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.

82 terms

Other

News Summarization

News summarization is the process of condensing lengthy news articles into concise, clear, and informative summaries that capture the essential information.

Data & Analytics

NewSQL

NewSQL is a modern relational database technology that combines the scalability of NoSQL systems with the ACID compliance and structured query capabilities of traditional SQL databases.

Generative AI

NFT

NFT is a non-fungible token, a unique digital asset that represents ownership of a specific item or piece of content on a blockchain.

Computer Vision

Night Vision

Night vision is the ability to see in low-light or dark environments using specialized technology that amplifies available light or detects infrared radiation.

Other

NLP

NLP is natural language processing, a field of artificial intelligence focused on enabling computers to understand, interpret, and generate human language.

Natural Language Processing (NLP)

NLTK

NLTK is a leading platform for building Python programs to work with human language data, offering tools for text processing and analysis.

Machine Learning

No Free Lunch Theorem

The No Free Lunch Theorem is a principle stating that no single optimization algorithm is universally optimal for all possible problems.

Other

No-Code AI

No-Code AI is a platform or tool that enables users to build, deploy, and manage artificial intelligence applications without requiring programming skills.

AI Fundamentals

Node

A Node is a fundamental part of a data structure, such as linked lists or trees, that contains data and links to other nodes.

Natural Language Processing (NLP)

Noise Reduction

Noise reduction is the process of minimizing unwanted or irrelevant data—such as background sounds, visual artifacts, or textual clutter—to improve the clarity, accuracy, and usability of information processed by an AI or digital system.

AI Ethics

Non-Maleficence

Non-Maleficence is the ethical principle of avoiding harm or injury to others in any professional or personal context.

Other

Non-Maximum Suppression

Non-Maximum Suppression is an algorithm used to select the most relevant bounding boxes by eliminating overlapping or redundant detections in object detection tasks.

Data & Analytics

Non-Relational Database

Non-Relational Database is a type of database that stores data in a flexible, schema-less format, unlike traditional relational databases that use structured tables.

Other

Nonprofit AI Initiatives

Nonprofit AI initiatives are projects and programs led by nonprofit organizations that leverage artificial intelligence to address social, environmental, and humanitarian challenges.

AI Agents & Systems

Norms

Norms are shared rules or expectations that guide behavior within a group or society.

Data & Analytics

NoSQL

NoSQL is a type of database designed for flexible, scalable storage of unstructured or semi-structured data without relying on traditional relational tables.

Other

Note-Taking Software

Note-taking software is a digital tool designed to help users capture, organize, and manage written or multimedia notes efficiently.

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.

Read more Read less

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.