NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam

What is Retrieval-Augmented Generation (RAG) and what problem does it solve?

RAG combines a retrieval system (vector database) with an LLM so the model can answer questions using up-to-date or private knowledge not in its training data RAG is a technique for reducing hallucinations by averaging outputs from multiple LLMs RAG is a fine-tuning method that adds a retrieval head to the transformer so it learns to cite sources RAG generates embeddings for documents and stores them in the model's context window for fast lookup

Correct Answer:

RAG combines a retrieval system (vector database) with an LLM so the model can answer questions using up-to-date or private knowledge not in its training data

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