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

AI Fundamentals

P vs NP Problem

The P vs NP Problem is a major unsolved question in computer science that asks whether every problem whose solution can be quickly verified can also be quickly solved.

Machine Learning

P-Value

P-value is a statistical measure that helps determine the significance of results in hypothesis testing.

Deep Learning & Neural Networks

PaLM

PaLM is a state-of-the-art language model developed by Google, designed to understand and generate human-like text through advanced deep learning techniques.

Data & Analytics

Pandas

Pandas is an open-source Python library designed for data manipulation and analysis, providing easy-to-use data structures and tools.

Computer Vision

Panoptic Segmentation

Panoptic segmentation is an advanced image analysis technique that simultaneously performs instance segmentation and semantic segmentation.

Computer Vision

Panorama

Panorama is a wide-angle view or representation of a physical space, often captured in a single image or series of images.

AI Fundamentals

Parallel Computing

Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously.

Data & Analytics

Parallel Processing

Parallel processing is a computing technique where multiple tasks or instructions are executed simultaneously to increase efficiency and speed.

Machine Learning

Parametric Model

A parametric model is a type of statistical model characterized by a finite set of parameters used to describe a dataset.

Deep Learning & Neural Networks

Parametric ReLU

Parametric ReLU is a type of activation function used in neural networks that introduces a learnable parameter to control the slope of the negative part of the function.

Natural Language Processing (NLP)

Parsing

Parsing is the process of analyzing a string of symbols, either in natural language or computer languages, to determine its grammatical structure.

Generative AI

Parti

Parti is a fundamental architectural concept referring to the primary organizing idea or scheme that guides the design of a building or space.

AI Agents & Systems

Partial Order Planning

Partial Order Planning is a flexible AI planning technique that creates plans by ordering only necessary actions while allowing others to remain unordered.

Computer Vision

Particle Filter

A Particle Filter is an algorithm used for estimating the state of a system that changes over time and is particularly useful in systems with non-linear processes or noise.

AI Fundamentals

Particle Swarm Optimization

Particle Swarm Optimization (PSO) is a computational method used to optimize a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.

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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.