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

Data & Analytics

Dark Data

Dark Data is the untapped, unstructured information collected by organizations but not analyzed or used for decision-making.

Data & Analytics

Dashboard

A dashboard is a visual interface that aggregates and displays key data and metrics to help users monitor performance and make informed decisions.

Data & Analytics

Data

Data is raw information collected and stored for analysis, interpretation, and decision-making.

Data & Analytics

Data Accuracy

Data Accuracy is the degree to which data correctly represents the real-world values or facts it is intended to depict.

Data & Analytics

Data Analytics

Data analytics is the process of examining, interpreting, and transforming raw data to uncover meaningful patterns and insights that support informed decision-making.

AI Fundamentals

Data Annotation

Data annotation is the process of labeling data so it can be used to train, test, and evaluate machine learning and AI models.

Data & Analytics

Data Architecture

Data Architecture is the structured design and management framework that defines how data is collected, stored, organized, and used within an organization.

Data & Analytics

Data Audit

Data Audit is a systematic examination and evaluation of an organization's data assets to ensure accuracy, compliance, and usability.

Machine Learning

Data Augmentation

Data Augmentation is a technique used in machine learning to increase the diversity of training data without actually collecting new data.

Other

Data Automation

Data Automation is the process of using technology to automatically collect, process, and manage data without manual intervention.

Data & Analytics

Data Availability

Data Availability is the measure of how accessible and ready data is for use when needed in any system or process.

Data & Analytics

Data Breach

Data breach is an incident where sensitive, confidential, or protected information is accessed or disclosed without authorization.

Data & Analytics

Data Build Tool

Data Build Tool (DBT) is a development framework that enables data analysts and engineers to transform raw data into clean, tested, and documented datasets using SQL.

Data & Analytics

Data Catalog

Data Catalog is an organized inventory of data assets that helps users discover, understand, and manage data efficiently.

Other

Data Cleaning

Data cleaning is the process of identifying and correcting errors or inconsistencies in data to improve its quality and reliability.

Data & Analytics

Data Cleansing

Data cleansing is the process of identifying and correcting errors or inconsistencies in data to improve its quality and reliability.

Data & Analytics

Data Completeness

Data completeness is the extent to which all required data is present, accurate, and available within a dataset for effective analysis and decision-making.

Data & Analytics

Data Consistency

Data Consistency is the assurance that data remains accurate, uniform, and reliable across all systems and platforms at any given time.

Data & Analytics

Data Cube

Data Cube is a multidimensional array of values used to represent and analyze data across multiple dimensions in business intelligence and data warehousing.

Data & Analytics

Data Currency

Data currency is the measure of how up-to-date and relevant data is for accurate decision-making and analysis.

Data & Analytics

Data Dictionary

A data dictionary is a centralized repository that defines and describes the structure, relationships, and metadata of data within a database or information system.

MLOps & Infrastructure

Data Drift

Data drift is the change in the statistical properties of input data over time, causing an AI or machine learning model’s performance to degrade.

Data & Analytics

Data Encryption

Data Encryption is the process of converting information into a coded format to prevent unauthorized access.

Data & Analytics

Data Engineering

Data Engineering is the practice of designing, building, and managing systems that collect, store, and process large volumes of data efficiently.

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.