The Plain-English AI Glossary
AI vocabulary changes weekly and most explanations assume you already know it. This glossary fixes that: every important term gets its own page, explained the way a sharp friend would explain it, with the practical intuition included.
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🧠 LLM (Large Language Model)
The engine behind ChatGPT, Claude, and Gemini: a neural network trained on vast text to predict and generate language.
🔤 Token
The chunks AI models actually read and write: roughly three-quarters of a word each, and the unit you pay for.
🪟 Context Window
The model's working memory: how much text it can consider at once, measured in tokens.
✍️ Prompt Engineering
The craft of writing instructions AI models respond to well; less magic syntax now, more clear thinking.
👻 Hallucination
When an AI states false information with total confidence: the single most important failure mode to understand.
📚 RAG (Retrieval-Augmented Generation)
The architecture that lets AI answer from your documents: retrieve the relevant bits, then generate with them in view.
🧭 Vector Search & Embeddings
Search by meaning instead of keywords: text turned into coordinates where similar ideas sit near each other.
🔌 MCP (Model Context Protocol)
The open standard that lets AI assistants plug into tools and data: USB-C for AI connections.
🤖 AI Agent
AI that does instead of answers: given a goal, it plans, uses tools, and executes multi-step work with limited supervision.
🎛 Fine-Tuning
Additional training that specializes a model on your examples: powerful for consistent style and format, overkill for most needs.
⚡ Inference
Running a trained model to get answers: the phase you actually pay for, and the industry's great cost battle.
🎨 Multimodal AI
Models that work across text, images, audio, and video in one brain: point a camera at the world and talk about it.
🔓 Open-Weight Models
Models whose parameters you can download and run yourself: Llama, DeepSeek, Qwen, and the ecosystem of AI you own.
🌌 AGI (Artificial General Intelligence)
The contested finish line: AI matching or exceeding humans across essentially all cognitive work, and nobody agrees when.
Why a Glossary?
Every AI conversation is full of words that gatekeep more than they explain. Each entry here is a standalone plain-English deep dive: what the term means, why it matters, and the practical intuition professionals actually use. New terms are added as the field invents them, which it does weekly.
Start with LLM if you are new to all of this, then hallucination, the one concept that keeps people out of trouble.
