Action language is a language for specifying state transition systems, and is commonly used to create formal models of the effects of actions on the world. Action languages are commonly used in the artificial intelligence and robotics domains, where they describe how actions affect the states of systems over time, and may be used for automated planning13.
Action model learning is an area of machine learning concerned with creation and modification of software agents knowledge about effects and preconditions of the actions that can be executed within its environment. This knowledge is usually represented in logic-based action description language and used as the input for automated planners14.
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, «the action selection problem» is typically associated with intelligent agents and animats artificial systems that exhibit complex behaviour in an agent environment15.
Activation function in the context of Artificial Neural Networks, is a function that takes in the weighted sum of all of the inputs from the previous layer and generates an output value to ignite the next layer16.
Active Learning/Active Learning Strategy is a special case of Semi-Supervised Machine Learning in which a learning agent is able to interactively query an oracle (usually, a human annotator) to obtain labels at new data points. A training approach in which the algorithm chooses some of the data it learns from. Active learning is particularly valuable when labeled examples are scarce or expensive to obtain. Instead of blindly seeking a diverse range of labeled examples, an active learning algorithm selectively seeks the particular range of examples it needs for learning17,18,19.
Adam optimization algorithm it is an extension of stochastic gradient descent which has recently gained wide acceptance for deep learning applications in computer vision and natural language processing20.
Adaptive algorithm is an algorithm that changes its behavior at the time it is run, based on a priori defined reward mechanism or criterion21,22.
Adaptive Gradient Algorithm (AdaGrad) is a sophisticated gradient descent algorithm that rescales the gradients of each parameter, effectively giving each parameter an independent learning rate23.
Adaptive neuro fuzzy inference system (ANFIS) (also adaptive network-based fuzzy inference system) is a kind of artificial neural network that is based on TakagiSugeno fuzzy inference system. The technique was developed in the early 1990s. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework. Its inference system corresponds to a set of fuzzy IFTHEN rules that have learning capability to approximate nonlinear functions. Hence, ANFIS is considered to be a universal estimator. For using the ANFIS in a more efficient and optimal way, one can use the best parameters obtained by genetic algorithm24.
Adaptive system is a system that automatically changes the data of its functioning algorithm and (sometimes) its structure in order to maintain or achieve an optimal state when external conditions change25.
Additive technologies are technologies for the layer-by-layer creation of three-dimensional objects based on their digital models («twins»), which make it possible to manufacture products of complex geometric shapes and profiles26.
Admissible heuristic in computer science, specifically in algorithms related to pathfinding, a heuristic function is said to be admissible if it never overestimates the cost of reaching the goal, i.e., the cost it estimates to reach the goal is not higher than the lowest possible cost from the current point in the path27.
Affective computing (also artificial emotional intelligence or emotion AI) the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. Affective computing is an interdisciplinary field spanning computer science, psychology, and cognitive science28.
Agent architecture is a blueprint for software agents and intelligent control systems, depicting the arrangement of components. The architectures implemented by intelligent agents are referred to as cognitive architectures29.
Agent in reinforcement learning, is the entity that uses a policy to maximize expected return gained from transitioning between states of the environment30.
Agglomerative clustering (see hierarchical clustering) is one of the clustering algorithms, first assigns every example to its own cluster, and iteratively merges the closest clusters to create a hierarchical tree31.
Aggregate is a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc., that comprise the county. To total data from smaller units into a large unit32.
Aggregator is a type of software that brings together various types of Web content and provides it in an easily accessible list. Feed aggregators collect things like online articles from newspapers or digital publications, blog postings, videos, podcasts, etc. A feed aggregator is also known as a news aggregator, feed reader, content aggregator or an RSS reader33.
AI acceleration acceleration of calculations encountered with AI, specialized AI hardware accelerators are allocated for this purpose (see also artificial intelligence accelerator, hardware acceleration)34.
AI acceleration is the acceleration of AI-related computations, for this purpose specialized AI hardware accelerators are used35.
AI accelerator is a class of microprocessor or computer system designed as hardware acceleration for artificial intelligence applications, especially artificial neural networks, machine vision, and machine learning36.
AI accelerator is a specialized chip that improves the speed and efficiency of training and testing neural networks. However, for semiconductor chips, including most AI accelerators, there is a theoretical minimum power consumption limit. Reducing consumption is possible only with the transition to optical neural networks and optical accelerators for them37.
AI benchmark is an AI benchmark for evaluating the capabilities, efficiency, performance and for comparing ANNs, machine learning (ML) models, architectures and algorithms when solving various AI problems, special benchmarks are created and standardized, initial marks. For example, Benchmarking Graph Neural Networks benchmarking (benchmarking) of graph neural networks (GNS, GNN) usually includes installing a specific benchmark, loading initial datasets, testing ANNs, adding a new dataset and repeating iterations.
AI benchmark is benchmarking of AI systems, to assess the capabilities, efficiency, performance and to compare ANNs, machine learning (ML) models, architectures and algorithms when solving various AI problems, special benchmark tests are created and standardized, benchmarks. For example, Benchmarking Graph Neural Networks benchmarking (benchmarking) of graph neural networks (GNS, GNN) usually includes installing a specific benchmark, loading initial datasets, testing ANNs, adding a new dataset and repeating iterations (see also artificial neural network benchmarks).
AI Building and Training Kits applications and software development kits (SDKs) that abstract platforms, frameworks, analytics libraries, and data analysis appliances, allowing software developers to incorporate AI into new or existing applications.
