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

AI Agents & Systems

Inertial Measurement Unit

An Inertial Measurement Unit (IMU) is a device that measures and reports a body’s specific force, angular rate, and sometimes magnetic field, enabling precise motion tracking.

Other

Inference

Inference is the process of drawing logical conclusions from available data or evidence.

AI Fundamentals

Inference Engine

An inference engine is a component of artificial intelligence that applies logical rules to a knowledge base to deduce new information.

Other

Inference Steps

Inference steps are the sequential logical processes through which conclusions are drawn from given data or premises.

AI Agents & Systems

Information Agent

An Information Agent is a software program or system designed to collect, process, and deliver relevant data or knowledge to users or other systems.

Machine Learning

Information Gain

Information Gain is a metric used to measure how much information a feature provides about a class in machine learning and decision tree algorithms.

AI Fundamentals

Information Theory

Information Theory is a mathematical framework for quantifying the transmission, processing, and storage of information.

MLOps & Infrastructure

Infrastructure as Code

Infrastructure as Code (IaC) is the practice of managing and provisioning computing infrastructure through machine-readable configuration files instead of manual hardware setup or interactive configuration tools.

Other

Ingredient Scanner

Ingredient Scanner is a digital tool that identifies and provides detailed information about the components in food or product labels using scanning technology.

AI Ethics

Inner Alignment

Inner Alignment is the process of ensuring that a machine learning model’s internal objectives align with the intended external goals set by its developers.

Other

InsightFace

InsightFace is an open-source deep learning framework for efficient and accurate face recognition and analysis.

Other

Inspection Automation

Inspection automation is the use of technology and software to perform quality checks and evaluations without manual intervention.

Machine Learning

Instance-Based Learning

Instance-Based Learning is a type of machine learning where the model memorizes the training instances and uses them to make predictions.

AI Agents & Systems

Instrumental Convergence

Instrumental convergence is the tendency of different intelligent agents to pursue similar intermediate goals as a means to achieve a wide variety of ultimate objectives.

MLOps & Infrastructure

Integration Testing

Integration Testing is the process of evaluating how different software modules work together to ensure combined functionality performs as expected.

Generative AI

Intellectual Property

Intellectual Property is the legal protection of creations of the mind, such as inventions, designs, and artistic works, granting exclusive rights to their creators.

Other

Intelligence Processing Unit

An Intelligence Processing Unit (IPU) is a specialized microprocessor designed to accelerate artificial intelligence and machine learning tasks efficiently.

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.