Александр Николаевич Власкин
Глоссариум по искусственному интеллекту: 2500 терминов. Том 2
Algorithm – an exact prescription for the execution in a certain order of a system of operations for solving any problem from some given class (set) of problems. The term «algorithm» comes from the name of the Uzbek mathematician Musa Al-Khorezmi, who in the 9th century proposed the simplest arithmetic algorithms. In mathematics and cybernetics, a class of problems of a certain type is considered solved when an algorithm is established to solve it. Finding algorithms is a natural human goal in solving various classes of problems46.
Algorithmic Assessment is a technical evaluation that helps identify and address potential risks and unintended consequences of AI systems across your business, to engender trust and build supportive systems around AI decision making47.
AlphaGo is the first computer program that defeated a professional player on the board game Go in October 2015. Later in October 2017, AlphaGo’s team released its new version named AlphaGo Zero which is stronger than any previous human-champion defeating versions. Go is played on 19 by 19 board which allows for 10171 possible layouts (chess 1050 configurations). It is estimated that there are 1080 atoms in the universe48.
Physical media is the physical material that is used to store or transmit information in a data transmission49.
Ambient intelligence (AmI) represents the future vision of intelligent computing where explicit input and output devices will not be required; instead, sensors and processors will be embedded into everyday devices and the environment will adapt to the user’s needs and desires seamlessly. AmI systems, will use the contextual information gathered through these embedded sensors and apply Artificial Intelligence (AI) techniques to interpret and anticipate the users’ needs. The technology will be designed to be human centric and easy to use50.
Analogical Reasoning – solving problems by using analogies, by comparing to past experiences51.
Analysis of algorithms (AofA) – the determination of the computational complexity of algorithms, that is the amount of time, storage and/or other resources necessary to execute them. Usually, this involves determining a function that relates the length of an algorithm’s input to the number of steps it takes (its time complexity) or the number of storage locations it uses (its space complexity)52.
Annotation is a metadatum attached to a piece of data, typically provided by a human annotator53.
Anokhin’s theory of functional systems is a functional system consists of a certain number of nodal mechanisms, each of which takes its place and has a certain specific purpose. The first of these is afferent synthesis, in which four obligatory components are distinguished: dominant motivation, situational and triggering afferentation, and memory. The interaction of these components leads to the decision-making process54.
Anomaly detection – the process of identifying outliers. For example, if the mean for a certain feature is 100 with a standard deviation of 10, then anomaly detection should flag a value of 200 as suspicious55,56.
Anonymization – the process in which data is de-identified as part of a mechanism to submit data for machine learning57.
Answer set programming (ASP) is a form of declarative programming oriented towards difficult (primarily NP-hard) search problems. It is based on the stable model (answer set) semantics of logic programming. In ASP, search problems are reduced to computing stable models, and answer set solvers – programs for generating stable models – are used to perform search58.
Antivirus software is a program or set of programs that are designed to prevent, search for, detect, and remove software viruses, and other malicious software like worms, trojans, adware, and more59.
Anytime algorithm is an algorithm that can return a valid solution to a problem even if it is interrupted before it ends60.
API-AS-a-service (AaaS) combines the API economy and software renting and provides application programming interfaces as a service61.
Application programming interface (API) is a set of subroutine definitions, communication protocols, and tools for building software. In general terms, it is a set of clearly defined methods of communication among various components. A good API makes it easier to develop a computer program by providing all the building blocks, which are then put together by the programmer. An API may be for a web-based system, operating system, database system, computer hardware, or software library62.
Application security is the process of making apps more secure by finding, fixing, and enhancing the security of apps. Much of this happens during the development phase, but it includes tools and methods to protect apps once they are deployed. This is becoming more important as hackers increasingly target applications with their attacks63.
Application-specific integrated circuit (ASIC) is a specialized integrated circuit for solving a specific problem64.
Approximate string matching (also fuzzy string searching) – the technique of finding strings that match a pattern approximately (rather than exactly). The problem of approximate string matching is typically divided into two sub-problems: finding approximate substring matches inside a given string and finding dictionary strings that match the pattern approximately65.
Approximation error – the discrepancy between an exact value and some approximation to it66.
Architectural description group (Architectural view) is a representation of the system as a whole in terms of a related set of interests67,68.
Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution69.
Architecture of a computer is a conceptual structure of a computer that determines the processing of information and includes methods for converting information into data and the principles of interaction between hardware and software70.
Architecture of a computing system is the configuration, composition and principles of interaction (including data exchange) of the elements of a computing system71.
Architecture of a system is the fundamental organization of a system, embodied in its elements, their relationships with each other and with the environment, as well as the principles that guide its design and evolution72.
Archival Information Collection (AIC) is information whose content is an aggregation of other archive information packages. The digital preservation function preserves the capability to regenerate the DIPs (Dissemination Information Packages) as needed over time73.
Archival Storage is a source for data that is not needed for an organization’s everyday operations, but may have to be accessed occasionally. By utilizing an archival storage, organizations can leverage to secondary sources, while still maintaining the protection of the data. Utilizing archival storage sources reduces primary storage costs required and allows an organization to maintain data that may be required for regulatory or other requirements74.
