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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.
Summarizing the article itself (lead expansion). Lead sections are nothing more than concise overviews, i.e. summaries , of article body content, and text summarization is one of the primary capabilities of LLMs which they were designed for.
This may be directly involved with creation of text content, or in support roles related to evaluating article quality, adding metadata, or generating images. As with any machine-generated content, care must be used when employing AI at scale or in applying it where the community consensus is to exercise more caution.
Generative AI can also be trained extensively on audio clips to produce natural-sounding speech synthesis and text-to-speech capabilities, exemplified by ElevenLabs' context-aware synthesis tools or Meta Platform's Voicebox. [53] AI-generated music from the Riffusion Inference Server, prompted with bossa nova with electric guitar
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 1000 academic articles, including those using artificial intelligence, examine Wikipedia, reuse information from Wikipedia, use technical extensions linked to Wikipedia, or research ...
The five-paragraph essay is a mainstay of high school writing instruction, designed to teach students how to compose a simple thesis and defend it in a methodical, easily graded package.
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