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

Football Analytics

Football Analytics is the practice of using data analysis and statistical methods to improve decision-making and performance in football (soccer) or American football.

Other

Form Embedding

Form embedding is the process of integrating interactive web forms directly into a webpage to collect user data seamlessly.

AI Ethics

Formal Verification

Formal Verification is a mathematical process used to prove or disprove the correctness of a system's design against specified properties or requirements.

AI Agents & Systems

Forward Chaining

Forward chaining is a reasoning method that starts with known facts and applies inference rules to derive new information until a goal is reached.

Generative AI

Foundation Model

A foundation model is a large, pre-trained AI model designed to serve as a flexible base that can be adapted to many different tasks and applications.

Machine Learning

FP-Growth

FP-Growth is an algorithm used for frequent pattern mining, which identifies recurring patterns in data sets without generating candidate sets.

Computer Vision

FPS

FPS is the abbreviation for Frames Per Second, a measure of how many individual images a video or animation displays each second.

Generative AI

Fréchet Inception Distance

Fréchet Inception Distance (FID) is a metric used to evaluate the quality of images generated by AI models by comparing their statistical features to real images.

Computer Vision

Frame Differencing

Frame Differencing is a video processing technique used to detect motion by comparing differences between frames.

Other

Frame Generation

Frame generation is a technique used to create intermediate frames between existing ones to produce smoother motion in videos and animations.

Other

Framework

A framework is a structured foundation of tools, libraries, and guidelines designed to simplify and accelerate the development of applications or systems.

AI Agents & Systems

Friendly AI

Friendly AI is artificial intelligence designed to prioritize human values, safety, and ethical considerations to ensure beneficial outcomes for society.

Data & Analytics

Full-Text Search

Full-text search is a search technique that scans and retrieves information by analyzing the complete text content within documents or databases.

Data & Analytics

Funnel Analysis

Funnel analysis is a method used to track and understand the steps users take to complete a specific goal on a website or app.

AI Fundamentals

Fuzzy Logic

Fuzzy Logic is a computational approach that allows for approximate rather than fixed and exact reasoning, similar to human decision-making.

Data & Analytics

Fuzzy Search

Fuzzy search is a technique that finds matches in data by allowing for approximate, rather than exact, string matching.

Machine Learning

Gain Chart

A Gain Chart is a graphical representation used to measure the performance of classification models by displaying the cumulative gains against the percentage of data processed.

Generative AI

Game Design

Game Design is the process of creating the rules, content, and structure of a game to deliver engaging and meaningful player experiences.

AI Fundamentals

Game Theory

Game Theory is the study of strategic decision-making among individuals or entities in situations where their choices affect one another.

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.