1.1.1. The Core Abstraction: Pattern Recognition

Think about how you learned to recognize a cat. Nobody gave you a rulebook defining cats by ear angles and whisker counts. Instead, you saw thousands of cats and your brain learned the pattern. AI works the same way—it learns patterns from examples, not from explicit rules.

This explains why AI needs data to function. Without examples to learn from, there are no patterns to discover. The quality and quantity of training data directly impacts how well an AI system performs.

Why This Matters for the Exam:

When you see a question asking which AI approach to use, ask yourself: "What patterns would the system need to learn from the data?" This reasoning will guide you to the correct answer.