Plain language: A trained system that has learned patterns from large amounts of data and uses those patterns to make predictions or generate outputs.

Technical: A mathematical structure derived from a training process in which parameters are adjusted to minimise error on a dataset. The model encodes learned statistical relationships and maps inputs to outputs at inference time.

Misconception: An AI model 'knows' things the way a human expert does. In practice, a model identifies and replicates statistical patterns in its training data, it does not understand or reason as humans do.

Real-world example: A medical imaging model trained on thousands of scans recognises patterns associated with specific conditions. When shown a new scan, it draws on those learned patterns to flag areas of concern for a clinician to review.

Related terms: AI · Generative AI · Algorithm · Hallucination