HKOTEN / TECHNOLOGY STORYTELLER
What is RAG? How AI finds evidence before it answers
Video in Vietnamese Published
About this video
Explains Retrieval-Augmented Generation in three stages: retrieve documents, add them as context, then generate an answer. It also covers why this can reduce hallucinations without guaranteeing that every answer is correct.
What is RAG, and why can AI use new information without retraining the whole model?
Learn how Retrieval-Augmented Generation helps AI retrieve documents, add context and produce answers based on the information it finds.
RAG (Retrieval-Augmented Generation) is a technique that augments content generation with information retrieval, introduced by Patrick Lewis and colleagues in a 2020 study at NeurIPS.
In this video, you will learn:
- How RAG works through three stages: Retrieval, Augmentation and Generation.
- How embeddings and document retrieval support an AI model.
- The difference between parametric and non-parametric memory.
- Why RAG can reduce hallucinations but does not guarantee that every answer is correct.
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