Titlebook: EdgeAI for Algorithmic Government; Rajan Gupta,Sanjana Das,Saibal Kumar Pal Book 2023 The Author(s), under exclusive license to Springer N

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悲觀

Book 2023igence brings out challenges of latency, overhead communication, and significant privacy risks. Due to the sheer volume of data generated by IoT devices, the data analysis must be performed at the forefront of the network. This introduces the need for edge computing in algorithmic government. EdgeAI

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Introduction: The Rise of a Nation,ndicators (KPIs). We also analyze how each enabling technology impacts the different KPIS for both the training and inference process. Finally, we summarize all the architectures, criteria for evaluating AI model workflow, and the enabling technologies for model training and inference at the edge in the form of a comparative analysis.

分解

Algorithmic Government,eral agencies. The issues identified are latency, communication overhead, and bandwidth consumption, focusing on security and privacy concerns. Finally, we discuss these challenges and drive demand for new computing technologies.

分解

AVANT

EdgeAI: Concept and Architecture,ndicators (KPIs). We also analyze how each enabling technology impacts the different KPIS for both the training and inference process. Finally, we summarize all the architectures, criteria for evaluating AI model workflow, and the enabling technologies for model training and inference at the edge in the form of a comparative analysis.

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