What is deep learning and what does it have to do with AI?

What is Deep Learning and What Does It Have to Do with AI?

Imagine you want to teach a child to recognize a cat. You wouldn't write a long list of rules like "if it has pointy ears, and whiskers, and fur, and a long tail, then it's a cat." What if the cat's ears are folded, or it has no tail? Instead, you'd show the child hundreds of pictures of different cats. Eventually, their brain would just... get it. They'd form their own intuitive understanding of what "cat-ness" is.

In the vast universe of Artificial Intelligence, Deep Learning is the magical technique that works just like that. It's a specific, very powerful type of machine learning that is behind most of the AI breakthroughs you hear about today, from ChatGPT to self-driving cars. Instead of being programmed with explicit rules, a deep learning system learns by recognizing patterns in enormous amounts of data.

The "deep" in deep learning refers to the structure of its brain, which is an "artificial neural network" with many layers. Just like a thought in the human brain passes through different neurons that each add a piece to the puzzle, data in a deep learning model passes through many layers. Early layers might learn to spot simple things like edges and colors. Deeper layers combine that information to recognize more complex things, like shapes or textures. The final layers combine *that* information to recognize whole objects, like the face of a person or, indeed, a cat.

Visual Aid: The Layers of Understanding

Deep Learning uses a layered neural network. Each layer learns to identify progressively more complex features, from simple lines to complete objects.

Quick Check

What does the "deep" in Deep Learning refer to?

Recap: What is Deep Learning?