The blog attempts to answer what is RAG and why we need it? It's key components and how to put these together. We’ll touch upon key concept of evaluation of a RAG system and variations of RAG.
RAG has significant advantage over traditional generative models that rely solely on pre-trained data. RAG systems incorporate a retrieval mechanism that dynamically fetches relevant information to improve the accuracy and reliability of responses. E...
Introduction LLM/Inference LLMs are the "brain" of RAG systems, responsible for interpreting input queries, retrieving relevant knowledge, and generating coherent, context-aware responses. Key roles of LLM in a RA system involve Natural Language Unde...
To understand RAG, we must take a few steps back and start with understanding what is AI. There are many definitions for what constitutes an AI. The one broadly accepted is that any system which matches or exceeds average human capability in a comple...