Technology, defined in plain English

AI bias happens when an AI system produces unfair or systematically skewed results.

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When an AI system gives an answer that sounds convincing but is made up or wrong. It might invent a fact, quotation or website. A confident tone does not mean the information is true.

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An AI model is a trained system that uses patterns in data to make predictions or produce responses.

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An AI prompt is the instruction or question you give an AI tool.

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Artificial intelligence, usually called AI, is technology that allows computers to do certain tasks that normally require human thinking. Imagine having an assistant who can quickly look through thousands of pieces of information and help you find an answer, recognize a pattern or make a suggestion. AI can help recognize speech, recommend movies, translate languages and answer questions. However, it doesn't think or understand everything the way a human does, and its answers can sometimes be wrong.

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An artificial neural network is a computer system that learns patterns from examples.

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A computer-based helper you can talk to by typing or speaking. Some chatbots answer from a fixed menu; others use AI to respond more flexibly. They may be useful, but their answers are not always right.

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Deep learning is a type of machine learning that uses neural networks with many layers.

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Technology that creates new-looking content from your instructions, such as text, pictures, music or computer code. It learns patterns from examples and uses them to produce an output. Always check important details.

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A large language model, or LLM, is a type of artificial intelligence that works with words and language. It powers many AI chat assistants, for example ChatGPT. You can ask it a question, request help writing a letter or ask it to explain something difficult. Imagine someone who has studied an enormous collection of books, articles and other writing and become very good at recognizing patterns in language. An LLM learns from large amounts of information and uses those patterns to produce responses. It can be helpful, but it can also make up information or provide incorrect answers. Important details should always be checked.

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Machine learning is a way of helping computers learn from examples. Imagine teaching a child to recognize different kinds of fruit. You show them pictures of apples, oranges and bananas. After seeing enough examples, they begin to recognize the differences. Machine learning works in a somewhat similar way. A computer examines many examples, looks for patterns and uses those patterns to make predictions about new information. It doesn't learn exactly like a person, and it can make mistakes when the examples are incomplete or misleading.

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Prompt engineering means learning how to give an AI tool clear instructions so it can provide a more useful response. Think about asking someone to cook dinner. If you simply say, “Make something nice,” they have to guess what you want. But if you say, “Please make a simple vegetarian dinner for two people using potatoes and vegetables,” the instructions are much clearer. The same idea applies to AI. Explaining what you need, who the answer is for and how you want it presented can improve the result.

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Examples a computer system studies while learning to recognize patterns. Just as a person learns from practice questions, an AI system learns from large collections of information. The quality of those examples matters.

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