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Vector Databases Are the Base of RAG Retrieval
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Why Will RAG Stay Despite LLMs’ Advancements?
Implementing a chatbot powered by Retrieval Augmented Generation (RAG) technology is a game-changer for businesses looking to enhance their customer support. This approach combines the conversational abilities of large language models with knowledge stored in vector databases from diverse fields, such as legal advising, educational assistance, healthcare, and more.
A standard RAG framework consists of two core systems: the Retriever and the Generator. The Retriever segments data (like documents), encodes data …
ai businesses chatbot conversational customer customer support databases diverse educational fields game knowledge language language models large language large language models legal llms machinelearning rag retrieval retrieval augmented generation support technology vector vectordatabase vector databases will