How is AI different from normal programming?

AI is different from normal programming in that it involves developing algorithms and models that can learn from data and make decisions or predictions based on that data. Normal programming, on the other hand, involves writing code that follows a set of predefined rules and instructions.

In traditional programming, the programmer writes code that specifies exactly how a program should behave under different conditions. The program follows these rules and executes the desired actions accordingly. However, this approach has limitations because it relies on the programmer's ability to anticipate every possible scenario and write code to handle it.

In contrast, AI involves developing algorithms and models that can learn from data and make decisions or predictions based on that data. This allows the system to adapt and improve over time as it is exposed to more data. Rather than being explicitly programmed to follow a set of rules, AI systems are trained to recognize patterns and make decisions based on those patterns.

AI also requires a different approach to testing and evaluation compared to traditional programming. Because AI systems are designed to learn from data, it's important to test and evaluate them on a wide range of real-world data to ensure that they can generalize and perform accurately in new situations.