AI Terminology

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A branch of computer science focused on creating machines that can perform tasks that typically require human intelligence, such as interpreting language, recognizing patterns, and solving problems.

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AI (Artificial Intelligence)

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An error that occurs in AI systems when the data they are trained on is not representative or contains inherent prejudices, leading to skewed or unfair outcomes.

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Bias

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The circumstances or background information that clarify the meaning of a statement or event, especially important in how AI interprets language.

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Context

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The protection of personal information stored in computer systems, ensuring that it is not misused or accessed without permission.

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Data Privacy

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The process by which AI models are taught to understand and perform tasks by feeding them large amounts of data.

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Data Training

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The set of moral principles that guide the development and use of AI technologies, ensuring they are used responsibly.

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Ethics in AI

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Describes AI systems that can create new content, such as text or images, from what they have learned during training.

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Generative

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A type of advanced AI that generates human-like text by predicting the most likely next word in a sequence.

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GPT (Generative Pre-trained Transformer)

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Extensive AI systems that process and generate language based on large datasets to improve their understanding and output.

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LLM (Large Language Model)

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A subset of AI that enables computers to improve their performance on tasks through learning from data, without being explicitly programmed.

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Machine Learning (ML)