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AI Glossary

Plain-English definitions for the jargon you hit reading AI tool docs and articles — no circular definitions, no unexplained acronyms. 34 terms and counting.

Core Concepts

LLM (Large Language Model)

The type of AI that powers ChatGPT, Claude, and Gemini — trained on huge amounts of text to predict and generate language.

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Token

A chunk of text (roughly ¾ of a word) that AI models read and generate one piece at a time.

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Context Window

The maximum amount of text an AI model can 'see' and remember at once during a conversation.

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Hallucination

When an AI confidently states something false or made-up as if it were fact.

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RAG (Retrieval-Augmented Generation)

A technique where an AI looks up real documents or sources before answering, instead of relying only on what it memorized during training.

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Fine-Tuning

Further training an existing AI model on a specific, narrower dataset to specialize it for a particular task or style.

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Embeddings

A way of converting text (or images) into numbers that capture their meaning, so a computer can compare how similar two pieces of content are.

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Multimodal AI

AI that can understand and work with more than one type of input — text, images, audio, or video — not just text.

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AI Agent

An AI system that can take multiple steps and use tools on its own to complete a task, rather than just answering one question at a time.

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Knowledge Cutoff

The date after which an AI model has no information, because its training data ends there.

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Parameters

The internal numerical values an AI model learns during training — roughly, a measure of the model's size and capacity.

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Inference

The process of an already-trained AI model actually generating a response to your input.

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Open-Weight Model

An AI model whose trained parameters are publicly downloadable, so anyone can run or modify it themselves.

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Chain-of-Thought Reasoning

When an AI model works through a problem in visible, step-by-step reasoning before giving a final answer.

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Vector Database

A database built to store and search embeddings — the numerical representations of meaning that let AI find similar content.

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Benchmark

A standardized test used to measure and compare how well different AI models perform on specific tasks.

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Small Language Model (SLM)

A compact AI language model with far fewer parameters than flagship models — faster and cheaper, but less broadly capable.

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Using AI Tools

How AI Sees & Creates