AI camera is a camera with artificial intelligence, digital cameras of a new generation allow you to analyze images by recognizing faces, their expression, object contours, textures, gradients, lighting patterns, which is taken into account when processing images; some AI cameras are capable of taking pictures on their own, without human intervention, at moments that the camera finds most interesting, etc. (see also camera, software-defined camera).
AI chipset is a chipset for systems with AI, for example, AI chipset industry is an industry of chipsets for systems with AI, AI chipset market is a market for chipsets for systems with AI.
AI chipset market chipset market for systems with artificial intelligence (AI), see also AI chipset.
AI chipset market is the market for chipsets for artificial intelligence (AI) systems.
AI cloud services AI model building tools, APIs, and associated middleware that enable you to build/train, deploy, and consume machine learning models that run on a prebuilt infrastructure as cloud services. These services include automated machine learning, machine vision services, and language analysis services.
AI CPU is a central processing unit for AI tasks, synonymous with AI processor.
AI engineer AI systems engineer.
AI engineering transfer of AI technologies from the level of R&D, experiments and prototypes to the engineering and technical level, with the expanded implementation of AI methods and tools in IT systems to solve real production problems of a company, organization. One of the strategic technological trends (trends) that can radically affect the state of the economy, production, finance, the state of the environment and, in general, the quality of life of a person and humanity.
AI hardware (also AI-enabled hardware) artificial intelligence infrastructure system hardware, AI infrastructure. Explanations in the Glossary are usually brief.
AI hardware is infrastructure hardware or artificial intelligence system, AI infrastructure.
AI industry for example, commercial AI industry commercial AI industry, commercial sector of the AI industry.
AI industry trends are promising directions for the development of the AI industry.
AI infrastructure (also AI-defined infrastructure, AI-enabled Infrastructure) artificial intelligence infrastructure systems, for example, AI infrastructure research research in the field of AI infrastructures (see also AI, AI hardware).
AI server (artificial intelligence server) is a server with (based on) AI; a server that provides solving AI problems.
AI shopper is a non-human economic entity that receives goods or services in exchange for payment. Examples include virtual personal assistants, smart appliances, connected cars, and IoT-enabled factory equipment. These AIs act on behalf of a human or organization client.
AI supercomputer is a supercomputer for artificial intelligence tasks, a supercomputer for AI, characterized by a focus on working with large amounts of data (see also artificial intelligence, supercomputer).
AI term is a term from the field of AI (from terminology, AI vocabulary), for example, in AI terms in terms of AI (in AI language) (see also AI terminology).
AI term is a term from the field of AI (from terminology, AI vocabulary), for example, in AI terms in terms of AI (in AI language).
AI terminology (artificial intelligence terminology) is a set of special terms related to the field of AI (see also AI term).
AI terminology is the terminology of artificial intelligence, a set of technical terms related to the field of AI.
AI TRiSM is the management of an AI model to ensure trust, fairness, efficiency, security, and data protection38.
AI vendor is a supplier of AI tools (systems, solutions).
AI vendor is a supplier of AI tools (systems, solutions).
AI winter (Winter of artificial intelligence) is a period of reduced interest in the subject area, reduced research funding. The term was coined by analogy with the idea of nuclear winter. The field of artificial intelligence has gone through several cycles of hype, followed by disappointment and criticism, followed by a strong cooling off of interest, and then followed by renewed interest years or decades later39,40.
AI workstation is a workstation (PC) with (based on) AI; AI RS, a specialized computer for solving technical or scientific problems, AI tasks; usually connected to a LAN with multi-user operating systems, intended primarily for the individual work of one specialist.
AI workstation is a workstation (PC) with means (based on) AI; AI PC, a specialized desktop PC for solving technical or scientific problems, AI tasks; usually connected to a LAN with multi-user operating systems, intended primarily for the individual work of one specialist.
AI-based management system the process of creating policies, allocating decision-making rights and ensuring organizational responsibility for risk and investment decisions for an application, as well as using artificial intelligence methods.
AI-based systems are information processing technologies that include models and algorithms that provide the ability to learn and perform cognitive tasks, with results in the form of predictive assessment and decision making in a material and virtual environment. AI systems are designed to work with some degree of autonomy through modeling and representation of knowledge, as well as the use of data and the calculation of correlations. AI-based systems can use various methodologies, in particular: machine learning, including deep learning and reinforcement learning; automated reasoning, including planning, dispatching, knowledge representation and reasoning, search and optimization. AI-based systems can be used in cyber-physical systems, including equipment control systems via the Internet, robotic equipment, social robotics and human-machine interface systems that combine the functions of control, recognition, processing of data collected by sensors, as well as the operation of actuators in the environment of functioning of AI systems41.
AI-complete. In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is equivalent to that of solving the central artificial intelligence problem making computers as intelligent as people, or strong AI. To call a problem AI-complete reflects an attitude that it would not be solved by a simple specific algorithm42.
AI-enabled using AI and equipped with AI, for example, AI-enabled tools tools with AI (see also AI-enabled device).
AI-enabled device is a device supported by an artificial intelligence (AI) system, such as an intelligent robot.
AI-enabled device is a device supported by an artificial intelligence (AI) system, such as an intelligent robot (see also AI-enabled healthcare device)43.
AI-enabled healthcare device is an AI-enabled device for healthcare (medical care), see also AI-enabled device.
AI-enabled healthcare device is an AI-enabled healthcare device44.
AI-enabled is hardware or software that uses AI-enabled AI, such as AI-enabled tools.