Neural network: definition

A neural network is a computing system loosely inspired by the brain, made of layers of connected nodes that adjust their strengths as they learn from data.

A neural network passes data through layers of simple units, each one weighing its inputs and passing a signal on. Training nudges those weights until the network produces the right outputs, which is how it "learns."

It is the fundamental building block of deep learning and the large models behind modern AI. You do not need the maths to use one, but knowing the term demystifies a lot of the jargon.

Related terms

Deep learning: Deep learning is machine learning that uses many-layered neural networks to learn complex patterns, and it is the approach behind most modern AI breakthroughs.
Machine learning: Machine learning is a branch of AI where a system learns patterns from data and improves at a task through examples, instead of being programmed with explicit rules.
Model training: Model training is the process of teaching an AI model by showing it data and adjusting its internal parameters until it performs the task well, which is done once up front and is computationally expensive.