An absolute beginner’s guide to machine learning, deep learning, and AI

Meet Samantha. She’s your friendly assistant from 2025. She sorts your mail, sets up your meetings, and orders groceries. She paints and writes poetry. She’s your best friend. She’s also an artificial intelligence from the movie Her, which imagines how a juiced-up Siri will change our lives.

Now, tech companies large and small are racing to make this a reality. You’ve read the news. You’ve heard the jargon: AI, machine learning, deep learning, neural networks, natural language processing.

Maybe it’s all a little confusing. So here’s a primer on these concepts and how they’re interrelated.

What is artificial intelligence, or AI?

AI, simply put, is an attempt to make computers as smart, or even smarter than human beings. It’s about giving computers human-like behaviors, thought processes, and reasoning abilities.

There are two kinds of artificial intelligence:

Narrow, or weak AI

That’s AI focused on one narrow task. Weak AI is already all around us. It has beaten us at chess, Jeopardy, and most recently, Go.

Digital assistants like Siri and Cortana are giving us the weather, and self-driving cars are on the road. But they have limits. A self-driving car can’t play chess. Siri can’t read and delete your unimportant emails. Weak AI has a narrow scope: It can’t go beyond its original programming.

Cortana is an example of weak AI.

Strong, or general AI

Here we enter the realm of science fiction. Samantha is the very definition of strong AI. She can learn new things and modify her own code base. She can beat you in chess and drive a car.

The anatomy of AI

So we know general AI is the end goal. How do we get there? Here are five areas it needs to master:

Tools to get there

When machines learn

From Siri to Samantha