Retrieval-augmented generation

Retrieval-augmented generation (RAG) is a technique that LLMsA large language model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content. More use to retrieve and incorporate new information from external data sources. The LLMsA large language model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content. More firstly refer to a specified set of documents and then respond to queries by the user, with these documents acting as supplementary information to the training data that has been used to train the LLMA large language model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content. More. In the early days of LLMsA large language model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content. More this was an approach that was frequently used to add either domain-specific or updated information that the training data didn’t contain (remember those messages that ChatGPT used to deliver about its knowledge cut-off date?). RAG can be used to allow internal company data to be used, or for using authoritative sources for generating responses.