Area under curve (AUC) – 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 classifier’s accuracy75.
Area Under the ROC curve 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 positive76.
Argumentation framework is 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 arguments77.
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 assessments78.
Artificial General Intelligence (AGI) as opposed to narrow intelligence, also known as complete, strong, super intelligence, Human Level Machine Intelligence, indicates the ability of a machine that can successfully perform any tasks in an intellectual way as the human being. Artificial superintelligence is a term referring to the time when the capability of computers will surpass humans79,80.
Artificial Intelligence (AI) – (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 195681.
Artificial Intelligence Automation Platforms – 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, Infrrd82.
Artificial intelligence engine (also AI engine, AIE) 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»83,84,85.
Artificial Intelligence Markup Language (AIML) is an XML dialect for creating natural language software agents86.
Artificial Intelligence of the Commonsense knowledge is one of the areas of development of artificial intelligence, which is engaged in modeling the ability of a person to analyze various life situations and be guided in his actions by common sense87.
Artificial Intelligence Open Library is a set of algorithms designed to develop technological solutions based on artificial intelligence, described using programming languages and posted on the Internet88.
Artificial intelligence system (AIS) 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 – 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 intelligence89.
Artificial life (Alife, A-Life) 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. 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 phenomena90.
Artificial Narrow Intelligence (ANI), 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 systems91.
Artificial Neural Network (ANN) 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 task92.
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 bounded93,94.
Artificial Superintelligence (ASI) 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 computer’s cognitive ability is superior to a human’s95.
Assistive intelligence is AI-based systems that help make decisions or perform actions.
Association for the Advancement of Artificial Intelligence (AAAI) is 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 directions96.
Association 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» recommendations97.
Association Rule Learning is a rule-based Machine Learning method for discovering interesting relations between variables in large data sets98.
Asymptotic computational complexity 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 notation99.
Asynchronous inter-chip protocols are protocols for data exchange in low-speed devices; instead of frames, individual characters are used to control the exchange of data100.
Attention mechanism 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 decoder101.
Attributional calculus (AC) is 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 people102.
Augmented Intelligence 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 intelligence103.
Augmented reality (AR) is 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 olfactory104.
Augmented reality technologies 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 features105.
Auto Associative Memory 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 vectors106.
Autoencoder (AE) is a type of Artificial Neural Network used to produce efficient representations of data in an unsupervised and non-linear manner, typically to reduce dimensionality107.
Automata theory – 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). 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 automata108,109.
Automated control system – a set of software and hardware designed to control technological and (or) production equipment (executive devices) and the processes they produce, as well as to control such equipment and processes110.
Automated planning and scheduling (also simply AI planning) is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space. Planning is also related to decision theory111.
Automated processing of personal data – processing of personal data using computer technology112.
Automated reasoning is an area of computer science and mathematical logic dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer programs that allow computers to reason completely, or nearly completely, automatically. Although automated reasoning is considered a sub-field of artificial intelligence, it also has connections with theoretical computer science, and even philosophy113.
Automated system is an organizational and technical system that guarantees the development of solutions based on the automation of information processes in various fields of activity114.
Automation bias is when a human decision maker favors recommendations made by an automated decision-making system over information made without automation, even when the automated decision-making system makes errors115.
Automation is a technology by which a process or procedure is performed with minimal human intervention116.
Autonomic computing is the ability of a system to adaptively self-manage its own resources for high-level computing functions without user input117.
Autonomous artificial intelligence is a biologically inspired system that tries to reproduce the structure of the brain, the principles of its operation with all the properties that follow from this118,119.
Autonomous car (also self-driving car, robot car, and driverless car) is a vehicle that is capable of sensing its environment and moving with little or no human input120.
Autonomous is a machine is described as autonomous if it can perform its task or tasks without needing human intervention121.
Autonomous robot is a robot that performs behaviors or tasks with a high degree of autonomy. Autonomous robotics is usually considered to be a subfield of artificial intelligence, robotics, and information engineering122.
Autonomous vehicle is a mode of transport based on an autonomous driving system. The control of an autonomous vehicle is fully automated and carried out without a driver using optical sensors, radar and computer algorithms123.
Autoregressive Model is an autoregressive model is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step. In statistics and signal processing, an autoregressive model is a representation of a type of random process. It is used to describe certain time-varying processes in nature, economics, etc.124.
Auxiliary intelligence – systems based on artificial intelligence that complement human decisions and are able to learn in the process of interacting with people and the environment.
Average precision is a metric for summarizing the performance of a ranked sequence of results. Average precision is calculated by taking the average of the precision values for each relevant result (each result in the ranked list where the recall increases relative to the previous result)125.
Ayasdi is an enterprise scale machine intelligence platform that delivers the automation that is needed to gain competitive advantage from the company’s big and complex data. Ayasdi supports large numbers of business analysts, data scientists, endusers, developers and operational systems across the organization, simultaneously creating, validating, using and deploying sophisticated analyses and mathematical models at scale126.
