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(The term "quote generator" can also be used for software that randomly selects real quotations.) Further to its esoteric interest, a discussion of parody generation as a useful technique for measuring the success of grammatical inferencing systems is included, along with suggestions for its practical application in areas of language modeling ...
Racter is an artificial intelligence program that generates English language prose at random. [1] It was published by Mindscape for IBM PC compatibles in 1984, then for the Apple II , Mac , and Amiga .
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Versions of the Lorem ipsum text have been used in typesetting at least since the 1960s, when it was popularized by advertisements for Letraset transfer sheets. [1] Lorem ipsum was introduced to the digital world in the mid-1980s, when Aldus employed it in graphic and word-processing templates for its desktop publishing program PageMaker .
The Character Generator Protocol (CHARGEN) service is an Internet protocol intended for testing, debugging, and measurement purposes. The user receives a stream of bytes . Although the specific format of the output is not prescribed by RFC 864 , the recommended pattern (and a de facto standard ) is shifted lines of 72 ASCII characters repeating.
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.
Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text. This dataset can contain documents in many languages, but is in practice dominated by English text. [36]
Arora et al. (2016) [25] explain word2vec and related algorithms as performing inference for a simple generative model for text, which involves a random walk generation process based upon loglinear topic model. They use this to explain some properties of word embeddings, including their use to solve analogies.