philosophical concerns related to the ...
A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to ...
Using Lorem ipsum to focus attention on graphic elements in a webpage design proposal One of the earliest examples of the Lorem ipsum placeholder text on 1960s advertising. In publishing and graphic design, Lorem ipsum (/ ˌ l ɔː. r ə m ˈ ɪ p. s ə m /) is a placeholder text commonly used to demonstrate the visual form of a document or a typeface without relying on meaningful content.
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
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