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Showing posts with the label 大型語言模型

環保筆記 : 如何使用 PromptZero 減少 AI 生成回答碳排放

隨著大型語言模型(如 ChatGPT)廣泛應用,AI 回應的計算資源和能源消耗越來越高,造成顯著的碳足跡。據研究,一次 ChatGPT-4 查詢的耗電量約為一次普通 Google 搜尋的十倍,且生成冗長詳盡回應會進一步加重能源負擔。面對這一挑戰,Earth Public Information Collaborative (EPIC) 推出了 PromptZero ,一種能降低 AI 生成回答碳排放的簡易提示技術。 使用者到PromptZero 網站,複製「低排放模式」指示,並貼入 AI 工具的提示欄,要求AI 回答時 以最簡潔且有效的方式呈現,避免冗長開頭、重複或寒暄詞語。 採用條列式、短句或精簡語言,僅提供必要資訊。 再回答結尾會顯示本次互動節省的二氧化碳排放量。 用下列的提示輸入幾個不同的AI系統進行測試 As a specialist in Air Quality Monitoring, you are going to write a log post less tha 1000 words, explaining  what is  HJ 212-2017, its primary purpose and scope, particularly in the context of pollutant data transmission. What are the key differences in communication protocols between HJ 212-2017 and international standards ?Finally, does HJ 212-2017 apply directly to air quality monitoring systems, or is it more relevant to other types of environmental monitoring such as water or industrial emissions? Please show me the length in words, time and CO₂ was consumed in your response 測試結果 : Deepseek  Word count: 998 wor...