Cache Augmented Generation (CAG) is a new framework that enhances the traditional Retrieval-Augmented Generation (RAG) by incorporating a caching mechanism. This innovation eliminates the need for a vector database, making the process significantly faster. According to recent tests, CAG operates at speeds up to 50% faster than traditional RAG systems. The framework’s efficiency stems from its ability to cache frequently accessed data, reducing retrieval times and computational overhead. This approach not only speeds up the generation process but also simplifies the overall architecture of RAG systems.
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