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  2. Wordtune - Wikipedia

    en.wikipedia.org/wiki/Wordtune

    Wordtune is an AI powered reading and writing companion capable of fixing grammatical errors, understanding context and meaning, suggesting paraphrases or alternative writing tones, and generating written text based on context. [1] [2] [3] It is developed by the Israeli AI company AI21 Labs. [4] [5] [6] [7]

  3. Predictive text - Wikipedia

    en.wikipedia.org/wiki/Predictive_text

    Predictive text could allow for an entire word to be input by single keypress. Predictive text makes efficient use of fewer device keys to input writing into a text message, an e-mail, an address book, a calendar, and the like. The most widely used, general, predictive text systems are T9, iTap, eZiText, and LetterWise/WordWise. There are many ...

  4. Get Paid to Write: Top 18 Sites That Pay (up to $1 per Word)

    www.aol.com/paid-write-top-18-sites-170032449.html

    And you should expect to be writing blog posts that are 2,000 words or more “unless it’s extremely wonderfully amazingly readable reading.” Pay : $300 to $1,000 per blog post

  5. Postmodernism Generator - Wikipedia

    en.wikipedia.org/wiki/Postmodernism_Generator

    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.

  6. Spelling suggestion - Wikipedia

    en.wikipedia.org/wiki/Spelling_suggestion

    Spelling suggestion is a feature of many computer software applications used to suggest plausible replacements for words that are likely to have been misspelled. Spelling suggestion features are commonly included in Internet search engines , word processors , spell checkers , medical transcription , automatic query reformulation , and frequency ...

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. Word2vec was developed by Tomáš Mikolov and colleagues at Google and published in 2013. Word2vec represents a word as a high-dimension vector of numbers which capture relationships between words.

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