Have you ever asked yourself: How does ChatGPT work?

Most people use ChatGPT! But have you ever asked yourself — how does it actually "WORK"?

Here’s a simple overview of what happens under the hood of an LLM — no PhD needed. Let's break it down in a SIMPLE way: ⬇️

So, what even is a deep learning model? At its core, it’s just math. A deep learning model takes input — like text or images — and transforms it through layers of neurons to produce an output. Each layer adds a bit of abstraction, shaping raw data into insight. It’s like a factory — raw data goes in, intelligence comes out.

What does input & output really mean? It’s all numbers under the hood. → Input: Words, images, audio — converted into vectors. → Output: A label, a score, a sentence — also numbers. The model learns to map one to the other, just like you learn to associate sounds with meaning.

But how does that mapping happen? Each node takes the output of the previous layer, multiplies it by a weight, adds a bias, and passes it on. Repeat across layers and you get a complex chain of math operations — transforming input step by step into something that makes sense. It's structure + logic + a lot of computation.

Wait, how does the model “understand” a word? That’s where embedding models come in. They turn words into vectors — multi-dimensional representations of meaning. So "king" and "queen" end up near each other in vector space. That’s how AI grasps context, not just spelling.

Okay, but how does an AI model learn? Through training. It starts with random guesses. Then it compares its output to the correct answer, sees how far off it was, and adjusts the internal weights. This feedback loop is called backpropagation. And when you repeat this millions of times — the model starts to get really good.

And what about Generative AI? That’s the magic behind tools like ChatGPT. They don’t classify — they generate. One word (or token) at a time, predicting what should come next based on everything that came before. It’s like auto-complete — but with far more intelligence, nuance, and training behind it.

This graphic is a gem 💎 for those new to AI — or even pros who need to explain it simply.

Author

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