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.

173 terms

Computer Vision

RGB

RGB is a color model that uses red, green, and blue light to create a wide spectrum of colors in digital displays and imaging.

Machine Learning

Ridge Regression

Ridge Regression is a type of linear regression that includes a regularization term to prevent overfitting by penalizing large coefficients.

Generative AI

Riffusion

Riffusion is an AI-powered technology that generates music riffs by transforming sound patterns into images and vice versa.

AI Ethics

Right to be Forgotten

The Right to be Forgotten is a legal principle allowing individuals to request the removal of personal information from online platforms under certain conditions.

AI Ethics

Right to Explanation

The Right to Explanation is a principle that allows individuals to understand how automated systems, especially AI algorithms, make decisions affecting them.

Computer Vision

Ringing Artifact

Ringing artifact is a visual distortion characterized by ripple-like patterns appearing near sharp edges in digital images or signals.

AI Ethics

Risk Assessment

Risk assessment is the process of identifying, evaluating, and prioritizing potential risks that could negatively impact a business or project.

Reinforcement Learning

RL Action

RL Action is a decision or move taken by an agent within a Reinforcement Learning environment to maximize rewards and achieve specific goals.

Reinforcement Learning

RL Agent

An RL Agent is a software entity that learns to make decisions by interacting with an environment using reinforcement learning principles.

Reinforcement Learning

RL Environment

RL Environment is the setting or system within which a reinforcement learning agent interacts, making decisions and receiving feedback to learn optimal behavior.

Reinforcement Learning

RL Horizon

RL Horizon is the planning timeframe in reinforcement learning that defines how far into the future an agent considers its actions to maximize cumulative rewards.

Reinforcement Learning

RL Policy

RL Policy is a set of rules or guidelines that an agent follows to make decisions in reinforcement learning environments.

Reinforcement Learning

RL Reward

RL Reward is a feedback signal in reinforcement learning that quantifies the success of an agent's actions toward achieving a goal.

Reinforcement Learning

RL State

RL State is the representation of an environment's current situation used by a reinforcement learning agent to make decisions.

Natural Language Processing (NLP)

RLHF

RLHF (Reinforcement Learning from Human Feedback) is a training method that improves AI behavior by using human judgments to guide and refine model outputs.

Machine Learning

RMSprop

RMSprop is an adaptive learning rate optimization algorithm primarily used in training artificial neural networks.

Other

Road Defect Detection

Road defect detection is the process of identifying and analyzing damages or irregularities on road surfaces to ensure maintenance and safety.

Generative AI

Road Network Generation

Road Network Generation is the process of creating and designing interconnected pathways and streets for transportation and urban planning purposes.

Deep Learning & Neural Networks

RoBERTa

RoBERTa is a robustly optimized BERT approach, designed to improve the performance of NLP models by fine-tuning hyperparameters and training on more data.

AI Agents & Systems

Roboethics

Roboethics is the study of moral principles and ethical guidelines governing the design, development, and use of robots and autonomous systems.

AI Agents & Systems

Robot

A robot is a programmable machine designed to perform tasks automatically or with minimal human intervention.

AI Agents & Systems

Robot Grasping

Robot grasping is the ability of a robotic system to securely hold and manipulate objects using mechanical hands or grippers.

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.