Retrieval-Augmented Generation (RAG) integrates external knowledge sources (databases, vector stores, document repositories) with LLMs, enabling them to generate contextually accurate and up-to-date responses without retraining.
B is incorrect: RAG does not speed up training; it improves inference results.
C is incorrect: speech recognition is not an RAG use case.
D is incorrect: computer vision augmentation is unrelated to RAG.
???? Reference:
AWS Documentation – Knowledge Bases for RAG in Amazon Bedrock
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