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

Health Data Analytics

Health Data Analytics is the process of collecting, examining, and interpreting health-related data to improve patient care, optimize operations, and support medical research.

Other

Healthcare AI

Healthcare AI is the application of artificial intelligence technologies to improve medical diagnosis, treatment, and patient care.

Natural Language Processing (NLP)

HELM

HELM is a cloud-native package manager that streamlines the deployment and management of applications within Kubernetes clusters.

Other

Helpdesk Automation

Helpdesk automation is the use of technology to streamline and manage customer support tasks without manual intervention.

Machine Learning

Heteroscedasticity

Heteroscedasticity is a condition in statistical models where the variability of a variable is unequal across the range of values of a second variable that predicts it.

Generative AI

Heun Sampler

Heun Sampler is a numerical method used in machine learning and computational statistics to generate samples from complex probability distributions efficiently.

AI Fundamentals

Heuristic

A heuristic is a practical approach to problem-solving based on experience and common sense, rather than strict algorithms or rules.

Computer Vision

HEVC

HEVC is a video compression standard designed to efficiently encode high-quality video at lower bitrates.

Machine Learning

Hidden Markov Model

A Hidden Markov Model (HMM) is a statistical model used to represent systems that are assumed to follow a Markov process with hidden states.

MLOps & Infrastructure

High Availability

High Availability is a system design approach that ensures continuous operation and minimal downtime by minimizing service interruptions.

Computer Vision

High Dynamic Range

High Dynamic Range (HDR) is a technology that enhances the contrast and color range of images and videos to produce more vivid and lifelike visuals.

Generative AI

High-Resolution Synthesis

High-Resolution Synthesis is the process of generating detailed, high-quality digital outputs, such as images or audio, by combining and enhancing data at a fine level of precision.

AI Agents & Systems

Hill Climbing

Hill climbing is an optimization algorithm that iteratively improves a solution by making small changes to reach a peak or optimal point.

Machine Learning

Hinge Loss

Hinge Loss is a loss function used primarily in machine learning for "maximum-margin" classification models, notably support vector machines.

Data & Analytics

HIPAA

HIPAA is a U.S. federal law designed to protect sensitive patient health information and ensure privacy and security in healthcare.

Computer Vision

Histogram Equalization

Histogram equalization is a technique in image processing that enhances contrast by redistributing the intensity values of an image.

Data & Analytics

Hive

Hive is a data warehousing tool built on top of Hadoop that facilitates querying and managing large datasets using a SQL-like language called HiveQL.

Computer Vision

HOG

HOG, or Histogram of Oriented Gradients, is a feature descriptor used in computer vision and image processing for detecting objects.

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.