These days, there’s growing attention on models like GPT, LLMs, and foundation models.
At the heart of all these models lies a single architecture: the Transformer.
There’s no shortage of explanations for how Transformers work.
But most of them are dense, overly technical, filled with math or abstract symbols — and hard to follow unless you already know the material.
Even people with a background in AI often find them frustrating at first.
We wanted to try a different approach.
At Omnis Labs, we’ve built AI-based platforms like Deep Block and applied AI to real-world, high-resolution image analysis.
Years ago, we also produced educational content and even ran AI training programs.
Some of those courses are still freely available on our YouTube channel.
Our core vision hasn’t changed:
To make AI easier to understand, easier to use, and more accessible to everyone.
That’s why we decided to create this e-book — an effort to explain how Transformers work in the simplest way possible.
No equations.
No complicated symbols and algebra.
Just clean diagrams, intuitive analogies, and a step-by-step walkthrough of how Transformer models process data.
This book is for students who are just starting to learn AI,
for professionals who’ve used models like GPT but don’t fully understand how they work,
and for anyone curious about the technology behind today’s most powerful AI systems.
We hope it helps.
What exactly a Transformer is, and why it works so well
How attention actually works (with visual examples)
What “self-attention,” “multi-head,” and “decoder-only” really mean
How popular models like GPT use Transformers
Why this architecture changed everything in NLP and beyond
No math overload. No dense academic language. Just the concepts — clearly explained.