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  2. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    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.

  3. 70,000 students are already using AI textbooks - AOL

    www.aol.com/finance/gen-ai-powered-textbooks...

    Leading textbook company Pearson has outfitted its digital textbooks—specifically 50 science titles, such as Intro to Biology and Intro to Chemistry—with generative AI study tools. As of this ...

  4. Multi-document summarization - Wikipedia

    en.wikipedia.org/wiki/Multi-document_summarization

    Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.

  5. Otter.ai - Wikipedia

    en.wikipedia.org/wiki/Otter.ai

    Otter.ai was founded as AISense in 2016 by Sam Liang and Yun Fu, two computer science engineers with a long history of working with artificial intelligence. [ 2 ] [ 3 ] In January 2018, the company announced a partnership with Zoom Video Communications to transcribe video meetings post-conference. [ 4 ]

  6. Facebook is reportedly developing AI to summarize news - AOL

    www.aol.com/facebook-reportedly-developing-ai...

    According to a report from BuzzFeed News, Facebook is testing an AI-powered tool called TL;DR (Too Long; Didn’t Read) to summarize news pieces, so you don’t even have to click through to read ...

  7. Semantic Scholar - Wikipedia

    en.wikipedia.org/wiki/Semantic_Scholar

    The AI technology is designed to identify hidden connections and links between research topics. [14] Like the previously cited search engines, Semantic Scholar also exploits graph structures, which include the Microsoft Academic Knowledge Graph , Springer Nature's SciGraph , and the Semantic Scholar Corpus (originally a 45 million papers corpus ...

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