How ChatGPT and Large Language Models Actually Work.

𝗘𝘃𝗲𝗿 𝘄𝗼𝗻𝗱𝗲𝗿 𝗵𝗼𝘄 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 “𝗿𝗲𝗮𝗱𝘀 𝘆𝗼𝘂𝗿 𝗺𝗶𝗻𝗱”?

You've don this: You type one sentence, and it writes a whole email, fixes your code, or explains cloud like you're 10.

Here's the tech behind it, broken down so even your little cousin could get it.

Most people think AI is magic lol.

It’s not.

Here’s what’s really happening behind the scenes of LLMs (Large Language Models) like ChatGPT:

👉🏾 Beginner's Guide to LLMs (Large Language Models)

What They Are + How They Actually Work (No BS)

🤖 What Is an LLM?

LLM stands for Large Language Model. It’s a type of artificial intelligence that’s really good at understanding and generating human language — like ChatGPT, Google Gemini, or Claude.

👉🏾 If you've ever used ChatGPT and thought “How does it know this?”, that’s an LLM at work.

🤷🏾♂️ What’s It Built to Do?

LLMs are built to do one main thing: 👉🏾 Predict the next word in a sentence.

It does that so well that it feels like you're talking to a real person. But it's just guessing what should come next, over and over again.

Ok, How Do LLMs Work... Like... Step by Step

1. It Reads the Whole Internet

LLMs learn by reading tons of text, books, websites, forums, code, everything.

Imagine feeding it all the words on Reddit, Wikipedia, and millions of blogs. That’s how it learns how people talk.

2. It Breaks Text Into Tokens

Before learning anything, the model splits all the words into tiny chunks called tokens.

👉🏾 Example: “I love pizza” → becomes → [“I”, “love”, “piz”, “za”]

This helps the model process language in smaller pieces it can work with.

3. It Plays a Giant Guessing Game

During training, the model does this over and over:

👉🏾 “The weather is ___.”

The AI guesses a word. If it’s wrong, it gets corrected. It learns by doing this trillions of times.

That’s how it gets better at predicting the next word.

4. It Uses the Transformer Brain 🧠

The “Transformer” is a special system that helps the model focus on what matters in a sentence.

👉🏾 Example: “Alex gave Taylor his book because he was done reading.” The model figures out “he” = Alex (not Taylor) using patterns.

This is how the LLM understands relationships between words.

5. It Stacks Words to Form Answers

When you type a question, the model:

• Breaks your sentence into tokens.

• Uses everything it learned to guess the best next word.

• Adds that word.

• Then guesses the next.

• Then the next…

Until you get a full answer, story, email, or even code.

6. It Doesn't Actually Think

LLMs seem smart, but they’re not thinking.

👉🏾 They don’t “understand” the way you do. They just recognize patterns and probabilities.

It’s like auto-complete, but trained on the entire internet.

7. It Has a Short Memory (Context Window)

LLMs can only “remember” a limited number of tokens at once (like reading a few pages at a time).

So if your conversation goes too long, it starts forgetting earlier stuff, unless it's designed to remember (like with special memory features).

8. It Runs on Powerful Machines

Training one LLM (like GPT-4) takes:

• Thousands of GPUs - GPU stands for Graphics Processing Unit, it's a special type of computer chip... But it’s not just for video games anymore...

• Millions of dollars

• Weeks or months of time

Once trained, it’s hosted in the cloud (AWS, Azure, Google Cloud), so anyone can access it through a phone, app, or website.

For example, Open AI which runs ChatGPT is hosted on the Azure platform.

Real-Life Example

Let’s say you ask ChatGPT:

“Explain the cloud to me like I’m 10.”

Here’s what happens:

• It breaks your question into tokens.

• It searches its mind (a giant web of learned patterns).

• It picks the best next word: “The…”

• Then the next: “cloud…”

• Then the next: “is…”

It keeps going until it gives you a full answer.

And it feels natural, like it “understands” you. But really, it’s just doing math to guess words.

So there you have it… 🤷🏾‍♂️

Step-by-step, broken-down explanation of:

👉🏾 "I wonder how this Chatddt... I mean Chatgtd... I mean… you know what I’m talking about… works?"

Now you know:

• It read the internet.

• It learned from patterns.

• It guesses the next word (really well).

• It doesn’t think, it predicts.

• And it runs on thousands of GPUs in giant server rooms somewhere in the cloud.

So next time someone says “This AI is magic,” You can hit them with: “Nah, chatddt, I mean, chatabc... it’s just math... Wild, powerful, expensive math.”