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Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence (AI) model. [ 1 ] A prompt is natural language text describing the task that an AI should perform. [ 2 ]
Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
Download QR code; Print/export Download as PDF; Printable version; In other projects Wikidata item; Appearance. ... a form of prompt engineering in generative AI;
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
A human performs prompt engineering when they write a prompt. An AI performs in-context learning when it reads the prompt, understands it, and correctly responds. If you are an office worker and you want to know how to prompt GPT-4 to do your work for you, then you want an article about prompt engineering with practical information and lots of ...
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This is a list of free and open-source software packages , computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software ; the GNU project in particular objects to their works being referred to as open-source . [ 1 ]
Prompt (natural language), instructions issued to a computer system (such as a text-to-image artificial intelligence) in the form of written or spoken language. Prompt engineering, a concept in artificial intelligence in which the description of the task is embedded in the input, e.g., as a question, instead of it being implicitly given.