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Homepage>IEEE Standards>35 INFORMATION TECHNOLOGY. OFFICE MACHINES>35.240 Applications of information technology>35.240.01 Application of information technology in general>IEEE 3301-2022 - IEEE Standard Adoption of Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Technical Specification Artificial Intelligence Framework (AIF) 1.1
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Released: 28.04.2023

IEEE 3301-2022 - IEEE Standard Adoption of Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Technical Specification Artificial Intelligence Framework (AIF) 1.1

IEEE Standard Adoption of Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Technical Specification Artificial Intelligence Framework (AIF) 1.1

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Standard number:IEEE 3301-2022
Released:28.04.2023
ISBN:978-1-5044-9334-5
Pages:68
Status:Active
Language:English
DESCRIPTION

IEEE 3301-2022

The MPAI AI Framework (MPAI-AIF) Technical Specification specifies architecture, interfaces, protocols and Application Programming Interfaces (API) of an AI Framework (AIF), especially designed for execution of AI-based implementations, but also suitable for mixed AI and traditional data processing workflows. MPAI-AIF possesses the following main features: • Operating System-independent. • Component-based modular architecture with standard interfaces. • Interfaces encapsulate Components to abstract them from the development environment. • Interface with the MPAI Store enables access to validated Components. • Component can be implemented as: software only (from Micro-Controller Units to High-Performance Computing), hardware only, and hybrid hardware-software. • Component system features are: • Execution in local and distributed Zero-Trust architectures. • Possibility to interact with other Implementations operating in proximity. • Direct support to Machine Learning functionalities.



New IEEE Standard - Active. This standard adopts MPAI AI Framework (MPAI-AIF) Technical Specification Version 1.1 as an IEEE Standard. The MPAI-AIF Technical Specification specifies architecture, interfaces, protocols, and Application Programming Interfaces (API) of an AI Framework (AIF), especially designed for the execution of AI-based implementation, but also suitable for mixed AI and traditional data processing workflow.