RAG
| Definition | : | Retrieval-Augmented Generation |
| Category | : | Computing » Artificial Intelligence |
| Country/Region | : | Worldwide  |
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What does RAG mean?
Retrieval-Augmented Generation (RAG) is an AI framework that improves Large Language Model (LLM) accuracy by retrieving data from from a knowledge source or database before generating a response. This helps the model provide answers that are more accurate, up-to-date, and grounded in real data, rather than relying solely on its training.
RAG combines the strengths of retrieval-based and generation-based models. This approach aims to improve the accuracy, relevance, and coherence of generated content by grounding it in retrieved information. It is widely used in chatbots, search assistants, documentation bots, and enterprise knowledge systems.
In simple terms:
Retrieve: Search for relevant information from a knowledge base.
Augment: Add that information to the prompt.
Generate: Produce a response using both the prompt and the retrieved information.
4 more results for RAG
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RAG | Recombination Activating Gene | |
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RAG | Red, Amber, Green | |
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RAG |
Real Academia Galega [Royal Galician Academy] |
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RAG | Richmond Art Gallery |
Frequently Asked Questions
What is the full form of RAG in AI?
The full form of RAG is Retrieval-Augmented Generation
What is the full form of RAG in Computing?
Retrieval-Augmented Generation
What are the full forms of RAG in Worldwide?
Retrieval-Augmented Generation | Recombination Activating Gene | Red, Amber, Green