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When deploying a multilingual AI chatbot globally, I want to minimize per-region latency while keeping communication costs down. Which strategy is most effective?
①Deploy lightweight translation layers and local inference endpoints in each major region.
②Simplify operations by consolidating all users into a single high-performance region.
③Cache the conversation text on a content delivery network and return responses.
④Keep expensive dedicated resources running in each region.
⑤Ensure that all translation and inference are performed on the client side.