Non machine learning Ai examples:

Artificial Intelligence (AI) is like giving a computer the ability to think and make decisions, somewhat similar to how humans think. AI can be made in different ways, and Machine Learning is just one of them.

Now, let’s look at some examples of AI that don’t rely on machine learning:

Rule-Based Systems: Imagine you have a computer program that follows a set of rules to make decisions. For instance, a simple chatbot that responds with pre-defined answers based on keywords you use. It doesn’t learn from data but follows instructions you give it.

Expert Systems: These are like computer programs that have a lot of knowledge about a specific topic. They use this knowledge to make decisions or provide advice. For instance, a medical expert system could help doctors diagnose diseases based on symptoms without learning from new patient data.

Genetic Algorithms: This is a bit like evolution in nature. Computers use these algorithms to solve problems by testing different solutions and keeping the best ones, just like natural selection in evolution.

Search Algorithms: Think of these as smart search engines. They help computers find the best solution among many options. For instance, chess-playing programs use search algorithms to figure out the best moves.

Knowledge Representation: Sometimes, AI systems need to understand and store information in a structured way. For example, a system that keeps track of your schedule and knows when your classes are without learning from new data.

These examples of AI don’t rely on machine learning, where a computer learns from data to make decisions. Instead, they follow predefined rules or use other methods to solve problems or make decisions based on what they already know.

So, AI is like a toolbox with different tools, and machine learning is just one of those tools. Depending on the task, you can choose the right tool, just like you’d use a hammer for some jobs and a screwdriver for others.