40 Days Training on RAG – Day 1

Session 1: Hello World of RAG + Introduction & Need of RAG

When I first started learning about RAG (Retrieval-Augmented Generation), I thought it was just another complex AI buzzword. But once I broke it down, I realized it is actually a very practical and powerful idea.

At its core, RAG is simply about helping a language model answer better by allowing it to look up information first before responding.

To understand RAG properly, we first need to understand how LLMs (Large Language Models) work.

What is a Model?

A model is nothing but an equation.

For example:

y=mx+cy = mx + cy=mx+c

This is a simple straight-line equation.

If values of x and y are given, the system tries to adjust the values of m and c so that the line best fits the graph.

This process is called learning.

In AI, the same idea becomes much larger:

y=m1x1+m2x2+m3x3+⋯+billions of terms+cy = m_1x_1 + m_2x_2 + m_3x_3 + \dots + billions\ of\ terms + cy=m1​x1​+m2​x2​+m3​x3​+⋯+billions of terms+c

The…