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

Deep Learning & Neural Networks

ReLU

ReLU is an activation function in neural networks that outputs the input directly if it is positive, otherwise, it outputs zero.

Generative AI

Remixing

Remixing is the process of creatively adapting or combining existing content to produce a new, original work.

Other

Remote Exam Monitoring

Remote Exam Monitoring is the use of technology to oversee and ensure the integrity of exams taken outside traditional testing centers.

Computer Vision

Remote Sensing

Remote sensing is the process of collecting information about an object or area from a distance, typically using satellites or aircraft.

Computer Vision

Rendering

Rendering is the process of generating a visual representation from a model or script, often used to produce images, animations, or videos.

Generative AI

Repetition Penalty

Repetition penalty is a mechanism used in language models and content generation to reduce the likelihood of repeating the same words or phrases excessively.

Generative AI

Report Generation

Report Generation is the automated or manual process of compiling data into organized, readable documents that summarize information for analysis, decision-making, or communication.

MLOps & Infrastructure

Reproducibility

Reproducibility is the ability to consistently duplicate the results of an experiment or process using the same methods and conditions.

Other

Research Paper Summarization

Research paper summarization is the process of condensing a research article into a concise and clear overview that highlights its key points and findings.

Generative AI

Reskilling

Reskilling is the process of learning new skills to adapt to changes in job requirements or career shifts.

Other

Resolution Upscaling

Resolution upscaling is the process of increasing the pixel count of an image or video to enhance its display quality on higher-resolution screens.

MLOps & Infrastructure

Resource Management

Resource Management is the process of efficiently allocating and utilizing an organization's assets, including people, finances, and materials, to achieve project or business goals.

AI Ethics

Responsible AI

Responsible AI is the practice of designing, developing, and deploying artificial intelligence systems that are ethical, transparent, and accountable.

AI Agents & Systems

REST

REST is an architectural style for designing networked applications that use stateless communication and standard HTTP methods.

MLOps & Infrastructure

REST API

REST API is a set of web standards and protocols that allow different software applications to communicate with each other using HTTP requests.

Other

Resume Parsing

Resume parsing is the automated process of extracting and organizing information from resumes into structured data formats.

Data & Analytics

Retention Analysis

Retention analysis is the process of measuring and understanding how well a business keeps its customers or users over time.

Deep Learning & Neural Networks

RetinaNet

RetinaNet is a deep learning model designed for object detection tasks, known for its ability to handle the class imbalance problem effectively using a focal loss function.

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.