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.

134 terms

Other

Image Upscaling

Image upscaling is the process of increasing the resolution of a digital image to improve its size and quality without significant loss of detail.

Generative AI

Image-to-Image

Image-to-Image is a technique that transforms one image into another using algorithms, often for enhancing, editing, or generating visuals.

Other

Image-to-Image Translation

Image-to-Image Translation is a computer vision technique that converts images from one style or domain to another while preserving core content.

Generative AI

Image-to-Text

Image-to-Text is a technology that converts written or printed text within images into editable and searchable digital text.

Generative AI

Imagen

Image Short Definition: An image is a visual representation, such as a photo, graphic, or illustration, used to convey information or enhance content.

Generative AI

Img2Img

Img2Img is a digital image processing technique that transforms or edits an existing image into a new one using artificial intelligence or algorithms.

Reinforcement Learning

Imitation Learning

Imitation Learning is a machine learning technique where models learn to perform tasks by mimicking expert behavior instead of relying solely on trial-and-error.

AI Ethics

Impact Assessment

Impact Assessment is the systematic process of identifying and evaluating the potential effects of a project, policy, or activity on the environment, society, or business outcomes.

Other

In-Database Analytics

In-Database Analytics is the process of performing data analysis directly within a database system to improve speed and efficiency by avoiding data movement.

Other

In-Database Machine Learning

In-Database Machine Learning is the process of performing machine learning model training and prediction directly within a database system without moving data externally.

Data & Analytics

In-Memory Database

An in-memory database is a type of database that stores data primarily in the main memory (RAM) for faster access and processing compared to disk-based databases.

Generative AI

Inception Score

Inception Score is a metric used to evaluate the quality and diversity of images generated by artificial intelligence models.

Other

Incident Automation

Incident Automation is the process of using software tools and predefined workflows to automatically detect, analyze, and resolve IT incidents without manual intervention.

MLOps & Infrastructure

Incident Management

Incident Management is the process of identifying, analyzing, and resolving unexpected disruptions to restore normal service operations as quickly as possible.

Data & Analytics

Indexing

Indexing is the process by which search engines organize and store web content to make it quickly retrievable for relevant search queries.

AI Ethics

Individual Fairness

Individual Fairness is a principle that ensures similar individuals receive similar treatment or outcomes in decision-making systems.

Machine Learning

Inductive Learning

Inductive Learning is a method in machine learning where algorithms formulate general rules from observed instances or data.

AI Agents & Systems

Industrial Robot

Industrial robot is a programmable automated machine designed to perform manufacturing tasks with precision and efficiency.

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.