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.
RAG and generative AI - Azure AI Search | Microsoft Learn
2024年12月18日 · Learn how generative AI and retrieval augmented generation (RAG) patterns are used in Azure AI Search solutions.
What is Retrieval-Augmented Generation (RAG) - GeeksforGeeks
2024年6月11日 · The retrieval-augmented generation (RAG) approach helps solve several challenges in natural language processing (NLP) and AI applications: Access to Custom Data: RAG allows AI models, especially large language models (LLMs), to access and incorporate custom data specific to an organization's domain. This enables the models to provide more ...
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 ...
What Is Retrieval-Augmented Generation, aka RAG? - NVIDIA Blog
2024年11月18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.
Understanding Retrieval-Augmented Generation (RAG) in AI
2 天之前 · Retrieval-Augmented Generation (RAG) is a transformative approach in artificial intelligence (AI) that enhances the performance of large language models (LLMs) by incorporating data from external, reliable sources. Unlike traditional LLMs, which rely solely on pre-existing training data, RAG connects these models to dynamic knowledge bases, enabling real-time, domain-specific responses.
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.
Retrieval augmented generation in Azure AI Foundry portal - Azure AI …
2024年12月12日 · This article talks about the importance and need for Retrieval Augmented Generation (RAG) and index in generative AI. What is RAG? Some basics first. Large language models (LLMs) like ChatGPT are trained on public internet data that was available at the point in time when they were trained.
What is RAG? | Microsoft Azure
Learn about retrieval-augmented generation (RAG), an AI framework that combines retrieval-based and generative models to produce more accurate responses.
What is retrieval-augmented generation (RAG)?
2024年11月12日 · Discover how Retrieval-Augmented Generation (RAG) is transforming AI by combining data retrieval with language generation, delivering smarter and more...
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