Neural network
A pile of tiny math units that learns patterns from examples.
A neural network is a program made of layers of simple units called neurons. Each neuron takes some numbers, multiplies them by its own weights, adds them up, and passes the result to the next layer. Alone, a neuron is trivial. Millions of them, stacked, can recognize a face or write a paragraph.
Nobody programs the weights by hand. During training, the network sees examples (a photo and the word 'cat'), makes a guess, measures how wrong it was, and nudges every weight a tiny bit in the direction that would have made the guess better. Repeat billions of times.
Large language models like Claude are neural networks of a specific shape (transformers) trained on text. Their 'knowledge' is nothing more than a very large set of adjusted weights.
Keep in mind
- Neurons are simple; the power comes from stacking millions of them.
- Training means adjusting weights to reduce errors on examples.
- A trained model is just a file full of numbers (the weights).
