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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.
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]
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, Inc. is an American transcription software company based in Mountain View, California. The company develops speech to text transcription applications using artificial intelligence and machine learning. Its software, called Otter, shows captions for live speakers, and generates written transcriptions of speech. [1]
Scribd Inc. (pronounced / ˈ s k r ɪ b d /) operates three primary platforms: Scribd, Everand, and SlideShare.Scribd is a digital document library that hosts over 195 million documents.
Another study [37] showed that Turnitin failed to detect text produced by popular free Internet-based paraphrasing tools. Besides, more sophisticated machine learning techniques, such as automated paraphrasing , can produce natural and expressive text, which is virtually impossible for Turnitin to detect.
Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
Various techniques exist to train policies to solve tasks with deep reinforcement learning algorithms, each having their own benefits. At the highest level, there is a distinction between model-based and model-free reinforcement learning, which refers to whether the algorithm attempts to learn a forward model of the environment dynamics.