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

AI Ethics

Existential Risk

Existential risk is the potential threat that could cause human extinction or permanently and drastically curtail humanity’s future development.

Reinforcement Learning

Expansion

Expansion is the process of growing or increasing the size, scope, or reach of a business, market, or concept.

Reinforcement Learning

Expected SARSA

Expected SARSA is a reinforcement learning algorithm that updates action-value estimates by considering the expected value of all possible next actions under the current policy.

MLOps & Infrastructure

Experiment Tracking

Experiment tracking is the systematic process of recording, monitoring, and managing the details and outcomes of experiments to ensure reproducibility and informed decision-making.

AI Fundamentals

Expert System

An Expert System is a computer program designed to mimic human expertise in specific domains to solve complex problems.

AI Ethics

Explainability

Explainability is the ability to clearly describe how a system, model, or decision-making process works and why it produces specific outcomes.

AI Ethics

Explainable AI

Explainable AI is artificial intelligence designed to provide clear, understandable insights into how it makes decisions or predictions.

Generative AI

Explaining Code

Explaining code is the process of clearly describing how a piece of software or script works, including its logic, functionality, and purpose.

AI Ethics

Explicability

Explicability is the quality of being clear and understandable, especially in explaining complex concepts or decisions.

Machine Learning

Exploding Gradient

Exploding gradient is a problem in neural networks where excessive growth in the error gradients during training leads to large updates and destabilizes learning.

Other

Exploratory Data Analysis

Exploratory Data Analysis is the process of analyzing data sets to summarize their main characteristics, often using visual methods, before formal modeling.

Data & Analytics

Exponential Smoothing

Exponential Smoothing is a time series forecasting technique that applies weighted averages of past observations, giving more importance to recent data.

AI Agents & Systems

Extended Kalman Filter

Extended Kalman Filter is an algorithm that estimates the state of a nonlinear dynamic system by linearizing around the current estimate to provide accurate predictions and corrections.

Data & Analytics

Extract Load Transform

Extract Load Transform (ELT) is a data integration process where data is first extracted, loaded into a target system, and then transformed within that system.

Data & Analytics

Extract Transform Load

Extract Transform Load (ETL) is a data integration process that involves extracting data from various sources, transforming it into a suitable format, and loading it into a target database or data warehouse.

Machine Learning

F1 Score

F1 Score is a metric used to evaluate the accuracy of a model by considering both precision and recall.

Other

Face Alignment

Face alignment is the process of adjusting and positioning facial features in an image to a standardized coordinate system for consistent analysis.

Other

Face Blending

Face blending is a digital technique that combines facial features from two or more images to create a single, seamless composite face.

Computer Vision

Face Detection

Face Detection is a computer technology used to identify and locate human faces in digital images.

Other

Face Embedding

Face embedding is a numerical representation of a person's facial features used for recognition and analysis by AI systems.

Other

Face Embeddings

Face embeddings are numerical vector representations of facial features used to identify and compare faces in machine learning and computer vision.

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.