Artificial Intelligence

Artificial Intelligence (AI) is a branch of computer science that deals with creating machines or systems that can simulate (copy) intelligent behaviours similar to those of humans.

Think of it this way: AI tries to make computers act "smart" like people do – they can learn new things, make decisions, and take action on their own.

An AI system can:

• Learn – acquire and process new information
• Decide – analyse situations and make choices based on that analysis
• Act autonomously – take actions without needing a human to control it at every step

For example, a virtual assistant on your phone uses AI to understand your voice commands (learn), figure out what you want (decide), and perform tasks like setting an alarm (act autonomously).

All AI systems share three main characteristics. These are like the building blocks that make AI work:

AI systems need large amounts of data to function properly. Data is just information – it could be numbers, text, images, or anything else a computer can process.

• The AI gathers and stores this data
• The more data an AI has, the better it can perform its tasks
• For example, a music recommendation AI needs data about millions of songs and what people listen to

AI systems have rules or algorithms (step-by-step instructions) that tell them how to use the data they've collected.

• These rules help the AI process information and make decisions
• Think of rules like a recipe – they tell the AI what steps to follow
• For example, "If a customer bought product A, suggest product B"

AI systems can use logical reasoning – this means they can think through information and come to conclusions.

• They evaluate (examine) information carefully
• They make decisions based on that information
• They can solve problems by working through steps logically
• For example, a chess AI reasons through possible moves and picks the best one

Many AI systems can also learn and adapt. This means they can:

• Change their own rules based on experience
• Modify the data they use
• Improve their performance over time
• Learn from mistakes so they don't repeat them
• Use results from previous decisions to make better future decisions

For example, a spam email filter learns which emails you mark as spam and gets better at recognizing similar emails in the future.