Large Language Models, Explained Like You're a Curious Human

Everything you need to know about how ChatGPT-style AI actually works. What Actually Is a Large Language Model? Strip away the hype and an LLM is surprisingly simple in structure. It boils down to two files sitting on a hard drive: A very large file of numbers — these are the "parameters" (or weights) of the neural network. Think of them as billions of tiny dials that have been carefully tuned. A small file of code — this is the algorithm that reads those numbers and actually produces text. It can be as short as ~500 lines of C code. That's it. Meta's Llama 2 70B model, for example, is a 140 GB parameter file plus a tiny run script. Together, they can run on a regular MacBook — no internet needed. ┌─────────────────────────────┐ ┌─────────────────────────┐ │ 📦 Parameters File │ │ ⚙️ Run Code │ │ │ + │ │ │ 140 GB of numbers │ │ ~500 lines of C │ │ Billions of tiny "dials" │ │ The "engine" that │ │ encoding world knowledge │ │ reads the dials │ └─────────────────────────────┘ └──────────