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Uncertainty Estimation in Multi-Agent Distributed Learning for AI-Enabled Edge Devices
March 15, 2024, 4:42 a.m. | Gleb Radchenko, Victoria Andrea Fill
cs.LG updates on arXiv.org arxiv.org
Abstract: Initially considered as low-power units with limited autonomous processing, Edge IoT devices have seen a paradigm shift with the introduction of FPGAs and AI accelerators. This advancement has vastly amplified their computational capabilities, emphasizing the practicality of edge AI. Such progress introduces new challenges of optimizing AI tasks for the limitations of energy and network resources typical in Edge computing environments. Our study explores methods that enable distributed data processing through AI-enabled edge devices, enhancing …
abstract accelerators advancement agent ai accelerators arxiv autonomous capabilities challenges computational cs.ai cs.dc cs.lg devices distributed distributed learning edge edge ai edge devices fpgas introduction iot low multi-agent paradigm power processing progress shift type uncertainty units
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