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

Electroencephalography (EEG)

Electroencephalography (EEG) is a technique that records electrical activity of the brain using sensors placed on the scalp.

AI Agents & Systems

Electronic Institution

Electronic Institution is a structured digital environment designed to regulate multi-agent interactions by defining roles, norms, and protocols to enable coordinated and trustworthy electronic transactions.

Data & Analytics

ELT

ELT is a data integration process that Extracts, Loads, and then Transforms data within a destination system for improved analytics and processing.

Generative AI

Email Generation

Email generation is the automated process of creating personalized email content for marketing, communication, or transactional purposes.

Other

Email Summarization

Email summarization is the process of automatically generating concise summaries of email content to highlight key information quickly.

Other

Email Tracking

Email tracking is the process of monitoring the delivery, opening, and interaction with sent emails to measure engagement and effectiveness.

Other

Embed API

Embed API is a programming interface that allows developers to integrate third-party content or services directly into their websites or applications.

Generative AI

Embedded AI

Embedded AI is artificial intelligence technology integrated directly into hardware devices to enable smart, real-time data processing without relying on cloud connectivity.

Data & Analytics

Embedded Analytics

Embedded Analytics is the integration of business intelligence tools and data analysis capabilities directly within software applications or platforms.

Other

Embedding

Embedding is the process of integrating external content or code into a website or digital platform to enhance functionality or display information seamlessly.

Generative AI

Embeddings

Embeddings are numerical representations of data that capture meaning and relationships so machines can understand and compare information.

AI Agents & Systems

Embodied Agent

An embodied agent is a digital or robotic entity designed to interact with its environment through a physical or virtual presence, combining perception, cognition, and action.

AI Fundamentals

Emergence

Emergence is the process by which complex systems and patterns arise out of a multiplicity of relatively simple interactions.

Other

Emotion AI

Emotion AI is artificial intelligence designed to detect, interpret, and respond to human emotions through data analysis and machine learning.

Other

Emotion Analytics

Emotion analytics is the process of detecting, measuring, and interpreting human emotions through data analysis techniques.

Other

Emotion Detection

Emotion detection is the process of identifying and interpreting human emotions through various data inputs such as facial expressions, voice tone, text, or physiological signals.

Other

Emotion Modeling

Emotion modeling is the process of representing and simulating human emotions within computational systems to enhance interaction and decision-making.

Computer Vision

Emotion Recognition

Emotion Recognition is the process of identifying human emotions from facial expressions, voice tone, or physiological signals.

Other

Emotion Simulation

Emotion simulation is the process of artificially replicating human emotions in machines or digital systems to enhance interaction and decision-making.

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.