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.
Retrieval-augmented generation - Wikipedia
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 ...
深度好文！最全的大模型 RAG 技术概览 - 知乎 - 知乎专栏
2024年1月20日 · 检索增强生成（Retrieval Augmented Generation, RAG）是一种技术，它通过从数据源中检索信息来辅助大语言模型（Large Language Model, LLM）生成答案。 简而言之，RAG 结合了搜索技术和大语言模型的提示词功能，即向模型提出问题，并以搜索算法找到的信息作为背景上下文，这些查询和检索到的上下文信息都会被整合进发送给大语言模型的提示中。 到了2023年，基于大语言模型的系统中，RAG 已成为最受欢迎的架构之一。 许多产品几乎完全基 …
什么是 RAG？— 检索增强生成 AI 详解 — AWS
检索增强生成（RAG）是指对大型语言模型输出进行优化，使其能够在生成响应之前引用训练数据来源之外的权威知识库。 大型语言模型（LLM）用海量数据进行训练，使用数十亿个参数为回答问题、翻译语言和完成句子等任务生成原始输出。 在 LLM 本就强大的功能基础上，RAG 将其扩展为能访问特定领域或组织的内部知识库，所有这些都无需重新训练模型。 这是一种经济高效地改进 LLM 输出的方法，让它在各种情境下都能保持相关性、准确性和实用性。 为什么检索增强生成 …
RAG and generative AI - Azure AI Search | Microsoft Learn
2024年9月3日 · Azure AI Search is a proven solution for information retrieval in a RAG architecture. It provides indexing and query capabilities, with the infrastructure and security of the Azure cloud. Through code and other components, you can design a comprehensive RAG solution that includes all of the elements for generative AI over your proprietary content.
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. Under the hood, LLMs are neural networks, typically measured by how many parameters they contain.
A Comprehensive Survey of Retrieval-Augmented Generation (RAG ...
2024年10月3日 · RAG combines retrieval mechanisms with generative language models to enhance the accuracy of outputs, addressing key limitations of LLMs. The study explores the basic architecture of RAG, focusing on how retrieval and generation are integrated to handle knowledge-intensive tasks.
What is retrieval-augmented generation (RAG)? - 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.
A first intro to Complex RAG (Retrieval Augmented Generation)
2023年12月13日 · In this article, we discuss various technical considerations when implementing RAG, exploring the concepts of chunking, query augmentation, hierarchies, multi-hop reasoning, and knowledge graphs....
What is RAG (retrieval augmented generation)? - IBM
2024年10月21日 · Retrieval augmented generation (RAG) is an architecture for optimizing the performance of an artificial intelligence (AI) model by connecting it with external knowledge bases. RAG helps large language models (LLMs) deliver more relevant responses at a higher quality.
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