
The landscape of artificial intelligence is continuously evolving, with large language models (LLMs) at the forefront of this transformation. However, despite their remarkable capabilities, LLMs often suffer from “hallucinations,” generating responses that are factually incorrect or nonsensical. AWS’s innovative approach to Retrieval-Augmented Generation (RAG) offers a promising solution to this challenge. This article delves into AWS’s automated RAG evaluation mechanism,