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.

114 terms

AI Agents & Systems

V-REP

V-REP is a versatile robot simulation platform used for designing, testing, and controlling robotic systems in virtual environments.

Other

VAE

VAE is a Variational Autoencoder, a type of generative model in machine learning that learns to encode and generate data by approximating complex probability distributions.

Machine Learning

Validation Data

Validation Data is a subset of data used to assess the performance of a model during training, ensuring it generalizes well to unseen data.

Natural Language Processing (NLP)

VALL-E

VALL-E is an advanced text-to-speech model developed by Microsoft that can generate high-quality, natural-sounding speech from text inputs.

Reinforcement Learning

Value Function

Value function is a mathematical concept that represents the expected benefit or utility derived from different choices or states in decision-making processes.

Reinforcement Learning

Value Iteration

Value Iteration is an algorithm used in reinforcement learning and decision processes to calculate the optimal policy by iteratively improving value estimates for each state.

Machine Learning

Vanishing Gradient

Vanishing Gradient is a problem in training neural networks where gradients become too small, hindering effective learning.

Generative AI

Variation

Variation is the process or instance of changing or differing in form, appearance, or condition within a set of similar items or concepts.

Deep Learning & Neural Networks

Variational Autoencoder

A Variational Autoencoder (VAE) is a type of artificial neural network used for unsupervised learning that encodes input data into a compressed representation and then reconstructs it, allowing for data generation and feature learning.

Other

Variational Quantum Algorithm

Variational Quantum Algorithm is a hybrid quantum-classical method that uses parameterized quantum circuits optimized by classical algorithms to solve complex problems efficiently.

Data & Analytics

Vector Data

Vector data is a type of digital information used in geographic information systems (GIS) and computer graphics that represents spatial features using points, lines, and polygons.

Other

Vector Database

A vector database is a specialized data storage system designed to efficiently store, index, and search high-dimensional vector embeddings used in machine learning and AI applications.

Generative AI

Vector Embeddings

Vector embeddings are numerical representations of data that capture meaning, context, or relationships in a format that machines can understand and compare.

Natural Language Processing (NLP)

Vector Search

Vector search is a method of retrieving information by comparing numerical vector representations of data to identify semantic similarity rather than relying on exact keyword matching.

Data & Analytics

Vectorization

Vectorization is the process of converting data, text, or images into numerical vectors to enable efficient computation and analysis by machine learning models and algorithms.

Other

Vegetable Recognition

Vegetable recognition is the process of identifying and classifying vegetables using visual or sensory data, often powered by machine learning and computer vision technologies.

Computer Vision

Vertical Blanking Interval

Vertical Blanking Interval is the brief period during which a display device’s electron beam resets from the bottom to the top of the screen, allowing the image to refresh without visible distortion.

Deep Learning & Neural Networks

VGGNet

VGGNet is a deep convolutional neural network architecture known for its simplicity and effectiveness in image classification tasks.

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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.