Classical programming or symbolic AI is kind of like the old-school way of making computers smart it’s where you tell the computer exactly what to do by giving it clear rules and symbols it’s not like machine learning where the computer figures things out by itself here you’re giving it step-by-step instructions. Everything in symbolic AI is based on logic and reasoning it’s about making the computer think using symbols and rules you define beforehand.

For example let’s say you want to make a program that plays chess you would write out all the rules of chess like how each piece moves and how the game is won and lost. The computer would follow these rules exactly and make decisions based on them it doesn’t learn from experience it just does what the rules say.

Symbolic AI is really good at tasks where there’s clear logic involved like solving math problems or playing chess because everything can be broken down into rules and symbols. But it’s not so great when it comes to more complex or fuzzy stuff like recognizing faces or understanding natural language because those things don’t have simple rules they’re more about patterns and learning from data.

In the early days of AI symbolic AI was super popular because it made sense to control the machine with clear instructions but as AI grew more advanced people started moving to machine learning and deep learning because they can handle more complex and messy problems better than symbolic AI can. So symbolic AI is still used in some places but it’s not as big as it used to be

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