RAG challenges
Software Engineer (L2) | AI Developer | Building products leveraging human-centric AI Software Engineer (L2) | AI Developer | Building products leveraging human-centric AI
Subham Kundu 2y Edited Report this post Practical challenges I encountered while developing Retrieval Augmented Generation systems (RAGs) for various clients, particularly in the context of the hot topics within the generative AI ecosystem, where blogs and companies continually explore RAG integration. In simple terms, RAG is used to query and retrieve answers from a company's internal data. To simplify, documents are first transformed into embeddings and stored in a vector database. When a user poses a question, the top documents and the query are sent to the Language Model (LLM), and the use
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