Area under curve (AUC) (Площадь под кривой) The area under a curve between two points is calculated by performing the definite integral. In the context of a receiver operating characteristic for a binary classifier, the AUC represents the classifiers accuracy [46].
Area Under the ROC curve (Площадь под кривой ROC) is the probability that a classifier will be more confident that a randomly chosen positive example is actually positive than that a randomly chosen negative example is positive.
Argumentation framework (Структура аргументации или система аргументации) A way to deal with contentious information and draw conclusions from it. In an abstract argumentation framework, entry-level information is a set of abstract arguments that, for instance, represent data or a proposition. Conflicts between arguments are represented by a binary relation on the set of arguments. []
Artifact Artifact is one of many kinds of tangible by-products produced during the development of software. Some artifacts (e.g., use cases, class diagrams, and other Unified Modeling Language (UML) models, requirements and design documents) help describe the function, architecture, and design of software. Other artifacts are concerned with the process of development itself such as project plans, business cases, and risk assessments. [47]
Artificial General Intelligence (AGI) (Общий Искусственный Интеллект) is a hypothetical type of AI that is completely analogous to the human mind and has self-awareness that can solve problems, learn and plan for the future.
Artificial Intelligence (AI) (Искусственный интеллект) (machine intelligence) refers to systems that display intelligent behavior by analyzing their environment and taking actions with some degree of autonomy to achieve specific goals. AI-based systems can be purely software-based, acting in the virtual world (e.g., voice assistants, image analysis software, search engines, speech and face recognition systems) or AI can be embedded in hardware devices (e.g., advanced robots, autonomous cars, drones, or Internet of Things applications). The term AI was first coined by John McCarthy in 1956. [48]
Artificial Intelligence Automation Platforms (Платформы автоматизации искусственного интеллекта) Platforms that enable the automation and scaling of production-ready AI. Artificial Intelligence Platforms involves the use of machines to perform the tasks that are performed by human beings. The platforms simulate the cognitive function that human minds perform such as problem-solving, learning, reasoning, social intelligence as well as general intelligence. Top Artificial Intelligence Platforms: Google AI Platform, TensorFlow, Microsoft Azure, Rainbird, Infosys Nia, Wipro HOLMES, Dialogflow, Premonition, Ayasdi, MindMeld, Meya, KAI, Vital A.I, Wit, Receptiviti, Watson Studio, Lumiata, Infrrd. [49].
Artificial intelligence engine (also AI engine, AIE) (Движок искусственного интеллекта) is an artificial intelligence engine, a hardware and software solution for increasing the speed and efficiency of artificial intelligence system tools.
Artificial Intelligence for IT Operations (AIOps) is an emerging IT practice that applies artificial intelligence to IT operations to help organizations intelligently manage infrastructure, networks, and applications for performance, resilience, capacity, uptime, and, in some cases, security. By shifting traditional, threshold-based alerts and manual processes to systems that take advantage of AI and machine learning, AIOps enables organizations to better monitor IT assets and anticipate negative incidents and impacts before they take hold. AIOps is a term coined by Gartner in 2016 as an industry category for machine learning analytics technology that enhances IT operations analytics covering operational tasks include automation, performance monitoring and event correlations, among others. Gartner define an AIOps Platform thus: An AIOps platform combines big data and machine learning functionality to support all primary IT operations functions through the scalable ingestion and analysis of the ever-increasing volume, variety and velocity of data generated by IT. The platform enables the concurrent use of multiple data sources, data collection methods, and analytical and presentation technologies. [50,51].
Artificial Intelligence Markup Language AIML (Язык разметки искусственного интеллекта) An XML dialect for creating natural language software agents [52]
Artificial Intelligence Open Library (Открытая библиотека искусственного интеллекта) is a set of algorithms designed to develop technological solutions based on artificial intelligence, described using programming languages and posted on the Internet.
Artificial intelligence system (AIS, Система искусственного интеллекта) is a programmed or digital mathematical model (implemented using computer computing systems) of human intellectual capabilities, the main purpose of which is to search, analyze and synthesize large amounts of data from the world around us in order to obtain new knowledge about it and solve them. basis of various vital tasks. The discipline Artificial Intelligence Systems includes consideration of the main issues of modern theory and practice of building intelligent systems.
Artificial intelligence technologies (Технологии искусственного интеллекта) technologies based on the use of artificial intelligence, including computer vision, natural language processing, speech recognition and synthesis, intelligent decision support and advanced methods of artificial intelligence.
Artificial life (Alife, A-Life, Искусственная жизнь) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American theoretical biologist, in 1986. [2] In 1987 Langton organized the first conference on the field, in Los Alamos, New Mexico. There are three main kinds of alife, named for their approaches: soft, from software; hard, from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena [53].
Artificial Narrow Intelligence (ANI) (Узкий искусственный интеллект) Artificial Narrow Intelligence, also known as weak or applied intelligence, represents most of the current artificial intelligent systems which usually focus on a specific task. Narrow AIs are mostly much better than humans at the task they were made for: for example, look at face recognition, chess computers, calculus, and translation. The definition of artificial narrow intelligence is in contrast to that of strong AI or artificial general intelligence, which aims at providing a system with consciousness or the ability to solve any problems. Virtual assistants and AlphaGo are examples of artificial narrow intelligence systems [54,55].
