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Which design decision is most appropriate when aiming to balance environmental impact and responsiveness in real-time recommendations for retail stores?
①Run all large-model inference in the centralized cloud, sacrificing responsiveness.
②Keep all parts that require real-time responsiveness local and always provide ample computing power.
③Use only a static recommendation list without performing inference.
④Adopt a hybrid architecture that delegates important real-time processing to small models at the edge, while performing heavy batch processing and training in the cloud.
⑤Prioritize operational costs over real-time requirements.