We’ve reached the final part of our “Branches of AI” series. In Part 1, we explored how AI learns from data (Machine Learning) and follows rules (Logic-Based AI). In Part 2, we saw how AI finds and remembers information through Search and Knowledge Representation.

Now, we’re wrapping it up with three fascinating branches that show how AI plans, adapts, and evolves: Planning, Heuristics, and Genetic Programming.

In last week’s article on Machine Learning and Logic-Based AI, we explored how some branches of AI learn from data while others follow rules. This week, we’re looking at two more branches: Search and Knowledge Representation, the parts of AI that deal with finding information and remembering it in a useful way.

When people talk about Artificial Intelligence, they often lump everything together under one mysterious umbrella. But AI isn’t just one thing — it’s a collection of different approaches. Today, we’ll look at two of the earliest and most important “branches” of AI: Machine Learning and Logic-Based AI.

Artificial Intelligence, or AI, is one of those terms that gets tossed around so often it sometimes feels like everyone is using it, but not all of us are really sure what it actually means. Is it robots taking over? Is it ChatGPT writing your emails? Is it your phone finishing your sentences?

The answer is: yes, kind of. But also, so much more.