#distributed

機械支援の翻訳下書き (Japanese) for "Federated AI": An approach to AI training and inference where models are distributed across multiple nodes or organizations without centralizing raw data. Each node trains on its local data and shares only model updates, preserving privacy while benefiting from collective learning.

“例文の下書き: The hospital network used federated AI to improve diagnosis models without sharing patient records.”

機械支援の翻訳下書き (Japanese) for "Edge Computing": A computing paradigm that processes data at or near its source — at the "edge" of the network — rather than sending it all to a central cloud datacenter. Edge computing reduces latency, lowers bandwidth costs, and enables real-time processing for users around the globe.

“例文の下書き: Serving the API from edge nodes cut response times from 200ms to 20ms for international users.”