[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-ai-":3},{"tag":4,"articles":11,"peer_article_count":12},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":10},"dc62f1f3-43ae-4a2f-8c85-685a3de57f23","AI 基礎設施","ai-",33,"AI 基礎設施涵蓋模型工作流、代理工具、算力採購、資料中心與電力成本，也包括雲端平台、晶片供應和部署管線。這些底層條件決定 AI 能不能穩定訓練、推理與擴張，對產品節奏與商業模式都有直接影響。","AI infrastructure covers the layers that make model work usable in production: GPUs and chips, data centers, power, cloud platforms, deployment pipelines, and agent tooling. These foundations shape training speed, inference cost, and whether AI products can scale sustainably.",[],34]