Retrieval-augmented generation (RAG) combines neural text generation with information retrieval to enhance language models in advertising and digital marketing, enabling tailored and dynamic content creation.
RAG generates personalized content by accessing up-to-date product details, user reviews, and market trends in real time, ensuring relevance and resonance with specific audience segments.
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