As a beginner in understanding LLMs, when I heard the term RAG-Retrieval Augmented Generation, I assumed it was a technique used within LLMs. However, from this session, I learned that RAG is all about use of our own custom or private data along with an LLM to generate more relevant responses. Before understanding RAG, we need to have clarity on what exactly these LLMs are? What does a Model mean? A model means an equation. Let's say now we have this equation y = mx + c This is a straight line equation. If the values of x and y are provided, then the system just tweak the values of m and c to come up with best fits. Here lets say x = 1 & y = 2, now I can have m=1 & c=1 or m=0 & c=2, etc., Here it learns different patterns. This process is called as learning. Parameters and Weights Similarly in an AI model, the equation would be much more larger with the billions of parameters. The more complex the equation, the more patterns the model can learn and so the relevance and accuracy improves.…