AI Glossary

A language model is a system trained on text to learn the statistical patterns of a language, enabling it to predict which words are likely to follow in a given context.

Natural language processing is the field concerned with enabling computers to read, analyse and respond to human language, covering tasks such as translation, summarisation, sentiment analysis and question answering.

The transformer is a neural network architecture that processes a whole sequence at once instead of step by step, using an attention mechanism to determine which parts of the input relate to which. It underpins most current large language models.

An artificial neural network is a computing structure made of simple connected units organised in layers, where learning happens by gradually adjusting the numerical weights on those connections until the output errors decrease.

Deep learning is a branch of machine learning that passes data through many successive layers of a neural network, allowing the system to discover for itself which features matter rather than having them specified by a human.

Generative AI is a category of artificial intelligence that produces new content such as text, images, audio, video or code, rather than only classifying or analysing existing data.

Machine learning is a branch of artificial intelligence in which a system learns patterns and relationships from examples in data, instead of following rules written explicitly by a programmer.

Artificial intelligence is a field aimed at building systems able to perform tasks normally associated with human intelligence, such as learning, reasoning, understanding language, recognising patterns, predicting and making decisions.

An artificial intelligence model trained on large amounts of language data to learn patterns in text, generate responses and perform tasks such as question answering, summarisation and translation.