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.

208 terms

Generative AI

Prototyping

Prototyping is the process of creating an early model or sample of a product to test and validate ideas before full-scale development.

Machine Learning

Pruning

Pruning is the process of removing unnecessary elements from a dataset or structure to improve efficiency and performance.

Generative AI

Pseudo Linear Multi-Step

Pseudo Linear Multi-Step is a numerical method used to solve complex differential equations by combining linear approximations with multiple iterative steps for enhanced accuracy.

Data & Analytics

Pseudonymization

Pseudonymization is a data protection technique that replaces personal identifiers with artificial identifiers to safeguard privacy while maintaining data usability.

Data & Analytics

Public Data

Public data is information that is freely accessible to anyone without restrictions or the need for special permissions.

Reinforcement Learning

PUCT

PUCT is a variant of the Upper Confidence Bound algorithm used in Monte Carlo Tree Search to balance exploration and exploitation during decision-making.

Generative AI

Purple Teaming

Purple Teaming is a collaborative cybersecurity approach where red (attack) and blue (defense) teams work together to enhance an organization’s security posture.

Data & Analytics

PySpark

PySpark is the Python API for Apache Spark, enabling large-scale data processing and analytics using Python programming language.

Other

Python

Python is a versatile, high-level programming language known for its readability and broad applications in software development, data analysis, and automation.

Other

Python 3

Python 3 is the latest major version of the Python programming language, designed for clear syntax, improved functionality, and modern programming practices.

Other

Python Programming

Python programming is the practice of writing code using the Python language, a versatile and beginner-friendly programming language used for software development, data analysis, automation, and more.

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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.