GenAI Vocabulary 101

5 min read

Fifteen terms, five minutes, zero jargon-panic. Learn the vocabulary that makes every AI tutorial, changelog, and Discord thread suddenly make sense.

Every craft has its handshake vocabulary. Chefs say *mise en place*, surfers say *point break*, and AI people say *inference* while nodding meaningfully. The good news: the core GenAI dictionary is small. Master the fifteen or so terms below and you can read any model announcement, follow any tutorial, and hold your own in any AI conversation. Let us get you fluent.

The big four

TermWhat it means
PromptThe text instruction you give a model. The single highest-leverage skill in all of GenAI.
ModelThe trained network that generates — Imagen 3, Sora 2, Suno are all models.
TokenThe chunk of text a language model reads — about three-quarters of a word.
InferenceRunning a trained model to generate output. Training happens once, in a lab; inference happens every time you press Generate.

Image-speak

Each of these has a full entry in the Academy glossary — inpainting, upscaling, and aspect ratio are the ones you will meet first when editing images in VAR2. Bookmark-worthy honorable mention: the negative prompt, where you list what you *do not* want.

Words you will hear in the wild

Vocabulary in action

Isometric illustration of a tiny startup office at night, pastel color palette, clean vector style, soft ambient glow, 1:1 aspect ratio

Model: nano-banana

One sentence, four vocab words doing real work: a style (isometric, vector), a palette (pastel), a mood (soft glow), and an aspect ratio (1:1). This is what fluency buys you.

Want to see how the pros wire these words together? Browse the model pages — start with Imagen 3 and Sora 2 — then head to Capabilities and Limits to learn what all this vocabulary can and cannot deliver.

Related glossary terms: Prompt, Token, Inference, Multimodal, Parameters

See every one of these terms doing real work in ready-made, remixable examples. Browse templates