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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.
Semantic Scholar is a research tool for scientific literature. It is developed at the Allen Institute for AI and was publicly released in November 2015. [2] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated summaries of scholarly papers. [3]
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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.
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 ]
Many Microsoft Outlook corporate users will soon have the option to create and send AI-written emails as the company widens its roll out Microsoft 365 Copilot, an artificial intelligence companion.
Notion AI uses artificial intelligence, which enables prediction of some results, text generation and solving arithmetic. It will also work with other datasets in response to an input by the user of the AI. This AI can automate some tasks and assist the user to make a paragraph or outline from a line of text.
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related to: ai that summarizes long articles apa 7 version 2 and 3