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

Generative AI

C2PA

C2PA is an open standard for verifying the authenticity and provenance of digital content to combat misinformation and ensure trust.

AI Fundamentals

Calculus

Calculus is a branch of mathematics that deals with the study of rates of change and accumulation.

Machine Learning

Calibration Curve

A calibration curve is a graphical representation used to determine the concentration of a substance in an unknown sample by comparing it to a set of standard samples with known concentrations.

Computer Vision

Camera Exposure

Camera Exposure is the amount of light allowed to reach the camera sensor or film, determining the brightness of a photograph.

MLOps & Infrastructure

Canary Deployment

Canary Deployment is a software release strategy that gradually rolls out new code to a small subset of users before a full-scale launch.

Other

Candidate Matching

Candidate matching is the process of aligning job applicants' skills, experience, and qualifications with the specific requirements of a job opening to identify the best fit.

Computer Vision

Canny Edge Detector

Canny Edge Detector is a multi-stage algorithm used in image processing to identify sharp changes in intensity, which correspond to edges in an image.

Data & Analytics

Canonicalization

Canonicalization is the process of selecting the preferred version of a web page URL among multiple duplicates to improve SEO and avoid content duplication issues.

Data & Analytics

CAP Theorem

CAP Theorem is a principle in distributed computing that states a system can only guarantee two out of three properties: Consistency, Availability, and Partition Tolerance.

Other

Caption generation

Caption generation is the automated process of creating descriptive text that explains or complements images, videos, or other visual content.

Other

Caption Generator

A caption generator is a software tool that automatically creates descriptive or engaging text captions for images or videos.

Data & Analytics

Cartogram

A cartogram is a type of map where geographic areas are resized according to a specific data variable rather than their actual land area.

Generative AI

Case Study Generation

Case Study Generation is the process of creating detailed, real-world examples that illustrate how a product, service, or strategy delivers value and solves problems.

Data & Analytics

Cassandra

Cassandra is a highly scalable, distributed NoSQL database designed for handling large amounts of data across many servers with high availability and fault tolerance.

Other

CAT Tool

CAT Tool is a software application designed to assist translators by managing and reusing translation content efficiently.

Other

CAT Tools

CAT Tools are software applications designed to assist translators by automating and streamlining the translation process through features like translation memory and terminology management.

Machine Learning

CatBoost

CatBoost is a high-performance, open-source gradient boosting library designed to handle categorical features naturally and efficiently.

Other

Causal Machine Learning

Causal Machine Learning is a field of study that combines machine learning techniques with causal inference to understand and predict cause-and-effect relationships.

Data & Analytics

Causation

Causation is the relationship where one event or action directly leads to the occurrence of another event.

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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.