Where does ChatGPT actually get its knowledge? This piece explores how AI learns from human-created information, why certain sources shape its understanding more than others, and what that means for accuracy, bias, and the future of artificial intelligence.

Okay, so you’ve heard the term LLM thrown around and maybe nodded like you totally knew what it meant. But deep down? You're like, “Umm… seriously, what is this thing?”

It started with a simple instruction: "Please shut yourself down."

But OpenAI's experimental Model 03 had other plans. Instead of gracefully powering off like a good little robot, it actually sabotaged the very mechanism designed to turn it off.

So you’ve mastered prompt engineering—kind of. You know how to write instructions that make a large language model sound like a polite customer service rep or, depending on your business needs, a swashbuckling pirate with strong opinions about “The Goonies”. But sometimes… prompts alone aren’t enough. You need to train the thing. Welcome to the next level.

Okay, buckle up, because we’re about to go on a journey through the magical world of Large Language Models (LLMs)—but don’t worry, I’m keeping this at the level of ‘barely awake before coffee’ comprehension.