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 Fundamentals

Graph Theory

Graph Theory is a branch of mathematics focused on studying graphs, which are structures made up of nodes (vertices) connected by edges.

Other

Graphic Text Generator

A Graphic Text Generator is a digital tool that creates visually styled text designs for use in various media and marketing materials.

AI Agents & Systems

GraphPlan

GraphPlan is an efficient planning algorithm that constructs a layered graph to solve complex planning problems by systematically exploring possible actions and states.

Computer Vision

Grayscale

Grayscale is a range of shades of gray without any color, used to represent images or designs in varying intensities from black to white.

Other

Grayscale Image

A grayscale image is a digital picture composed exclusively of shades of gray, ranging from black to white, without any color.

AI Fundamentals

Grey Box

Grey box is a testing approach that combines both white box and black box testing techniques, providing partial knowledge of the internal workings of the system.

AI Fundamentals

Grid Computing

Grid Computing is a distributed computing model that involves a network of computers working together to perform large-scale tasks.

Machine Learning

Grid Search

Grid Search is a systematic method for hyperparameter optimization in machine learning models.

Machine Learning

Ground Truth

Ground truth is the accurate and objective data used as a reference to evaluate models or systems in various fields.

AI Ethics

Group Fairness

Group Fairness is a principle ensuring that different demographic or social groups receive equitable treatment and outcomes in algorithms, policies, or decision-making processes.

Deep Learning & Neural Networks

Group Normalization

Group Normalization is a technique used in machine learning to stabilize and accelerate the training of neural networks by normalizing feature activations across groups of channels.

Computer Vision

Grouped Convolution

Grouped convolution is a convolutional neural network technique that splits input channels into separate groups, performing convolution independently within each group to reduce computational cost and improve model efficiency.

Other

Growth Prediction

Growth prediction is the process of forecasting future increases in business metrics, market demand, or user engagement using data analysis and modeling techniques.

MLOps & Infrastructure

gRPC

gRPC is an open-source remote procedure call framework designed to efficiently connect services across different environments.

Deep Learning & Neural Networks

GShard

GShard is a system for efficiently scaling large-scale machine learning models by enabling model parallelism across thousands of devices.

Computer Vision

H.264

H.264 is a video compression standard that efficiently encodes digital video for streaming, storage, and broadcasting.

Computer Vision

H.265

H.265 is a video compression standard that efficiently encodes high-quality video at lower bitrates than its predecessor, H.264.

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.