Artificial Neural Network (ANN) (Искусственная нейронная сеть) is a computational model in machine learning, which is inspired by the biological structures and functions of the mammalian brain. Such a model consists of multiple units called artificial neurons which build connections between each other to pass information. The advantage of such a model is that it progressively learns the tasks from the given data without specific programing for a single task.
Artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. The difference between an artificial neuron and a biological neuron is shown in the figure.
Artificial neurons are the elementary units of an artificial neural network. An artificial neuron receives one or more inputs (representing excitatory postsynaptic potentials and inhibitory postsynaptic potentials on nerve dendrites) and sums them to produce an output signal (or activation, representing the action potential of the neuron that is transmitted down its axon). Typically, each input is weighted separately, and the sum is passed through a non-linear function known as an activation function or transfer function. Transfer functions are usually sigmoid, but they can also take the form of other non-linear functions, piecewise linear functions, or step functions. They are also often monotonically increasing, continuous, differentiable, and bounded [56,57].
Artificial Superintelligence (ASI) (Искусственный сверхинтеллект) is a term referring to the time when the capability of computers will surpass humans. Artificial intelligence, which has been much used since the 1970s, refers to the ability of computers to mimic human thought. Artificial superintelligence goes a step beyond and posits a world in which a computers cognitive ability is superior to a human.
Assistive intelligence (Вспомогательный интеллект) is AI-based systems that help make decisions or perform actions.
Association (Ассоциация) is another type of unsupervised learning method that uses different rules to find relationships between variables in a given dataset. These methods are frequently used for market basket analysis and recommendation engines, along the lines of Customers Who Bought This Item Also Bought recommendations.
Association for the Advancement of Artificial Intelligence (AAAI) (Ассоциация по развитию искусственного интеллекта) An international, nonprofit, scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artificial intelligence (AI), improve the teaching and training of AI practitioners, and provide guidance for research planners and funders concerning the importance and potential of current AI developments and future directions
Association Rule Learning (Правила обучения ассоциации) A rule-based Machine Learning method for discovering interesting relations between variables in large data sets.
Asymptotic computational complexity (Асимптотическая вычислительная сложность) In computational complexity theory, asymptotic computational complexity is the usage of asymptotic analysis for the estimation of computational complexity of algorithms and computational problems, commonly associated with the usage of the big O notation [58].
Asynchronous inter-chip protocols (Асинхронные межкристальные протоколы) are protocols for data exchange in low-speed devices; instead of frames, individual characters are used to control the exchange of data.
Attention mechanism (Механизм внимания) is one of the key innovations in the field of neural machine translation. Attention allowed neural machine translation models to outperform classical machine translation systems based on phrase translation. The main bottleneck in sequence-to-sequence learning is that the entire content of the original sequence needs to be compressed into a vector of a fixed size. The attention mechanism facilitates this task by allowing the decoder to look back at the hidden states of the original sequence, which are then provided as a weighted average as additional input to the decoder.
Attributional calculus (AC) (Атрибутивное исчисление) A logic and representation system defined by Ryszard S. Michalski. It combines elements of predicate logic, propositional calculus, and multi-valued logic. Attributional calculus provides a formal language for natural induction, an inductive learning process whose results are in forms natural to people [59].
Augmented Intelligence (Дополненный (расширенный) интеллект) is the intersection of machine learning and advanced applications, where clinical knowledge and medical data converge on a single platform. The potential benefits of Augmented Intelligence are realized when it is used in the context of workflows and systems that healthcare practitioners operate and interact with. Unlike Artificial Intelligence, which tries to replicate human intelligence, Augmented Intelligence works with and amplifies human intelligence [60]
Augmented reality (AR) (Дополненная реальность) An interactive experience of a real-world environment where the objects that reside in the real-world are augmented by computer-generated perceptual information, sometimes across multiple sensory modalities, including visual, auditory, haptic, somatosensory, and olfactory.
Augmented reality technologies (Технологии дополненной реальности) are visualization technologies based on adding information or visual effects to the physical world by overlaying graphic and/or sound content to improve user experience and interactive features.
Auto Associative Memory (Автоассоциативная память) is a single layer neural network in which the input training vector and the output target vectors are the same. The weights are determined so that the network stores a set of patterns. As shown in the following figure, the architecture of Auto Associative memory network has n number of input training vectors and similar n number of output target vectors [61].
Autoencoder (Автокодер) а type of Artificial Neural Network used to produce efficient representations of data in an unsupervised and non-linear manner, typically to reduce dimensionality [62].
Automata theory (Теория автоматов) The study of abstract machines and automata, as well as the computational problems that can be solved using them. It is a theory in theoretical computer science and discrete mathematics (a subject of study in both mathematics and computer science). [63] Automata theory (part of the theory of computation) is a theoretical branch of Computer Science and Mathematics, which mainly deals with the logic of computation with respect to simple machines, referred to as automata [64].