Artificial intelligence models are computer programs that aim to replicate aspects of human intelligence. Developers input rules (known as algorithms) that allow the program to make decisions, notice patterns, and make predictions.

Successful models have a user-friendly interface. That means new users can interact with it without much direction.

For example, Bing Chat is an AI-powered chatbot app that can have back-and-forth conversations with users:

People type messages into the text box and the software replies—thanks to the accessible interface.

However, it’s the AI model that does the heavy lifting. It runs in the background and provides relevant answers to questions it has never encountered before.

Users don’t interact with the AI model directly. But it powers the whole experience.

Artificial intelligence is a complex topic with a lot of overlapping terminology. So, let’s clear a few things up.

Artificial Intelligence vs. Machine Learning vs. Deep Learning

Think of artificial intelligence, machine learning, and deep learning as one big tree. 

The trunk is AI. And one of its biggest branches is machine learning (ML). But that big branch splits into several smaller branches. One of them is deep learning (DL).

What’s the bottom line?

All are connected. But each term doesn’t refer to the same process.

Here’s what it looks like: