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

Deep Learning & Neural Networks

Pix2Pix

Pix2Pix is a deep learning model developed for image-to-image translation tasks using a conditional generative adversarial network (cGAN).

Other

Pix2Pix Model

Pix2Pix Model is a type of generative adversarial network (GAN) designed for image-to-image translation tasks.

Computer Vision

Pixel

Pixel is the smallest unit of a digital image or display that represents a single point of color.

Deep Learning & Neural Networks

PixelRNN

PixelRNN is a type of neural network designed for image generation, predicting the value of each pixel sequentially based on the pixels previously generated.

Other

Planar Tracking

Planar tracking is a computer vision technique that tracks flat surfaces or planes within video footage to analyze motion and changes over time.

Other

Plant Disease Detection

Plant disease detection is the process of identifying and diagnosing diseases in plants using various techniques and tools.

Other

Player Projection

Player projection is the process of estimating a sports player's future performance based on past data and predictive analytics.

Other

Player Tracking

Player tracking is the technology and process used to monitor and analyze the movement, behavior, and performance of players in sports or gaming environments.

Data & Analytics

Plotly

Plotly is an interactive data visualization library used to create dynamic and shareable charts and graphs for web applications and data analysis.

Generative AI

Poetry Generation

Poetry generation is the process of creating poetic text through computational methods that mimic human creativity and language patterns.

Data & Analytics

Point

Point is a specific location or position in space or on a surface, often used as a fundamental element in geometry and other fields.

Computer Vision

Point Cloud

A point cloud is a collection of data points in space, often used to represent the surface of a 3D object or environment.

Generative AI

Point-E

Point-E is an AI-driven system designed to generate 3D point clouds from simple 2D images or text prompts, enabling quick and efficient 3D model creation.

Computer Vision

Pointwise Convolution

Pointwise convolution is a type of convolutional operation using 1x1 filters to combine input channels and reduce computational complexity in neural networks.

Other

Poker Bot

A poker bot is an automated software program designed to play poker games by making strategic decisions without human intervention.

Reinforcement Learning

Policy Iteration

Policy Iteration is a dynamic programming method used in reinforcement learning to find the optimal policy by iteratively evaluating and improving policies.

Other

Policy Optimization

Policy optimization is a method in reinforcement learning focused on improving decision-making strategies by directly adjusting policies to maximize rewards.

Natural Language Processing (NLP)

Poly-Encoder

A Poly-Encoder is an advanced neural network architecture used to efficiently encode and match multiple context representations in tasks such as question-answering and dialogue systems.

Data & Analytics

Polygon

Polygon is a multi-sided geometric shape used in mathematics and computer graphics to represent complex forms and areas.

Other

Polygon Annotation

Polygon annotation is a method of labeling objects in images by outlining their exact shape with multiple connected points to create a polygon.

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.