Organizations are increasingly using generative artificial intelligence (genAI) tools to convert unstructured data into usable information. Retrieval augmented generation (RAG) technology enhances the genAI model to provide more accurate and specific responses to queries. Large language models (LLMs) form the basis of genAI technology, but they can be outdated and not specific to a task. RAG optimizes LLMs by accessing an external knowledge base, improving the accuracy and contextuality of its outputs. RAG can retrieve public internet data and data from private knowledge bases. RAG minimizes the chances of hallucinations in genAI results and maximizes the chances of producing accurate results based on factual inputs.
2024-02-26 09:00:05
Original from www.computerworld.com