How Do LLMs Work?

A visual, beginner-friendly guide to understanding Large Language Models like ChatGPT and Claude

What Are Large Language Models?

Large Language Models (LLMs) are AI systems trained on massive amounts of text to understand and generate human-like language. They power tools like ChatGPT, Claude, and many other AI assistants you use every day.

Let's break down how these amazing systems work, step by step, with visual examples that make complex concepts easy to understand.

Step 1

Tokenization: How AI Reads Text

Breaking Text into Tokens

Original Text:

Hello, how are you?

Tokens:

Hello

how

are

you

Step 2

Neural Networks: The Brain of AI

Neural Network Structure

Step 3

Attention: How AI Focuses on Important Words

Attention Mechanism

Current Focus:

The

cat

sat

the

mat

Attention Weights:

The

100%

cat

70%

sat

40%

10%

the

10%

mat

10%

Step 4

Transformers: The Modern AI Architecture

Transformer Architecture

Encoder (Understanding)

Input Embedding

Positional Encoding

Self-Attention

Decoder (Generation)

Masked Attention

Cross-Attention

Output

Step 5

Training: How AI Learns

Training Process

Training Data

Billions of words

AI Model

Learning patterns

Epoch 1 of 5

Training Progress:

Accuracy

60.0%

Improving

Loss

2.50

Decreasing

Putting It All Together

Large Language Models combine all these components - tokenization, neural networks, attention mechanisms, and transformers - into a powerful system that can understand and generate human-like text.

Now that you understand how LLMs work, you can write better prompts to get the most out of AI tools like ChatGPT and Claude!

Try Improving Your Prompts