A generative AI approach where outputs are grounded in external knowledge sources, such as documents or databases.
More about Knowledge-Grounded Generation
Knowledge-Grounded Generation combines the strengths of retrieval-based models and generative AI to produce outputs that are contextually accurate and based on external knowledge. This approach typically involves fetching information from sources like vector databases or knowledge retrieval and using it to generate responses.
It is especially useful for applications like retrieval-augmented generation, customer service bots, and question answering systems, ensuring that responses are both relevant and factually correct.
