Recommendation ITU-T M.3383 introduces the requirements for log analysis in telecom management with artificial intelligence (AI) and includes a functional…
International
Recommendation ITU-T F.742.1 describes application scenarios and requirements for smart class system based on artificial intelligence, including application scenarios, service…
ETSI GR SAI 009 V 1.1.1
Securing Artificial Intelligence (SAI) – Artificial Intelligence Computing Platform Security Framework
This work item aims to specify a security framework of AI computing platform containing hardware and basic software to protect…
PD ISO/IEC TR 24372:2021
Information technology – Artificial intelligence (AI) – Overview of computational approaches for AI systems
This document provides an overview of the state of the art of computational approaches for AI systems, by describing: a)…
This document presents specific characteristics of industrial internet platforms (IIPs), including related security threats, context-specific security control objectives and security…
ITU-T M.3385
Intelligence levels evaluation framework of artificial intelligence enhanced telecom operation and management
Recommendation ITU-T M.3385 provides a detailed evaluation framework, evaluation rating method and automatic evaluating process for intelligence levels of systems…
ITU-T M.3384
Intelligence levels of artificial intelligence-enhanced telecom operation and management
Recommendation ITU-T M.3384 provides definitions, classifications, object selection and an automatic evaluating mechanism for the evaluation of the intelligence levels…
ISO/IEC CD 8663
Information technology – Brain-computer Interfaces – Vocabulary
This document specifies the terms and definitions commonly used in the field of Brain-computer Interface (BCI), including basic concepts and…
ITU-T L Supplement 53
Guidelines on the implementation of environmental efficiency criteria for artificial intelligence and other emerging technologies
Supplement 53 to ITU-T L-series Recommendations provides guidelines to policy-makers, technologists, innovators, environmentalists and other stakeholders from the technology industry,…
Recommendation ITU-T Y.3183 provides a framework for machine learning-assisted network slicing management, leveraging vertical end users’ feedback on quality of…
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