AI glossary cheat sheet

The terms worth knowing

Artificial intelligence (AI)

Software designed to perform tasks that normally require human judgement, pattern recognition or decision-making.

Machine learning (ML)

A branch of AI in which systems learn patterns from data rather than relying only on hand-written rules.

Large language model (LLM)

A model trained on large amounts of text to predict and generate language, including tools used for chat, summarisation and drafting.

Generative AI

AI that creates new text, images, audio, video or code from patterns learned during training.

Natural language processing (NLP)

Methods that help computers analyse, understand and generate human language.

Computer vision

AI techniques used to interpret images and video, from quality inspection to medical imaging.

Predictive analytics

Using historical data and statistical or machine-learning models to estimate what is likely to happen next.

AI agent

A system that can plan and take a sequence of actions towards a goal, often using tools or external services.

Human in the loop

A workflow in which a person reviews, approves or corrects important AI decisions rather than leaving the system fully autonomous.

Model drift

A decline in model performance when real-world data or behaviour changes after deployment.

Explainability

The ability to give people a useful account of why an AI system produced a result or recommendation.

Algorithmic bias

Systematic unfairness in an automated system caused by data, design choices, objectives or the way the system is used.

Useful rule of thumb: ask what data the system uses, what decision it influences, who checks it, and what happens when it is wrong.