Closed-Loop Control
Closed-loop control is a system that automatically adjusts its actions based on feedback to achieve desired results.
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.
Closed-loop control is a system that automatically adjusts its actions based on feedback to achieve desired results.
Cloud computing is the delivery of computing services over the internet, allowing users to access and store data and applications remotely.
Cloud Cost Optimization is the process of reducing and managing expenses related to cloud computing resources without compromising performance or scalability.
Cloud Data Warehouse is a scalable, cloud-based repository designed to store, manage, and analyze large volumes of structured and semi-structured data for business intelligence and analytics.
Cloud Spend Anomaly Detection is the process of identifying unexpected or unusual patterns in cloud service expenditures to prevent overspending and optimize budgets.
Cloud storage is a service that allows users to save and access data on remote servers via the internet instead of local devices.
Cloud-Native Security is the practice of protecting applications, data, and infrastructure designed specifically for cloud environments using integrated, scalable, and automated security measures.
CloudFormation is an AWS service that enables you to model, provision, and manage cloud infrastructure as code using templates.
Cluster analysis is a statistical method used to group similar objects or data points into clusters based on their characteristics or features.
Cluster computing is a method of linking multiple computers to work together as a single powerful system for improved performance and reliability.
Clustering is a machine learning technique that involves grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other…
Clustering algorithm is a method of grouping data points into clusters based on similarity or distance criteria without predefined labels.
CMOS sensor is a type of image sensor used in digital cameras and devices to convert light into electrical signals for capturing photos and videos.
CMYK is a color model used in printing that combines cyan, magenta, yellow, and black inks to produce a wide range of colors.
CNTK is Microsoft's deep learning framework known as the Cognitive Toolkit.
Co-Creation is a collaborative process where businesses and customers work together to create products, services, or experiences.
Co-reference resolution is a natural language processing task that involves identifying all expressions in a text that refer to the same entity.
Coalition Formation is the process by which individuals or groups come together to achieve a common goal by pooling resources, influence, or power.
A cobot is a collaborative robot designed to work safely alongside humans in shared workspaces, enhancing productivity and efficiency.
COCO Format is a standardized JSON structure used to annotate images for computer vision tasks, especially object detection and segmentation.
Code annotation is the practice of adding explanatory notes or comments within source code to clarify its purpose, logic, or functionality.
Page 51 of 162
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.