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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.
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.
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Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
An example of user-generated content, a personalised sign and objects in the virtual world of Second Life. User-generated content (UGC), alternatively known as user-created content (UCC), emerged from the rise of intelligent web services which allow everyday users to create content, such as images, videos, audio, text, testimonials, and software (e.g. video game mods) and interact with other ...
1. From the inbox, click Compose. 2. In the "To" field, type the name or email address of your contact. 3. In the "Subject" field, type a brief summary of the email.