How AI Actually Works

🧠 What is a Neural Network?

A neural network is a bunch of "neurons" (nodes) connected in layers. Each connection has a weight — a number that says how much that input matters. Drag the slider and watch how fast the connections multiply!

GPT-4 has roughly 1.8T parameters (weights). That's 1800B connections, and training it cost ~$100M.

🏋️ What is Training?

Training is when the network sees thousands of examples and adjusts its weights to get better. Each pass through the data is called an "epoch." Watch accuracy climb toward ~95% and loss fall toward 0 as the model learns!

🔤 What are Tokens?

AI models don't read words or letters — they read tokens. A token is roughly a word or word-piece. GPT-4 charges per token. Type something and see it split!

GPT-4 has a context window of ~128,000 tokens. That's roughly a 300-page book at once.

⚙️ The Math Behind It: Perceptron

A perceptron is the simplest neural network: multiply each input by its weight, add a bias, then squash through sigmoid to get a 0–1 probability. This is the same operation repeated billions of times inside GPT-4.