AI Glossary: 3,885 terms, defined

Plain-language definitions of the vocabulary used across machine learning, model architectures, tooling and AI safety. Every entry opens with a one-sentence definition, then explains where the term is used.

3,885 terms

Other

Quantum Annealing

Quantum annealing is a quantum computing technique used to solve complex optimization problems by finding the lowest energy state of a system.

Data & Analytics

Query Execution Plan

A Query Execution Plan is a detailed roadmap that a database follows to retrieve or manipulate data for a given query efficiently.

Data & Analytics

Query Optimization

Query Optimization is the process of improving database queries to execute more efficiently and retrieve data faster.

Other

Question Generation

Question Generation is the process of automatically creating relevant and meaningful questions from text or data to facilitate learning, assessment, or conversational AI.

Other

Quiz Embedding

Quiz embedding is the process of integrating interactive quizzes directly into web pages or digital content to engage users and collect data.

Generative AI

Quiz Generation

Quiz generation is the process of creating interactive question-and-answer assessments designed to test knowledge or gather information.

Other

R

R is a programming language and environment designed for statistical computing, data analysis, and graphical representation.

Other

R Package

An R package is a collection of R functions, data, and compiled code bundled together to extend the capabilities of the R programming environment.

Deep Learning & Neural Networks

R-CNN

R-CNN is a family of machine learning models designed to perform object detection tasks by combining region proposal methods with convolutional neural networks.

Machine Learning

R-Squared

R-Squared is a statistical measure that represents the proportion of variance for a dependent variable that's explained by an independent variable or variables in a regression model.

Data & Analytics

R-Tree

R-Tree is a tree data structure used for indexing multi-dimensional spatial data such as geographical coordinates, rectangles, and polygons.

Computer Vision

Radar

Radar is a technology that uses radio waves to detect and locate objects by measuring the time it takes for signals to bounce back.

Other

Radiology AI

Radiology AI is the application of artificial intelligence technologies to assist in interpreting medical images for improved diagnosis and patient care.

AI Fundamentals

RAG

(Retrieval-Augmented Generation) Short Definition: Retrieval-Augmented Generation (RAG) is an AI architecture that combines information retrieval with text generation to produce responses grounded in external, up-to-date, or proprietary data.

Machine Learning

Random Forest

Random Forest is an ensemble learning method used for classification and regression tasks by constructing multiple decision trees and outputting the mode or mean prediction.

Machine Learning

Random Search

Random Search is a simple optimization technique that explores a problem space by randomly selecting points to evaluate.

Machine Learning

Ranking

Ranking is the position at which a website or webpage appears in search engine results pages (SERPs).

About the TiorAI AI Glossary

The TiorAI AI Glossary is a free reference of 3,885 artificial intelligence terms, each defined in plain English. Every entry opens with a one-sentence definition that stands on its own, then explains where the term is actually used and how it sits next to the ideas around it. There is nothing to sign up for and nothing to download: each definition has its own page and its own URL, so a term you needed once can be linked to and found again.

Three ways to find a term

They combine, and none of them cancels the others. The A to Z strip narrows the index to a single initial, with the # key collecting the entries that begin with a digit or a symbol and that no letter would reach. The category filter cuts the glossary to one of sixteen subject areas, among them Machine Learning, Deep Learning and Neural Networks, Natural Language Processing, Computer Vision, Generative AI, Reinforcement Learning, AI Agents and Systems, MLOps and Infrastructure, Data and Analytics, and AI Ethics. The search field matches names and definitions, so a concept you can only half-name still surfaces. Every combination has its own URL, which means a narrowed view can be bookmarked or sent to a colleague.

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What the definitions cover

The vocabulary of modern AI, at the three depths people arrive needing. The fundamentals a first week runs into — model, parameter, training, inference, overfitting. The architecture behind current systems — transformers, attention, embeddings, diffusion, retrieval-augmented generation. And the operational and governance language that turns up in a procurement review or a policy document — fine-tuning, hallucination, alignment, model drift, bias. Terms are defined as they are used in practice rather than as they appear in a paper abstract.

Definitions that answer first

Each entry leads with the answer. The opening sentence says what the term means without assuming the rest of the page, which is what makes an entry useful to someone who arrived from a search with exactly one question. The explanation underneath is for the reader who wants more than that: what the idea is commonly confused with, what it looks like in practice, and which neighbouring terms are worth reading next. The card in the index above shows the opening of that definition, so you can tell from the results whether an entry is the one you want.

Where the glossary fits

A glossary answers what something means; it is not the place that tells you what to do about it. Where a concept has products behind it, the AI tools directory is where they are listed, and where it has a working instruction behind it, the prompt library is where that lives. Entries link out to those when the link earns its place, and the glossary stays what a glossary is — the definitions, ordered so they can be browsed, and written so a single one can be read on its own.

Using this glossary

How is the glossary ordered?

Alphabetically by term name, which is the order a reference work is browsed in and the order every page of this archive has always used. The sort menu can switch it to reverse alphabetical, or to recently added and recently updated if you want to see what has changed.

What does the letter strip do?

It narrows the index to terms whose name begins with that character, and it keeps whatever else you have set — a category filter, a search, a sort — so you can move between letters without starting again. The # entry collects the terms that begin with a digit or a symbol, which no letter would reach.

Why do some terms have no specific category?

Entries that span several areas, or that predate the current category set, sit under “Other”. It holds a large share of the glossary, so the filter is most useful for narrowing to a named topic rather than for excluding one.

What is in a glossary entry?

A short definition in plain language, then a longer explanation of where the term is used and how it relates to neighbouring concepts. The card above shows the opening of that definition; the entry itself also links to related terms and, where relevant, to the AI tools that implement the idea.

How do I search the glossary?

The field at the top matches term names and definitions, so a concept you can only half-name will usually surface. Search combines with the category filter and the letter strip, and every combination has its own URL, so a narrowed view can be bookmarked or shared.