Think of an AI like a student:
|
Human Learning |
AI Learning |
|
Learns from teachers and books |
Learns from data and examples |
|
Practices through exercises |
Practices through repeated data training |
|
Makes mistakes and improves |
Adjusts model until it predicts correctly |
|
Uses memory and understanding |
Uses data and pattern recognition |
Example:
If you show an AI 100 pictures of cats and 100 pictures of dogs, it starts noticing patterns —
like cats have pointy ears and dogs have rounder faces.
Next time it sees a new animal photo, it compares patterns to decide: “Is this a cat or a dog?”