Access to information (Доступ к информации) the ability to obtain information and use it.
Access to information constituting a commercial secret (Доступ к информации, составляющей коммерческую тайну) familiarization of certain persons with information constituting a commercial secret, with the consent of its owner or on other legal grounds, provided that this information is kept confidential.
Accuracy (Точность) The fraction of predictions that a classification model got right.
Action (Действие) In reinforcement learning, the mechanism by which the agent transitions between states of the environment. The agent chooses the action by using a policy.
Action language (Язык действий) 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 planning [18].
Action model learning (Обучение модели действий) 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 planners [19].
Action selection (Выбор действия) 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 environment [20].
Activation function (Функция активации нейрона) In the context of Artificial Neural Networks, 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 layer [21].
Active Learning/Active Learning Strategy (Активное обучение/ Стратегия активного обучения) 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 learning.
Adam optimization algorithm (Алгоритм оптимизации Адам) it is an extension of stochastic gradient descent which has recently gained wide acceptance for deep learning applications in computer vision and natural language processing [22].
Adaptive algorithm (Адаптивный алгоритм) An algorithm that changes its behavior at the time it is run, based on a priori defined reward mechanism or criterion [23].
Adaptive Gradient Algorithm (AdaGrad) (АдаптивныйAdaptive Gradient Algorithm (AdaGrad) ( A sophisticated gradient descent algorithm that rescales the gradients of each parameter, effectively giving each parameter an independent learning rate [24].
Adaptive neuro fuzzy inference system (ANFIS) (Also adaptive network-based fuzzy inference system.) (Адаптивная система нейро-нечеткого вывода) A kind of artificial neural network that is based on Takagi Sugeno 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 IF THEN 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 algorithm [25].
Adaptive system (Адаптивная система) 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 change.
Additive technologies (Аддитивные технологии) 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 profiles.
Admissible heuristic (Допустимая эвристика) 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 path.
Affective computing (Also artificial emotional intelligence or emotion AI.) (Аффективные вычисления) 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 science [26].
Agent (Агент) In reinforcement learning, the entity that uses a policy to maximize expected return gained from transitioning between states of the environment.
Agent architecture (Архитектура агента) 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 architectures [27].
Agglomerative clustering (See hierarchical clustering.) (Агломеративная кластеризация) Agglomerative clustering first assigns every example to its own cluster, and iteratively merges the closest clusters to create a hierarchical tree.
Aggregate (Агрегат) 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 unit. [28]
Aggregator (Агрегатор) A feed 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 reader. [29]
AI benchmark (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 chipset market (AI chipset market is the market for chipsets for artificial intelligence (AI) systems.
AI acceleration (ИИ ускорение) acceleration of calculations encountered with AI, specialized AI hardware accelerators are allocated for this purpose (see also artificial intelligence accelerator, hardware acceleration).
AI acceleration (AI acceleration is the acceleration of AI-related computations, for this purpose specialized AI hardware accelerators are used.
AI accelerator (ИИ ускоритель) A class of microprocessor or computer system designed as hardware acceleration for artificial intelligence applications, especially artificial neural networks, machine vision, and machine learning.
AI benchmark (ИИ бенчмарк) 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 (Комплекты для создания и обучения искусственного интеллекта) 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 (ИИ камера) 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 (ИИ чипсет) 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 (ИИ рыное чипов) chipset market for systems with artificial intelligence (AI), see also AI chipset.
AI cloud services (Облачные сервисы искусственного интеллекта) 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 (Центральный процессор ИИ) is a central processing unit for AI tasks, synonymous with AI processor.
AI engineer (ИИ-инженер) AI systems engineer.
AI engineering (ИИ-инжиниринг) 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 AI hardware) AI hardware, AI hardware, artificial intelligence infrastructure [system] hardware, AI infrastructure. Explanations in the Glossary are usually brief
AI hardware (Аппаратное обеспечение ИИ) is infrastructure hardware or artificial intelligence system, AI infrastructure.
AI industry (Индустрия ИИ) for example, commercial AI industry commercial AI industry, commercial sector of the AI industry.
AI industry trends (AI industry trends are promising directions for the development of the AI industry.
AI infrastructure AI infrastructure artificial intelligence infrastructure [systems], AI infrastructure, AI infrastructure, for example, AI infrastructure research research in the field of AI infrastructures (see also AI, AI hardware).
AI server (ИИ сервер) artificial intelligence server is a server with (based on) AI; a server that provides solving AI problems.
AI shopper (ИИ-покупатель) 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 (ИИ суперкомпьютер) 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 (ИИ термин) a term from the field of AI (from terminology, AI vocabulary), for example, in AI terms in terms of AI (in AI language).
AI term (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 (AI terminology) artificial intelligence terminology, is a set of special terms related to the field of AI (see also AI term).
AI terminology (AI terminology is the terminology of artificial intelligence, a set of technical terms related to the field of AI.
AI TRiSM (Управление доверием, рисками и безопасностью ИИ) is the management of an AI model to ensure trust, fairness, efficiency, security, and data protection.
AI vendor (ИИ вендор) is a supplier of AI tools (systems, solutions).
AI vendor (AI vendor is a supplier of AI tools (systems, solutions).
AI winter (Winter of artificial intelligence, Зима искусственного интеллекта) 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 later [30].