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 [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/AI_accelerator (дата обращения: 27.04.2023)].
AI acceleration is the acceleration of AI-related computations, for this purpose specialized AI hardware accelerators are used[35 - AI acceleration [Электронный ресурс] https://flibusta.su URL: https://flibusta.su/book/38568-anglo-russkiy-tolkovyiy-slovar-po-iskusstvennomu-intellektu-i-robotote/read/ (дата обращения 06.07.2023)].
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 learning[36 - AI acceleration [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/AI_accelerator (дата обращения: 27.04.2023)].
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 them[37 - AI accelerator [Электронный ресурс] https://flibusta.su URL: https://flibusta.su/book/38568-anglo-russkiy-tolkovyiy-slovar-po-iskusstvennomu-intellektu-i-robotote/read/ (дата обращения 06.07.2023)].
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 protection[38 - Управление доверием, рисками и безопасностью ИИ (Концепция AI TRiSM) [Электронный ресурс] https://oprosso.ru URL: https://oprosso.ru/landing/blog/study/desyat-strategicheskikh-tekhnologicheskikh-trendov-na-2023-god/ (дата обращения 04.07.2023)].
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 later[39 - AI winter [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/AI_winter (дата обращения: 07.07.2022)],[40 - .Commonsense knowledge (artificial intelligence). [Электронный ресурс] en.wikipedia.org URL: https://en.wikipedia.org/wiki/Commonsense_knowledge_(artificial_intelligence) (дата обращения: 30.08.2023)].
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 systems[41 - Системы на основе ИИ [Электронный ресурс] https://en.unesco.org URL: https://en.unesco.org/artificial-intelligence/ethics#recommendation (дата обращения: 29.01.2022)].
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 algorithm[42 - AI-complete [Электронный ресурс] https://dic.academic.ru URL: https://dic.academic.ru/dic.nsf/eng_rus/373471/AI (дата обращения: 27.01.2022)].
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 device [Электронный ресурс] https://www.google.ru URL: https://www.google.ru/books/edition/Англо_русский_толковый/PxxgEAAAQBAJ?hl=ru&gbpv=1&dq=AI-enabled+device&pg=PA30&printsec=frontcover (дата обращения 07.07.2023)].
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 device[44 - AI-enabled healthcare [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Artificial_intelligence_in_healthcare (дата обращения: 27.04.2023)].
AI-enabled is hardware or software that uses AI-enabled AI, such as AI-enabled tools.
AI-optimized – optimized for AI tasks; AI-optimized chip, for example, an AI-optimized chip is a chip optimized for AI tasks (see also artificial intelligence).
AI-optimized is one that is optimized for AI tasks or optimized using AI tools, for example, an AI-optimized chip is a chip that is optimized for AI tasks.
AlexNet – the name of a neural network that won the ImageNet Large Scale Visual Recognition Challenge in 2012. It is named after Alex Krizhevsky, then a computer science PhD student at Stanford University. See ImageNet.[45 - AlexNet [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/AlexNet (дата обращения: 11.05.2023)]
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 problems[46 - Алгоритм [Электронный ресурс] https://intuit.ru URL: https://intuit.ru/studies/courses/1122/167/lecture/4566 (дата обращения: 27.03.2023)].
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 making[47 - Algorithmic Assessment [Электронный ресурс] https://www.accenture.com URL: https://www.accenture.com/nz-en/services/applied-intelligence/ai-ethics-governance (дата обращения: 27.03.2023)].
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 universe[48 - AlphaGo [Электронный ресурс] https://tadviser.ru URL: https://www.tadviser.ru/index.php/Продукт:AlphaGo (дата обращения: 19.02.2022)].
Physical media is the physical material that is used to store or transmit information in a data transmission[49 - Physical media [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Physical_media#:~:text= Physical%20media%20refers%20to%20the, such %20as%20weight%20and%20color (дата обращения 07.07.2023)].
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 use[50 - Ambient intelligence (AmI) [Электронный ресурс] https://infosys.com URL: https://www.infosys.com/insights/ai-automation/ambient-intelligence.html #:~:text=Ambient%20intelligence%20 (AmI) %20represents%20the, user’s %20needs%20and%20desires%20seamlessly (дата обращения: 31.07.2022)].
