Lethal Autonomous Weapons
Lethal Autonomous Weapons are military systems capable of selecting and engaging targets without human intervention.
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.
Lethal Autonomous Weapons are military systems capable of selecting and engaging targets without human intervention.
Level design is the process of creating stages or environments in a game that shape the player's experience and challenge.
Levenshtein Distance is a measure of the difference between two strings, quantified by counting the minimum number of single-character edits required to change one string into the other.
License Plate Recognition is an automated technology that identifies and reads vehicle license plates using optical character recognition and image processing.
LiDAR is a remote sensing technology that uses laser light to measure distances and create precise, three-dimensional maps of environments.
A Lift Chart is a graphical representation used to assess the performance of a predictive model by comparing its results against random selection.
LightGBM is a gradient boosting framework that uses tree-based learning algorithms for efficient and scalable machine learning.
Lightness is the perceived brightness or luminance of a color or object, indicating how light or dark it appears to the human eye.
A line chart is a graphical representation that displays information as a series of data points connected by straight lines, typically used to show trends over time.
Linear algebra is a branch of mathematics that deals with vectors, vector spaces, linear transformations, and systems of linear equations.
Linear Discriminant Analysis (LDA) is a statistical method used for dimensionality reduction and classification by finding the linear combination of features that best separate two or more classes.
Linear Regression is a statistical method used to model and analyze the relationships between a dependent variable and one or more independent variables by fitting a linear equation to observed data.
Linestring is a geometric object used in mapping and spatial analysis to represent a sequence of connected points forming a continuous line.
Linformer is a transformer model variant designed to improve computational efficiency by approximating self-attention mechanisms.
Linguistic analytics is the process of analyzing language data to extract meaningful insights about communication patterns, sentiment, and context.
Link Tracking is the process of monitoring and analyzing user clicks on hyperlinks to measure engagement and campaign effectiveness.
Linked Data is a method of publishing structured data so that it can be interlinked and become more useful through semantic queries across the web.
Lip syncing is the process of matching lip movements to a pre-recorded audio track, often used in video production and live performances.
Lip-Sync AI is artificial intelligence technology that automatically synchronizes a speaker’s lip movements with audio or speech.
Lip-sync dubbing is the process of replacing the original audio of a video with a new voiceover that matches the lip movements of the on-screen actors.
Lip-sync technology is a digital method that synchronizes a speaker’s lip movements with audio to create realistic visual speech animation.
Listen, Attend and Spell Short Definition: Listen, Attend and Spell is a neural network model designed for automatic speech recognition tasks.
Litigation analytics is the use of data analysis and visualization tools to assess patterns and outcomes in legal cases for informed decision-making.
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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.