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.

294 terms

Other

Core ML

Core ML is Apple’s machine learning framework that enables developers to integrate trained models into iOS, macOS, and other Apple platform apps for efficient on-device inference.

Computer Vision

Corner Detection

Corner detection is a technique used in computer vision to identify points in an image where the direction of intensity changes sharply.

Natural Language Processing (NLP)

Corpus

A corpus is a structured and curated collection of texts—written or spoken—used for linguistic research, natural language processing (NLP), and training machine learning models.

Data & Analytics

Correlation

Correlation is a statistical measure that describes the strength and direction of a relationship between two variables.

Deep Learning & Neural Networks

CosFace

CosFace is a deep learning approach used to improve face recognition accuracy by optimizing the margin between classes in the cosine space.

Machine Learning

Cost Function

A cost function is a mathematical formula used to measure the error or "cost" of a model's predictions compared to the actual data.

MLOps & Infrastructure

Cost Management

Cost Management is the process of planning, monitoring, and controlling expenses to ensure a project or business operates within its budget.

Data & Analytics

CouchDB

CouchDB is an open-source NoSQL database that stores data in JSON format and uses a flexible, distributed architecture for scalable web applications.

AI Ethics

Counterfactual Explanations

Counterfactual explanations are descriptions of how changing specific input features would alter the outcome of a decision-making model.

AI Ethics

Counterfactual Fairness

Counterfactual fairness is a fairness criterion in machine learning that ensures decisions remain unchanged in hypothetical scenarios where a protected attribute is altered.

Machine Learning

Covariate Shift

Covariate shift is a scenario in machine learning where the distribution of input data changes between the training phase and the application phase.

Generative AI

Creative AI

Creative AI is artificial intelligence designed to generate original ideas, content, or artwork by mimicking human creativity.

Other

Creative AI Tools

Creative AI tools are software applications powered by artificial intelligence designed to assist and enhance the creative process in fields like writing, design, music, and multimedia production.

Other

Creative Prompt

A creative prompt is a stimulus or idea designed to inspire original thinking and generate new content or solutions.

Other

Creative Writing AI

Creative Writing AI is artificial intelligence designed to generate original and imaginative written content such as stories, poems, or scripts.

Other

Creative Writing Prompt

A creative writing prompt is a starting idea or stimulus designed to inspire writers to produce original stories, poems, or other written works.

Generative AI

Creator Economy

Creator Economy is the digital ecosystem where independent content creators monetize their skills, audience, and creations through online platforms and tools.

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.