AI, Machine Learning, and Deep Learning are not the same thing.

Understanding the difference is the key to understanding how modern AI truly works. Let's break down this crucial relationship, one layer at a time.

Artificial Intelligence (AI)

Think of AI as the entire universe of making computers smart. It's the broad, overarching dream, first conceived in the 1950s, of creating machines that can think and reason like humans. It includes everything from simple rules-based logic to the most advanced neural networks.

It's the goal.

Machine Learning (ML)

Machine Learning is a **subset** of AI. It's not a different thing; it's a specific *approach* to achieving AI. Instead of writing explicit rules, ML is the practice of "training" a program by showing it vast amounts of data, allowing it to learn the patterns for itself.

It's the method. Your email's spam filter is a classic example of ML.

Deep Learning (DL)

Deep Learning is a highly specialized **subset** of Machine Learning. It uses complex, multi-layered neural networks (hence the term "deep") to solve the most complex pattern-recognition problems. It's the powerhouse behind today's most advanced AI.

It's the advanced technique. A self-driving car identifying a pedestrian uses Deep Learning.

Let's Use an Analogy

Still confusing? Think of it in terms of vehicles.