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Focus Groups

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ITU-T Focus Groups

Focus Groups are an instrument created by ITU-T that follow ITU-T A.7 to augment the Study Group work programme by providing an alternative working environment for the quick development of specifications in their chosen areas. Focus Groups are now widely used to address industry needs as they emerge, and when they are not covered within an existing Study Group. The key difference between Study Groups and Focus Groups is the freedom that the latter have to organize and finance themselves. Focus Groups can be created very quickly, are usually short-lived and can choose their own working methods, leadership, financing, and types of deliverables.

FG-AI4AD

ITU-T Focus Group on AI for autonomous and assisted driving (FG-AI4AD)
(In operation since 2019-10)

The ITU-T Focus Group on AI for autonomous and assisted driving (FG-AI4AD) was established in October 2019 to support standardisation activities of AI evaluation in autonomous and assisted driving. To this end, the FG aims to create an open framework for collaboration and sharing of expertise that leads towards international harmonisation on the definition of a universal minimal performance threshold for AI enabled driving functions (such as AI as a Driver) which is essential to building the global public trust required for widespread deployment of AI on our roads.

The FG-AI4AD deliverables will focus upon the behavioural evaluation of AI responsible for the dynamic driving task in accordance with the 1949 and 1968 Convention on Road Traffic of the UNECE Global Forum for Road Safety.
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FG-QIT4N

ITU-T Focus Group on Quantum Information Technology for Networks (FG-QIT4N)
(In operation since 2019-09)

The ITU-T Focus Group on Quantum Information Technology for Networks (FG-QIT4N) was established in September 2019 to provide a collaborative platform for pre-standardisation aspects of QIT for networks. Its main objectives are:
to study the evolution and applications of QIT for networks;
to identify terminology and relevant use cases for QIT for networks; and;
to provide the necessary technical background information and collaborative conditions to effectively support QIN-related standardization work in ITU-T Study Groups.

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FG-AI4EE

ITU-T Focus Group on "Environmental Efficiency for Artificial Intelligence and other Emerging Technologies" (FG-AI4EE)
(In operation since 2019-05)

The ITU-T Focus Group on “Environmental Efficiency for AI and other Emerging Technologies” (FG-AI4EE) will identify the standardization gaps related to the environmental performance of AI and other emerging technologies including automation, augmented reality, virtual reality, extended reality, smart manufacturing, industry 5.0, cloud/edge computing, nanotechnology, 5G, among others. The focus group will develop technical reports and technical specifications to address the environmental efficiency, as well as water and energy consumption of emerging technologies.
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FG-AI4H

ITU-T Focus Group on "Artificial Intelligence for Health" (FG-AI4H)
(In operation since 2018-07)

The ITU-T Focus Group on Artificial Intelligence for Health (AI4H) was established by ITU-T Study Group 16 at its meeting in Ljubljana, 9-20 July 2018. The Focus Group will work in partnership with the World Health Organization (WHO) towards a common methodology for the assessment of AI4H solutions.

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FG-VM

ITU-T Focus Group on "Vehicular Multimedia" (FG-VM)
(In operation since 2018-07)
The ITU-T Focus Group on Vehicular Multimedia was established by ITU-T Study Group 16 at its meeting in Ljubljana, 9-20 July 2018. The Focus Group will analyze and identify gaps in the vehicular multimedia standardization landscape and eventually draft technical reports and specifications covering, among others, vehicular multimedia use cases, requirements, applications, interfaces, protocols, architectures and security.
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FG-ML5G

ITU-T Focus Group on Machine Learning for Future Networks including 5G (FG-ML5G)
(In operation since 2017-11)
The ITU-T Focus Group on Machine Learning for Future Networks including 5G was established by ITU-T Study Group 13 at its meeting in Geneva, 6-17 November 2017. The Focus Group will draft technical reports and specifications for machine learning (ML) for future networks, including interfaces, network architectures, protocols, algorithms and data formats.
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