AI is the broad goal of making machines act intelligently; machine learning is a subset that learns patterns from data; deep learning is a subset of machine learning using multi-layered neural networks.
These three terms are often used interchangeably in casual conversation, but they describe nested categories, like a set of Russian dolls.
The broadest term — any technique that lets machines mimic intelligent behavior, whether through simple hand-coded rules or complex learning systems.
A subset of AI where systems learn patterns from data rather than being explicitly programmed with rules — for example, a spam filter that learns from examples of spam and non-spam emails.
A subset of machine learning that uses neural networks with many layers ("deep" networks) to learn increasingly abstract features from raw data. It's behind most recent breakthroughs in image recognition, speech recognition, and large language models like the one answering this question.
Last reviewed: September 2026