Scaling Distributed Machine Learning, to the Edge & Back
watch on portal.gitnation.org ↗https://portal.gitnation.org/contents/scaling-distributed-machine-learning-to-the-edge-and-backsummary
Explains why organizations move data storage and machine learning to edge locations and how combining an edge database with edge compute in one platform enables distributed architectures. Describes geographically distributed learning so models learn location-specific behaviors and argues that performance improvements validate mobile edge computing for ML workloads.
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