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

AI Agents & Systems

Human-Robot Interaction

Human-Robot Interaction is the study and design of communication and cooperation between humans and robots to achieve effective and intuitive collaboration.

Other

Humanization

Humanization is the process of making technology, communication, or content feel more relatable, authentic, and emotionally engaging by incorporating human traits and perspectives.

Other

Humanizing AI Content

Humanizing AI content is the process of making machine-generated text feel natural, relatable, and engaging by adding human-like tone, emotion, and context.

AI Agents & Systems

Humanoid Robot

Humanoid robot is a robot designed to resemble the human body in shape and movement, often used to interact with people or perform human-like tasks.

Other

Hybrid Intelligence

Hybrid Intelligence is the combined cognitive ability of humans and artificial intelligence systems working collaboratively to enhance decision-making and problem-solving.

Generative AI

Hyper-Personalization

Hyper-Personalization is an advanced marketing technique that uses real-time data and AI to deliver highly tailored content and experiences to individual customers.

AI Fundamentals

Hyperautomation

Hyperautomation is the application of advanced technologies, like artificial intelligence and machine learning, to automate processes beyond traditional automation capabilities.

Generative AI

Hypernetwork

Hypernetwork is a neural network architecture where one network generates the weights or parameters for another network to enhance adaptability and efficiency.

Other

Hyperparameter Optimization

Hyperparameter optimization is the process of automatically finding the best settings for a machine learning model’s hyperparameters to improve its performance.

Machine Learning

Hyperparameter Tuning

Hyperparameter tuning is the process of selecting the optimal set of parameters that governs the learning process of a machine learning model.

Computer Vision

Hyperspectral Imaging

Hyperspectral imaging is a technology that captures and processes information across a wide spectrum of light wavelengths to analyze the composition of objects in great detail.

Generative AI

Icon Generation

Icon Generation is the process of creating visual symbols or graphics that represent ideas, objects, or actions, often used in digital interfaces and branding.

Other

ID Document Recognition

ID Document Recognition is a technology that automatically identifies and extracts information from identity documents such as passports, driver’s licenses, or ID cards.

Other

IDE integration

IDE integration is the process of connecting an Integrated Development Environment with external tools or services to enhance software development workflows.

Data & Analytics

Identity and Access Management

Identity and Access Management (IAM) is a framework of policies and technologies that ensures the right individuals have appropriate access to an organization’s resources.

Other

Identity Verification

Identity verification is the process of confirming a person's identity using various methods to ensure they are who they claim to be.

AI Ethics

IEEE 7000

IEEE 7000 is a standard that provides a structured process for addressing ethical concerns in system design and development.

Other

iframe

An iframe is an HTML element that allows embedding another HTML document within the current web page.

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.