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AI Glossary: Key Terms Worth Knowing

You’re reading an article about AI and you hit “LLM,” “RAG,” or “fine-tuning.” You open another tab to look it up — and there’s another new term waiting for you.

This glossary is your lifeline. Every term is explained plainly, with no technical background assumed, and where it makes sense, it links to an article where you can see it in action.

Terms are ordered from basic to more advanced — not alphabetically.


Core concepts

Artificial Intelligence (AI)
Generative AI
Large Language Model (LLM)
Prompt
Prompt engineering

How to write prompts in practice — with templates and examples, step by step — is covered in How to write prompts.


How AI works

Training data
Neural network
Model parameters
Context window
Token
Knowledge cutoff

AI behavior and limitations

Hallucination
Benchmark
Inference

More advanced concepts

Fine-tuning

Adapting an existing model on specific data. The result behaves as if it already knows the style and terminology of a particular organization.

RAG

Before answering, the AI searches a document database and builds its response on concrete sources — not just learned patterns.

Multimodal AI

A model that works with multiple input types at once — text, images, audio, video. GPT-4o and Gemini are multimodal.

Agentic AI

AI capable of autonomously carrying out sequences of steps — searching the web, running code, interacting with tools — without asking for confirmation at every step.

Inpainting

An AI image-editing technique where the model “fills in” a missing or removed part of an image based on the surrounding context. Used for example when removing a watermark, erasing objects from a photo, or editing part of an image. Covered in detail in the AI image editing hub.

System prompt

An instruction inserted into a conversation before your first message, which defines the AI’s behavior — its role, tone, constraints, and response format. Users typically never see it; it is set by the tool’s operator. This is why ChatGPT behaves differently from AI Chat in other applications, even when both run on the same underlying model.


Quick acronym reference

AcronymFull nameIn brief
AIArtificial IntelligenceMachines that learn and reason
LLMLarge Language ModelAI trained on massive text datasets
RAGRetrieval-Augmented GenerationAI + document search combined
GPTGenerative Pre-trained TransformerThe architecture behind ChatGPT
APIApplication Programming InterfaceHow to connect AI to your own software
SaaSSoftware as a ServiceCloud-based subscription tool

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Topic overview
AI Basics
All articles on topic AI Basics