A technique that enhances AI model outputs by integrating retrieved knowledge into the generation process.
More about Knowledge Retrieval Augmentation
Knowledge Retrieval Augmentation combines retrieval systems and generative AI to produce responses enriched with retrieved information. This process involves fetching relevant knowledge from sources like external knowledge bases or vector databases and incorporating it into AI outputs.
This technique is central to frameworks like retrieval-augmented generation (RAG) and applications such as context-aware generation, where accuracy and relevance are paramount.
