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

Audio Features

Audio features are measurable attributes of sound recordings that describe characteristics like tempo, pitch, and timbre to help analyze and classify audio content.

Generative AI

Audio Generation

Audio Generation is the process of creating sound waves or audio content using digital technologies, often powered by artificial intelligence or software tools.

Other

Audio Integration

Audio Integration is the process of incorporating sound elements into digital platforms, applications, or devices to enhance user experience and functionality.

Other

Audio Stem Separation

Audio stem separation is the process of isolating individual sound elements, such as vocals, drums, or instruments, from a mixed audio track into separate audio files called stems.

Other

Audio Synthesis

Audio synthesis is the process of generating sound electronically by manipulating waveforms and acoustic parameters.

Generative AI

Audio-to-Text

Audio-to-Text is the process of converting spoken language in audio files into written text through transcription technology.

Generative AI

AudioLDM

AudioLDM is a cutting-edge text-to-audio generation model that converts written descriptions into high-quality soundscapes and audio clips.

AI Ethics

Auditing

Auditing is the systematic examination and evaluation of an organization's processes, systems, or financial records to ensure accuracy, compliance, and effectiveness.

Computer Vision

Augmented Reality

Augmented Reality is a technology that overlays digital information and media onto the real world through devices like smartphones and AR glasses.

Other

Augmented Writing

Augmented Writing is the use of AI-powered tools to enhance and improve the writing process by providing real-time suggestions, content optimization, and language refinement.

Other

Auto captioning

Auto captioning is the automated process of generating text captions for audio or video content using speech recognition technology.

MLOps & Infrastructure

Auto-Scaling

Auto-scaling is an automated process that adjusts computing resources dynamically based on demand to maintain optimal performance and cost efficiency.

Other

Automated Essay Scoring

Automated Essay Scoring is a technology that uses computer algorithms to evaluate and grade written essays objectively and efficiently.

Other

Automated Grading

Automated grading is the use of computer algorithms and software to evaluate and score assessments without human intervention.

Other

Automated Labeling

Automated labeling is the process of using software or algorithms to assign descriptive tags or categories to data without manual input.

Other

Automated Machine Learning

Automated Machine Learning is the process of using software to automate the tasks involved in building and deploying machine learning models.

Other

Automated Remediation

Automated Remediation is the process of using software tools to detect and fix security or operational issues without manual intervention.

Other

Automated scoring

Automated scoring is the use of computer algorithms to evaluate and assign scores to responses or performances without human intervention.

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.

Read more Read less

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.