Category: Amazon Bedrock Knowledge Bases

State-of-the-art AI agents rely on external tools to perform actions on their behalf. A tool is a function with a clear description, defined inputs, and outputs that extend the capabilities of a large language model (LLM). As toolkits expand, selecting the right tool for each task requires effective mechanisms, among which semantic search enables agents […]

Retrieval-Augmented Generation (RAG) is a technique that optimizes large language model (LLM) outputs by referencing authoritative knowledge bases outside of the model’s training data before generating responses. This addresses common limitations of traditional LLMs, such as outdated knowledge, hallucinated facts, and misinterpreted terminology. Organizations can implement RAG to enhance their generative AI applications with current, […]