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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.
A paper generator is computer software that composes scholarly papers in the style of those that appear in academic journals or conference proceedings. Typically, the generator uses technical jargon from the field to compose sentences that are grammatically correct and seem erudite but are actually nonsensical. [ 1 ]
This task heavily relies on prompt engineering in order for the AI to give satisfactory results. For me, I settled with the prompt "Can you copyedit this paragraph from Wikipedia while still keeping the tone and the information as intact as possible:" followed by the paragraph without citations in plain text.
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]
According to one user, who had access to a private early release of the OpenAI GPT-3 API, GPT-3 was "eerily good" at writing "amazingly coherent text" with only a few simple prompts. [20] In an initial experiment 80 US subjects were asked to judge if short ~200 word articles were written by humans or GPT-3.
A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [ 3 ] providing relevant context, or describing a character for the AI to mimic.
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