Alexander Vlaskin - Artificial Intelligence Glossarium - 1000 terms

Artifact (Артефакт)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 47 Artifact [Электронный ресурс] //en.wikipedia.org URL: https://en.wikipedia.org/wiki/Artifact_(software_development) (дата обращения: 07.07.2022) ]

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 48 Artificial Intelligence [Электронный ресурс] // absel.ua URL: https://absel.ua/news/tri-tipa-iskusstvennogo-intellekta-ponimanie-ii.htmlobuchenii (дата обращения: 18.02.2022) ]

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 49 Artificial Intelligence Automation Platforms [Электронный ресурс] www.predictiveanalyticstoday.com URL: https://www.predictiveanalyticstoday.com/artificial-intelligence-platforms/ (дата обращения: 07.07.2022) ].

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 50 Artificial Intelligence for IT Operations (AIOps) [Электронный ресурс] www.cio.com URL: https://www.cio.com/article/196239/what-is-aiops-injecting-intelligence-into-it-operations.html (дата обращения: 07.07.2022) , 51 51 Artificial Intelligence for IT Operations (AIOps) [Электронный ресурс] www.gartner.com URL: https://www.gartner.com/en/information-technology/glossary/aiops-platform (дата обращения: 07.07.2022) ].

Artificial Intelligence Markup Language AIML (Язык разметки искусственного интеллекта) –An XML dialect for creating natural language software agents [ 52 52 Artificial Intelligence Markup Language AIML [Электронный ресурс] // engati.com URL: https://www.engati.com/glossary/artificial-intelligence-markup-language (дата обращения: 18.02.2022) ]

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 53 Artificial life [Электронный ресурс] //en.wikipedia.org URL: https://en.wikipedia.org/wiki/Artificial_life (дата обращения: 07.07.2022) ].

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 54 Artificial Narrow Intelligence (ANI) [Электронный ресурс] // dic.academic.ru URL: https://dic.academic.ru/dic.nsf/ruwiki/318696 (дата обращения: 27.01.2022) , 55 55 Artificial Narrow Intelligence (ANI) [Электронный ресурс] // dic.academic.ru URL: https://dic.academic.ru/searchall.php?SWord=Artificial+Narrow+Intelligence+%28ANI%29+&from=ru&to=xx&did=&stype (дата обращения: 27.01.2022) ].