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A related application is summarizing news articles. Imagine a system, which automatically pulls together news articles on a given topic (from the web), and concisely represents the latest news as a summary. Image collection summarization is another application example of automatic summarization.
Based on the results, AI models seem to be a very powerful brainstorming tool, and via prompt engineering, these AI do allow an impressive amount of refinement to the plan. AI can also be a great tool as a pointer to potential sources and can remind editors of Wikipedia's content policy (NPOV, RS, etc.)
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 ...
(and the corresponding index file, pages-articles-multistream-index.txt.bz2) pages-articles.xml.bz2 and pages-articles-multistream.xml.bz2 both contain the same xml contents. So if you unpack either, you get the same data. But with multistream, it is possible to get an article from the archive without unpacking the whole thing.
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.
Earth; To listen to this article click on play (AI narration).Article version: 28 October 2024. Easter Island (similar to this Fall of Civilizations podcast) Pig intelligence (short & interesting) Aristotle (like a mix between brief biographical audiobook, a history podcast and an abridged audiobook about a philosophy as an introduction or overview) Linux Two-level utilitarianism (short ...
Subsets of the Wikipedia corpus are considered the largest well-curated data sets available for AI training. [ 19 ] [ 20 ] A 2012 paper reported that more than 1,000 academic articles, including those using artificial intelligence, examine Wikipedia, reuse information from Wikipedia, use technical extensions linked to Wikipedia, or research ...
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 ]
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