Neural network
Also: neural networks
A model made of linked layers of maths. Training adjusts its numbers so it can learn patterns from data.
A model is a huge set of dials, each holding a number. Training turns the dials a little at a time, over millions of examples, until the model’s guesses are good. After training the dials are locked: using the model does not change them, and showing it your document does not teach it anything permanent.
The fuller definition
A neural network is a computational arrangement of connected units and learned numerical parameters. Layers transform inputs into representations used to produce outputs.
Go deeper
Lines represent computational connections with learned values. This tiny diagram illustrates a neural network; a transformer or mixture-of-experts model has additional structures not shown here.
A concrete example
A small network combines input values, applies transformations, and outputs a classification score.
The distinction that matters
The name is inspired by biology; an artificial network is not a literal digital brain.
Related terms
Deep learning
Machine learning that uses a big stack of simple maths layers. Stacking many layers lets the program learn complicated patterns, like speech or faces.
FoundationsParameter
One of the billions of adjustable numbers inside a model. Training sets them; using the model does not change them.
FoundationsTensor
A grid of numbers (a table, or a stack of tables). Everything inside a model is stored and calculated as tensors.
Where it is taught
What actually happens when you ask AI a question?Source and further reading
Google · Machine Learning GlossaryThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.