While LLMs (Large Language Models) address generic knowledge very well, it is the combination of LLMs with internal documents that delivers results that can be trusted. This so-called RAG (Retrieval Augmented Generation) approach consists of a preparation phase whereby documents are uploaded, converted, segmented, vectorized and indexed. Once a question is asked a retriever leveraging … Continue reading (Whitepaper) Get more value out of LLMs and your own documents with RAG
Tag: Retrieval-Augmented Generation
Natural language questions and answers on local and confidential information Introduction Large Language Models (LLMs such as GPT) have sparked significant progress in the way, users can interact with text: they deliver impressive results on tasks such as text generation, text summarization and many other scenarios. The predominant mode of interaction with LLMs is using … Continue reading Use the power of LLMs on your own documents using Kairntech