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.

306 terms

Data & Analytics

S3

S3 is Amazon Simple Storage Service, a scalable cloud storage solution designed for storing and retrieving any amount of data from anywhere on the web.

Machine Learning

Saddle Point

A saddle point is a point in the domain of a function where the function changes direction from increasing to decreasing, or vice versa, without having a local extremum.

AI Ethics

Safe Exploration

Safe Exploration is a strategy that ensures discovering new information or opportunities while minimizing risks and negative consequences.

AI Ethics

Safe Reinforcement Learning

Safe Reinforcement Learning is a branch of reinforcement learning focused on ensuring that autonomous agents learn and act without causing harmful or risky behaviors.

AI Ethics

Safety

Safety is the condition of being protected from harm, danger, or risk in any environment or activity.

Generative AI

Safety Filter

Safety filter is a technology designed to identify and block harmful, inappropriate, or unsafe content from digital platforms.

Computer Vision

Saliency Detection

Saliency detection is a computer vision technique that identifies the most visually prominent or important regions in an image or video.

Computer Vision

Salt and Pepper Noise

Salt and pepper noise is a type of digital image noise characterized by random occurrences of black and white pixels scattered throughout the image.

Generative AI

Sandwiching

Sandwiching is an SEO technique that involves placing a targeted keyword or phrase between two pieces of content or links to improve search engine rankings and user engagement.

Data & Analytics

Sankey Diagram

A Sankey diagram is a flow chart that visually represents the magnitude of transfers or flows between entities using arrows proportional to the flow quantity.

Machine Learning

SARIMA

SARIMA is a statistical model used for forecasting time series data that incorporates seasonal patterns, trends, and noise.

Reinforcement Learning

SARSA

SARSA is a reinforcement learning algorithm that updates its action-value estimates based on the current state, action, reward, next state, and next action.

Computer Vision

Satellite Imagery

Satellite imagery is the collection of visual data of Earth’s surface captured by sensors on satellites orbiting the planet.

AI Agents & Systems

SatPlan

SatPlan is a planning algorithm that transforms planning problems into Boolean satisfiability problems to find solutions using SAT solvers.

Computer Vision

Saturation

Saturation is the intensity or purity of a color, indicating how vivid or muted it appears.

MLOps & Infrastructure

Scalability

Scalability is the ability of a system, network, or process to handle increased demand or growth efficiently without sacrificing performance.

Generative AI

Scalable Oversight

Scalable oversight is a systematic approach to managing, monitoring, and controlling complex processes or systems efficiently as they grow in size or complexity.

Other

Scam Detection

Scam detection is the process of identifying and preventing fraudulent activities by recognizing deceptive patterns and behaviors.

Data & Analytics

Scatter Plot

A scatter plot is a graphical representation that displays values for two variables as points on a two-dimensional grid, revealing relationships or patterns between them.

Generative AI

Scenario Generation

Scenario Generation is the process of creating detailed, plausible future situations to explore potential outcomes and inform decision-making.

Other

Scene Detection

Scene detection is the process of identifying and segmenting distinct scenes within a video or film based on changes in visual or audio content.

Other

Scene Recognition

Scene Recognition is a computer vision process that identifies and classifies the overall environment or context within an image or video.

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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.