Why Rules Aren't Enough for AI
For decades, one common approach to AI was to write explicit rules: if this condition, then that action. Rules can work in narrow worlds. They struggle when reality has too many exceptions.
The limit of hard-coded intelligence
As you add rules for every edge case, the system grows brittle. Sticky notes pile up. Special cases conflict. The approach that felt clear at the start becomes impossible to maintain.
Why learning became necessary
When the world is too messy to specify by hand, systems need another way to improve: learning from examples instead of enumerating every rule in advance.