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The first is generic summarization, which focuses on obtaining a generic summary or abstract of the collection (whether documents, or sets of images, or videos, news stories etc.). The second is query relevant summarization, sometimes called query-based summarization, which summarizes objects specific to a query. Summarization systems are able ...
NotebookLM can generate summaries, explanations, and answers based on content uploaded by users. It also includes "Audio Overviews," which summarize documents in a conversational, podcast-like format. [8] [1] In addition to text files, NotebookLM can process PDFs, Google Docs, websites, and Google Slides. [8]
Leo uses the LLaMA 2 LLM from Meta Platforms and the Claude LLM from Anthropic.. It can suggest followup questions, and summarize webpages, PDFs, and videos. [2] [3]Leo has a $15 per month premium version that enables more requests and uses larger LLMs.
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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]
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.
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