Retrieval-augmented generation - Wikipedia
Retrieval Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities.
What is RAG? - Retrieval-Augmented Generation AI Explained
Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response.
What is RAG? A Deep Dive into Retrieval Augmented Generation
2024年11月6日 · At its core, Retrieval Augmented Generation is a hybrid approach that fuses two powerful AI techniques: information retrieval and text generation. Traditional language models, such as GPT-3, rely on vast amounts of pre-trained data. While these models are adept at producing fluent and coherent responses, they are limited by the static nature of ...
What is retrieval-augmented generation (RAG)? - McKinsey
2024年10月30日 · Retrieval-augmented generation, or RAG, is a process applied to large language models to make their outputs more relevant for the end user. A golden outline of a speech bubble is filled with a jumble of colorful, balloon-like spheres.
What Is Retrieval-Augmented Generation, aka RAG? - NVIDIA Blog
2023年11月15日 · Retrieval-augmented generation (RAG) is a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources. In other words, it fills a gap in how LLMs work.
Retrieval Augmented Generation (RAG): A Complete Guide
2024年10月24日 · Retrieval augmented generation (RAG) is a framework for blending generative models such as ChatGPT-3 or 4 with retrieval systems.
Retrieval-Augmented Generation for AI-Generated Content: A …
2024年2月29日 · Retrieval-Augmented Generation (RAG) has recently emerged as a paradigm to address such challenges. In particular, RAG introduces the information retrieval process, which enhances the generation process by retrieving relevant objects from available data stores, leading to higher accuracy and better robustness.
What is Retrieval-Augmented Generation (RAG)?
What is Retrieval-Augmented Generation (RAG)? RAG (Retrieval-Augmented Generation) is an AI framework that combines the strengths of traditional information retrieval systems (such as search and...
What is retrieval-augmented generation? - IBM Research
2023年8月22日 · Retrieval-augmented generation (RAG) is an AI framework for improving the quality of LLM-generated responses by grounding the model on external sources of knowledge to supplement the LLM’s internal representation of information.
Retrieval-Augmented Generation for Large Language Models: A …
2023年12月18日 · Retrieval-Augmented Generation (RAG) has emerged as a promising solution by incorporating knowledge from external databases. This enhances the accuracy and credibility of the generation, particularly for knowledge-intensive tasks, and allows for continuous knowledge updates and integration of domain-specific information.
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