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

MLOps & Infrastructure

Shadow Deployment

Shadow Deployment is a software release strategy where new code runs alongside the current system without affecting live operations, allowing real-world testing before full rollout.

Generative AI

Shap-E

Shap-E is a machine learning model designed to generate 3D shapes from textual descriptions, enabling seamless text-to-3D content creation.

Data & Analytics

Shapefile

Shapefile is a popular geospatial vector data format used to represent geographic features like points, lines, and polygons in mapping and GIS applications.

Other

Shapley values

Shapley values are a method from cooperative game theory used to fairly distribute the total gains or contributions among players based on their individual contributions.

Data & Analytics

Sharding

Sharding is a database architecture technique that splits large datasets into smaller, more manageable parts called shards to improve performance and scalability.

AI Agents & Systems

Shared Plan

A Shared Plan is a collaborative subscription model where multiple users or teams access a set of services or resources under a single account.

AI Agents & Systems

Shopping Agent

A Shopping Agent is a service or software that assists consumers in finding, comparing, and purchasing products from various retailers efficiently.

Computer Vision

Shot Noise

Shot noise is a type of electronic noise that arises from the discrete nature of electric charge causing random fluctuations in current or voltage.

Computer Vision

Shutter Speed

Shutter speed is the length of time a camera's shutter remains open to expose light onto the camera sensor or film.

AI Ethics

Side Effects

Side effects are unintended or secondary outcomes that occur in addition to the primary intended effect of an action, treatment, or process.

Computer Vision

SIFT

SIFT is an algorithm used in computer vision to detect and describe local features in images.

Deep Learning & Neural Networks

Sigmoid Function

The sigmoid function is a mathematical function that maps any real-valued number into a value between 0 and 1, often used in machine learning for logistic regression and neural networks.

Computer Vision

Signal-to-Noise Ratio

Signal-to-Noise Ratio is a measure comparing the level of a desired signal to the level of background noise, indicating the clarity of the signal.

Other

Silence Detection

Silence detection is a technology that identifies pauses or gaps in audio where no significant sound is present.

Other

Similarity Search

Similarity Search is a technique used to find items or data points that are most alike or closely related to a given query based on defined similarity metrics.

AI Agents & Systems

Simplex Algorithm

Simplex Algorithm is a mathematical method used to solve linear programming problems by efficiently navigating feasible solutions to find the optimal value.

AI Agents & Systems

Simulated Annealing

Simulated Annealing is a probabilistic optimization technique inspired by the annealing process in metallurgy used to find near-optimal solutions in complex search spaces.

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.