Have you ever wondered what all the terminology around AI means? Here is a brief breakdown:
AI is the overarching field.
Machine Learning is a subset of AI. Its development spans back to the 1950s where basic pattern recognition was used to read typed characters and used to sort post.
Deep Learning is a type of machine learning that uses neural networks to identify patterns in huge amounts of data. It can learn the complexities of human language and context of words using word embedding and transformer models.
Neural Networks mimic the way the human brain operates by making complex connections, classification and pattern recognition of data. These systems can't tell us how they make connections to get to their output.
Natural Language Processing (NLP), a branch of AI that helps computers interpret and respond to human language often using deep learning techniques.
Large Language Models (LLMs) are part of NLP and trained on huge amounts of textual data.
If you still feel unsure about the terminology surrounding AI, explore the Study Skills resource: Understanding AI: What it can and can't do.
Generative AI (GenAI) includes LLMs and other models that can create new content such as text, images, audio, video and other media in response to users' prompts.
The diagram below is a visual representation of these branches and relationships of Artificial Intelligence. Click here for an accessible PDF of this image.
Alan Turing Institute (2025) Data science and AI glossary. Available at: https://www.turing.ac.uk/news/data-science-and-ai-glossary (Accessed: 12 June 2025).
Stanford Medicine Magazine (2023) ABCs of AI: A brief glossary of artificial intelligence terminology Available at: http://stanmed.stanford.edu/brief-glossary-artificial-intelligence-ai/ (Accessed: 12 June 2025).