Day 21 How ChatGPT Really Works: Large Language Models Explained | AI in 5

ChatGPT, Claude, Gemini — they can feel like magic. But at their core, a Large Language Model does ONE simple thing, over and over: it predicts the next token. In Day 21 we finally demystify LLMs, walk through the exact three‑step loop they run, and watch a tiny version of it work for real — using the SAME tokenizer the real GPT models use. You'll learn: what an LLM actually does (predict the next token) • what makes it "large" (huge data + billions of parameters) • the 3 steps: tokenize → predict a probability for every next token → sample → repeat • why it feels intelligent • and why it predicts plausible text rather than truly "knowing." The demo is real and runnable. 0:00 LLMs · 0:41 The one thing an LLM does · 1:20 What makes it 'large' · 2:01 Text → tokens · 2:42 Predict the next token · 3:19 Context in, token out · 3:56 Sample & repeat · 4:36 Watch it for real · 5:10 The code · 5:46 Run it · 6:28 Tokenize·predict·sample·repeat · 7:05 Know its limits · 7:45 Recap Subscribe for a new AI lesson every day. Tomorrow: how LLMs are actually trained. #AI #LLM #ChatGPT