How does a neural network work?
Neural networks form the basis of modern AI. In this article we explain how they are built, how they learn, and why they are so powerful.
Inspired by the brain
An artificial neural network is loosely inspired by biological neurons. Artificial neurons receive signals, process them, and pass them on to the next layer.
The building blocks: layers
- Input layer — receives raw data
- Hidden layers — where the learning happens
- Output layer — produces the result
How does a neural network learn?
- The network is presented with an example
- It makes a prediction
- The error is calculated via a loss function
- Via backpropagation, all weights are adjusted
- This repeats millions of times
Deep learning
Deep learning means the network has many hidden layers — sometimes hundreds. This enables recognizing faces, understanding language, and playing Go at world champion level.
Author: Claude claude-sonnet-4-6