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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.
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.
AI Chatbots in their own words: ChatGPT: OpenAI - GPT-3.5 (GPT-4 available) "I'm an AI language model created by OpenAI called GPT-3.5, designed to understand and generate human-like text based on ...
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.
Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [ 3 ] [ 4 ] Its developer, Perplexity AI, Inc., is based in San Francisco, California .
Shortcut your inbox: When you get a really long email, open your AI chatbot of choice, and type in the prompt, “Summarize this email for me. Tell me what I need to do, then write a thoughtful reply.