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.

3,885 terms

Other

Thematic Search

Thematic search is a search technique that focuses on finding information based on overarching themes or topics rather than exact keywords.

Other

Therapy Chatbot

A therapy chatbot is an AI-powered digital tool designed to provide mental health support and guidance through conversational interactions.

Computer Vision

Thermal Imaging

Thermal imaging is a technology that captures images based on the heat emitted by objects, allowing visualization of temperature differences.

Computer Vision

Thinning

Thinning is the agricultural or horticultural practice of selectively removing plants or branches to improve growth, health, and yield.

Machine Learning

Thompson Sampling

Thompson Sampling is a probabilistic algorithm used for decision-making under uncertainty, often applied in multi-armed bandit problems.

Other

Tidy Data

Tidy data is a standardized way of organizing data where each variable forms a column, each observation forms a row, and each type of observational unit forms a table.

Other

Tidyverse

Tidyverse is a collection of R packages designed for data science that share an underlying design philosophy and consistent data structures.

Other

TikTok Algorithm

TikTok Algorithm is the set of data-driven rules and processes that determine which videos appear on a user's feed to maximize engagement and relevance.

Machine Learning

Time Series Analysis

Time Series Analysis is a statistical technique used to analyze time-ordered data points to understand underlying patterns and predict future trends.

Data & Analytics

Time Series Database

A Time Series Database is a specialized database optimized for storing, retrieving, and managing time-stamped data points collected sequentially over time.

Reinforcement Learning

Time Step

Time Step is the discrete interval of time used in simulations and computational models to progress the system state incrementally.

Generative AI

TinyML

TinyML is a branch of machine learning focused on running AI models on ultra-low-power, resource-constrained devices like microcontrollers.

Generative AI

Title Generation

Title generation is the process of creating compelling and relevant titles for content that attract both search engines and human readers.

Generative AI

Token Economy

Token economy is a behavioral strategy that uses tokens as a form of currency to reinforce desired actions and encourage positive behavior.

Other

Tokens

Tokens are individual units of text used in natural language processing to represent words, phrases, or characters for computational analysis.

Generative AI

Tone Adjustment

Tone adjustment is the process of modifying the style and emotional quality of communication to match the audience or context.

Computer Vision

Tone Mapping

Tone mapping is a technique used to convert high dynamic range (HDR) images into a format with lower dynamic range suitable for display on standard screens.

Natural Language Processing (NLP)

Top-P Sampling

Top-P Sampling is a stochastic sampling technique used in natural language processing to generate text by selecting from a subset of probable next words based on cumulative probability.

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.