AI GlossaryRAG (Retrieval-Augmented Generation)ENTRY — Generative AI
[Generative AI]
RAG (Retrieval-Augmented Generation).
Combining retrieval systems with language models to generate responses grounded in external knowledge.
In-depth explanation
01RAG addresses LLM limitations like outdated knowledge and hallucinations by retrieving relevant documents before generation. The retrieved context is included in the prompt, grounding the response in actual sources. This enables knowledge-intensive applications, reduces hallucinations, and allows updating knowledge without retraining the model.
Examples
02EX. 01
ChatGPT with browsing
EX. 02
Enterprise knowledge assistants
More in Generative AI
0301Diffusion ModelGenerative models that learn to create data by reversing a gradual noising process.02Generative Adversarial Network (GAN)Two neural networks competing against each other to generate realistic synthetic data.03GPTGenerative Pre-trained Transformer, a family of large language models trained to generate text.04HallucinationWhen AI models generate plausible-sounding but factually incorrect or fabricated information.05Large Language Model (LLM)AI models trained on vast text data that can generate and understand human-like text.06Prompt EngineeringThe practice of crafting effective inputs to get desired outputs from AI models.
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