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.

119 terms

AI Fundamentals

Bayesian Network

A Bayesian Network is a graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph.

Machine Learning

Bayesian Optimization

Bayesian Optimization is a probabilistic model-based optimization technique used to find the maximum of an unknown function efficiently.

AI Agents & Systems

BDI Agent

BDI Agent is an intelligent software entity designed to simulate human-like decision-making based on Beliefs, Desires, and Intentions.

Natural Language Processing (NLP)

Beam Search

Beam Search is a heuristic search algorithm that explores a graph by expanding the most promising nodes in a limited set, often used in natural language processing and machine translation.

Data & Analytics

Beats

Beats are the basic units of time or rhythmic pulses in music that create the underlying tempo and groove.

Other

Beauty Tech

Beauty Tech is the integration of technology and innovation into beauty products, services, and experiences to enhance personal care and aesthetics.

Other

Beauty Technology

Beauty technology is the use of advanced devices and digital innovations to enhance skincare, cosmetics, and personal care routines.

Reinforcement Learning

Behavior Cloning

Behavior cloning is a machine learning technique where an agent learns to mimic expert behavior by observing and replicating actions from recorded data.

AI Agents & Systems

Behavior Tree

Behavior Tree is a hierarchical model used to design and control complex decision-making processes in AI, robotics, and game development.

AI Ethics

Beijing Academy of AI Principles

The Beijing Academy of AI Principles is a set of ethical guidelines developed to promote responsible and trustworthy artificial intelligence development and deployment.

AI Agents & Systems

Belief-Desire-Intention

Belief-Desire-Intention (BDI) is a cognitive model used to describe and simulate rational decision-making based on an agent’s beliefs, desires, and intentions.

Reinforcement Learning

Bellman Equation

The Bellman Equation is a fundamental recursive formula used in dynamic programming and reinforcement learning to determine the optimal decision-making strategy by breaking down complex problems into simpler subproblems.

AI Ethics

Beneficence

Beneficence is the ethical principle of doing good and promoting the well-being of others through positive actions.

AI Agents & Systems

Benevolence

Benevolence is the quality of showing kindness and a genuine desire to do good for others without expecting anything in return.

MLOps & Infrastructure

BentoML

BentoML is an open-source platform designed to simplify the deployment, management, and scaling of machine learning models as production-ready APIs.

Deep Learning & Neural Networks

BERT

BERT is a natural language processing model developed by Google that helps computers understand the context of words in search queries.

Other

Bias Reduction

Bias reduction is the process of identifying and minimizing prejudices or systematic errors to ensure fair and accurate outcomes in data analysis, decision-making, or AI models.

Machine Learning

Bias-Variance Tradeoff

Bias-Variance Tradeoff is the balance between the error introduced by the model's assumptions (bias) and the error due to variability in predictions (variance).

Computer Vision

Bicubic Interpolation

Bicubic interpolation is a resampling method that uses cubic polynomials to estimate new pixel values in images, providing smoother and more accurate results than simpler techniques.

Data & Analytics

Big Data

Big Data is the vast volume of structured and unstructured information generated at high velocity from diverse sources, requiring advanced methods to store, process, and analyze it effectively.

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.