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.

122 terms

Other

Facial Landmarking

Facial landmarking is the process of identifying and mapping key points on a human face to analyze its structure and features.

Other

Facial Motion Capture

Facial Motion Capture is a technology that records an actor's facial expressions and movements to create realistic digital animations.

Other

Facial Recognition

Facial recognition is a technology that identifies or verifies a person's identity using their facial features.

Other

Facial Tracking

Facial tracking is the technology that detects and monitors facial movements and expressions in real-time using cameras and software algorithms.

Data & Analytics

Fact Table

A Fact Table is a central database table in a data warehouse that stores quantitative data for analysis, typically containing measurable, numerical metrics linked to dimension tables.

Generative AI

Fair Use

Fair Use is a legal doctrine that allows limited use of copyrighted material without permission for purposes such as criticism, commentary, news reporting, education, or research.

AI Ethics

Fairness

Fairness is the quality of making judgments and decisions that are free from bias, favoritism, or injustice, ensuring equal treatment for all individuals or groups.

Other

Fairness in AI

Fairness in AI is the principle of designing and deploying artificial intelligence systems that treat all individuals and groups impartially, avoiding bias and discrimination.

AI Ethics

Fairness Metrics

Fairness metrics are quantitative measures used to evaluate and ensure equitable treatment and unbiased outcomes in algorithms and decision-making systems.

Other

Fake Data

Fake data is artificially created information used to simulate real data for testing, training, or demonstration purposes.

Other

Fall Detection

Fall detection is a technology or system designed to identify when a person has experienced a fall, often to trigger alerts for timely assistance.

Other

FAQ Automation

FAQ Automation is the use of technology to automatically create, manage, and update Frequently Asked Questions on websites or platforms.

Other

Fashion Design AI

Fashion Design AI is the use of artificial intelligence technologies to assist in creating, predicting, and optimizing fashion designs and trends.

Other

Fashion Tech

Fashion Tech is the integration of technology into the fashion industry to innovate design, production, and retail experiences.

Deep Learning & Neural Networks

Fast R-CNN

Fast R-CNN is a deep learning algorithm used for object detection that improves speed and accuracy by processing images in a single forward pass.

MLOps & Infrastructure

FastAPI

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python based on standard Python type hints.

Deep Learning & Neural Networks

Faster R-CNN

Faster R-CNN is a deep learning model used for object detection that combines region proposal networks with convolutional neural networks for high-speed and accurate detection.

Deep Learning & Neural Networks

FastText

FastText is an open-source, library developed by Facebook's AI Research (FAIR) lab used to efficiently learn word representations and text classifications.

Other

Fatigue Detection

Fatigue detection is a technology or method used to identify signs of tiredness or drowsiness in individuals, often to prevent accidents or improve safety.

Machine Learning

Feature

A feature is a distinct attribute or aspect of a product or service that provides value to the user.

Other

Feature Attribution

Feature attribution is the process of identifying and assigning credit to specific features or elements that contribute to a model’s predictions or outcomes.

Computer Vision

Feature Descriptor

A feature descriptor is a representation of an object or pattern's visual features used in image processing and computer vision.

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.