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Y.3172
Y.3172 is an ITU-T Recommendation specifying an architecture for machine learning in future networks including 5G (IMT-2020). The architecture describes a machine learning pipeline in the context of Telecommunications network, telecommunication networks that involves the training of machine learning models, and also the deployment using methods such as Containership (computer science), containers and Orchestration (computing), orchestration. A set of architectural requirements and specific architectural components needed to satisfy these requirements are presented. This includes i.a., machine learning pipeline as well as machine learning management and orchestration functionalities. Additionally, the standard describes the integration of such components into future networks including IMT-2020 as well as guidelines for applying this architectural framework in a variety of technology-specific underlying networks. The Recommendation Y.3173 builds upon Y.3172 by specifying a framewo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ITU-T
The ITU Telecommunication Standardization Sector (ITU-T) is one of the three sectors (divisions or units) of the International Telecommunication Union (ITU). It is responsible for coordinating standards for telecommunications and Information Communication Technology such as X.509 for cybersecurity, Y.3172 and Y.3173 for machine learning, and H.264/MPEG-4 AVC for video compression, between its Member States, Private Sector Members, and Academia Members. The first meeting of the World Telecommunication Standardization Assembly (WTSA), the sector's governing conference, took place on 1 March of that year. ITU-T has a permanent secretariat called the Telecommunication Standardization Bureau (TSB), which is based at the ITU headquarters in Geneva, Switzerland. The current director of the TSB is Chaesub Lee (of South Korea), whose first 4-year term commenced on 1 January 2015, and whose second 4-year term commenced on 1 January 2019. Chaesub Lee succeeded Malcolm Johnson (Director), Malc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ITU-T Study Group 13
The ITU-T Study Group 13 (SG13) is a statutory group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with networks, infrastructure and cloud computing, including the networking aspects of mobile telecommunications. Examples include: Y.1564, Y.1731, etc.. Recent work includes a series of standards on using machine learning in networking, such as Y.3172, Y.3173, Y.3176, and Y.3181. Administratively, SG13 is a statutory meeting of the World Telecommunication Standardization Assembly (WTSA), which creates the ITU-T Study Groups and appoints their management teams. The secretariat is provided by the Telecommunication Standardization Bureau (under Director Chaesub Lee Chaesub Lee PhD (Korean: 이재섭) is the Director of ITU Telecommunication Standardization Bureau, the permanent secretariat of the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and as such, an Under-Secr ...). References {{Compu-network-stub In ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
IMT-2020
International Mobile Telecommunications-2020 (IMT-2020 Standard) are the requirements issued by the ITU Radiocommunication Sector (ITU-R) of the International Telecommunication Union (ITU) in 2015 for 5G networks, devices and services. On February 1st, 2021, the standard was published as Recommendation ITU-R M.2150-0 titled ''Detailed specifications of the radio interfaces of IMT-2020'', but most of it was finalized years earlier. For example the requirements for radio access technologies listed below were adopted in November 2017. Following the publication of the requirements the developers of radio access technologies such as 3GPP and ETSI are expected to develop 5G technologies meeting these requirements. 3GPP is developing radio access technologies 5G NR, LTE-M and NB-IoT that together are expected to meet all requirements, while ETSI is developing DECT-2020 NR and Nufront is developing EUHT (Enhanced Ultra High Throughput). Requirements The following parameters are the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Telecommunications Network
A telecommunications network is a group of nodes interconnected by telecommunications links that are used to exchange messages between the nodes. The links may use a variety of technologies based on the methodologies of circuit switching, message switching, or packet switching, to pass messages and signals. Multiple nodes may cooperate to pass the message from an originating node to the destination node, via multiple network hops. For this routing function, each node in the network is assigned a network address for identification and locating it on the network. The collection of addresses in the network is called the address space of the network. Examples of telecommunications networks include computer networks, the Internet, the public switched telephone network (PSTN), the global Telex network, the aeronautical ACARS network, and the wireless radio networks of cell phone telecommunication providers. Network structure In general, every telecommunications network conceptually ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Containership (computer Science)
In computer science, object composition and object aggregation are closely related ways to combine objects or data types into more complex ones. In conversation the distinction between composition and aggregation is often ignored. Common kinds of compositions are objects used in object-oriented programming, tagged unions, sets, sequences, and various graph structures. Object compositions relate to, but are not the same as, data structures. Object composition refers to the logical or conceptual structure of the information, not the implementation or physical data structure used to represent it. For example, a sequence differs from a set because (among other things) the order of the composed items matters for the former but not the latter. Data structures such as arrays, linked lists, hash tables, and many others can be used to implement either of them. Perhaps confusingly, some of the same terms are used for both data structures and composites. For example, "binary tree" ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Orchestration (computing)
In system administration, orchestration is the automated configuration, coordination, and management of computer systems and software.Erl, Thomas (2005) Service-Oriented Architecture: Concepts, Technology & Design. ''Prentice Hall'', . A number of tools exist for automation of server configuration and management, including Kubernetes, Ansible, Puppet, Salt, Terraform, and AWS CloudFormation. Usage Orchestration is often discussed in the context of service-oriented architecture, virtualization, provisioning, converged infrastructure and dynamic data center topics. Orchestration in this sense is about aligning the business request with the applications, data, and infrastructure. In the context of cloud computing, the main difference between workflow automation and orchestration is that workflows are processed and completed as processes within a single domain for automation purposes, whereas orchestration includes a workflow and provides a directed action towards larger goals an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AI For Good
AI for Good is a year-round digital platform of the United Nations, where AI innovators and problem owners learn, discuss and connect to identify practical AI solutions to advance the UN Sustainable Development Goals, SDGs. The impetus for organizing global summits that are action oriented, came from existing discourse in artificial intelligence (AI) research being dominated by research streams such as the Netflix Prize (improve the movie recommendation algorithm). AI for Good aims to bring forward Artificial Intelligence research topics that contribute towards more global problems, in particular through the Sustainable Development Goals. AI for Good came out of the AI for Good Global Summit 2020 which had been moved online in 2020 due to the COVID-19 Pandemic. AI for Good is organized by the Standardization Sector of ITU (ITU-T). Since moving online, AI for Good developed into three main programme streams: Learn, Build, and Connect. AI for Good also helps organize ITU's Global Stan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ITU-WHO Focus Group On Artificial Intelligence For Health
The ITU-WHO Focus Group on Artificial Intelligence for Health (AI for Health) is an inter-agency collaboration between the World Health Organization and the ITU, which created a benchmarking framework to assess the accuracy of AI in health. This organization convenes an international network of experts and stakeholders from fields like research, practice, regulation, ethics, public health, etc, that develops guideline documentation and code. The documents address ethics, assessment/evaluation, handling, and regulation of AI for health solutions, covering specific use cases including AI in ophthalmology, histopathology, dentistry, malaria detection, radiology, symptom checker applications, etc. FG-AI4H has established an ad hoc group concerned with digital technologies for health emergencies, including COVID-19. All documentation is public. The idea for the Focus Group came out of the Health Track of the 2018 AI for Good Global Summit. Administratively, FG-AI4H was created by ITU ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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