AI vs. Machine Learning vs. Deep Learning: What Is the Difference?

News stories use artificial intelligence, machine learning and deep learning almost interchangeably. They are related, but each one is a narrower idea than the one before.

Artificial intelligence

AI is the broadest term. It covers any technique that lets a computer perform tasks we associate with human intelligence, such as recognizing speech, making decisions or translating languages. A simple rule-based program for playing chess counts as AI.

Machine learning

Machine learning is a subset of AI. Instead of following rules written by a programmer, the system learns patterns from data. Show it thousands of emails labeled spam or not spam, and it learns to sort new messages on its own.

Deep learning

Deep learning is a subset of machine learning that uses neural networks with many layers. These networks are especially good at messy data such as images, audio and text. Modern chatbots and image generators are built with deep learning.

A simple way to remember it

• AI is the goal: smart behavior from machines.
• Machine learning is one way to reach it: learning from data.
• Deep learning is one powerful kind of machine learning: layered neural networks.

Why the difference matters

Many products labeled AI are actually simple statistics or fixed rules, and that is fine for many jobs. Knowing the terms helps you judge claims. If a company says its product uses deep learning, ask what data it was trained on and how well it has been tested.

Takeaway

Think of three nested circles. Deep learning sits inside machine learning, which sits inside AI. Keeping that picture in mind makes the headlines much easier to read.