RAG vs CAG : Revolutionizing AI Efficiency and Speed If you’ve been keeping up with the latest buzz in generative AI, you’ve likely heard about how models like ChatGPT and GPT-4 are transforming fields such as content creation and customer support. However, while these models are incredibly powerful, they sometimes face challenges with factual accuracy or domain-specific knowledge. That’s where Retrieval-Augmented Generation (RAG) and Cache-Augmented Generation (CAG) come into play. Let’s explore these two innovative approaches and see how CAG might be redefining AI efficiency. What is Retrieval-Augmented Generation (RAG)? RAG enhances the capabilities of AI by allowing it to fetch real-time information from external sources, such as Wikipedia, research papers, or internal company documents. Think of it as giving your AI a dynamic memory boost. Instead of relying solely on pre-trained knowledge, RAG retrieves the most relevant documents in real time to ensure accurate and up-to...