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Thankfully, researchers at the Allen Institute for Artificial Intelligence have developed a new model to summarize text from scientific papers, and present it in a few sentences in the form of TL ...
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.
GPT-2's flexibility was described as "impressive" by The Verge; specifically, its ability to translate text between languages, summarize long articles, and answer trivia questions were noted. [ 17 ] A study by the University of Amsterdam employing a modified Turing test found that at least in some scenarios, participants were unable to ...
6. Explain complex topics in new ways. Generative AI can even help you better understand the topics you’re writing about, especially if the tool you’re using is connected to the internet.
Generative AI systems trained on words or word tokens include GPT-3, GPT-4, GPT-4o, LaMDA, LLaMA, BLOOM, Gemini and others (see List of large language models). They are capable of natural language processing , machine translation , and natural language generation and can be used as foundation models for other tasks. [ 62 ]
Meta AI (formerly Facebook) also has a generative transformer-based foundational large language model, known as LLaMA. [48] Foundational GPTs can also employ modalities other than text, for input and/or output. GPT-4 is a multi-modal LLM that is capable of processing text and image input (though its output is limited to text). [49]
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