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

Real-Time Transcription

Real-time transcription is the instant conversion of spoken language into written text as the speech occurs.

Other

Real-Time Translation

Real-Time Translation is the instant conversion of spoken or written language from one language to another as communication occurs.

AI Fundamentals

Reasoning

Reasoning is an AI capability that enables a system to analyze information, draw logical conclusions, and make decisions based on relationships, rules, or evidence.

Machine Learning

Recall

Recall is the process of retrieving information from memory when needed.

Natural Language Processing (NLP)

Recall at K

Recall at K is a metric used to evaluate the effectiveness of an information retrieval system by measuring the proportion of relevant items retrieved within the top K results.

Other

Receipt Scanning

Receipt scanning is the digital process of capturing and extracting information from paper or electronic receipts using specialized software or apps.

Computer Vision

Receptive Field

Receptive field is the specific region or area of input data that a neuron or unit in a neural network processes or responds to.

Other

Recipe Generation

Recipe generation is the process of automatically creating cooking instructions and ingredient lists using algorithms or AI technology.

Other

Recipe Generator

A Recipe Generator is a software tool that automatically creates cooking recipes based on user inputs or predefined criteria.

Other

Recipe Integration

Recipe integration is the process of embedding structured recipe data into web content to enhance search engine visibility and improve user experience.

Other

Recipe Recommendation

Recipe recommendation is a personalized suggestion system that helps users discover recipes tailored to their preferences, dietary needs, and cooking skills.

Other

Recommendation Engine

A Recommendation Engine is a software system that analyzes data to suggest relevant products, content, or information to users based on their preferences and behavior.

Data & Analytics

Recommendation System

A recommendation system is an AI-driven system that suggests relevant content, products, or actions to users based on data, behavior, and preferences.

Other

Recommender System

Recommender System is a technology that suggests products, services, or content to users based on their preferences, behaviors, or similarities to others.

Data & Analytics

Record Linkage

Record linkage is the process of identifying and merging records that refer to the same entity across different data sources.

Other

Recruitment Automation

Recruitment automation is the use of software and technology to streamline and optimize the hiring process by automating repetitive tasks.

Generative AI

Recursive Reward Modeling

Recursive Reward Modeling is a method of training AI systems by breaking down complex tasks into simpler subtasks, using human feedback recursively to guide the AI’s learning process.

Generative AI

Red Teaming

Red Teaming is a strategic approach where a group simulates adversarial attacks to identify vulnerabilities and improve an organization’s security or decision-making processes.

Data & Analytics

Redis

Redis is an open-source, in-memory data structure store used as a database, cache, and message broker.

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.