今年以來，人工智能（AI）的熱潮席卷全球。不過，你知道和AI對話還會消耗水資源嗎？綜合美聯社、歐洲新聞電視臺報道，加州大學河濱分校電氣與計算機工程系研究人員任紹磊的一項研究發現，每當人們問人工智能大模型ChatGPT 5到50個提示詞或問題時，它就會“吞下”500毫升的水（接近一小瓶礦泉水的水）。而每個月都有十數億用戶在這個平臺提問，這一數字增長的很快。
“It’s fair to say the majority of the growth is due to AI,” including “its heavy investment in generative AI and partnership with OpenAI,” said Shaolei Ren, a researcher at the University of California, Riverside who has been trying to calculate the environmental impact of generative AI products such as ChatGPT.
In a paper due to be published later this year, Ren’s team estimates ChatGPT gulps up 500 milliliters of water every time you ask it a series of between 5 to 50 prompts or questions. With nearly 1.5 billion users a month, that adds up fast.據央視財經報道，訓練和運行AI大模型，通常需要數以萬計的服務器來提供計算資源、存儲資源以及低延遲的網絡連接，這些服務器會以集群的方式部署在名為“數據中心（data center）”的物理場所，當它們一起工作時，會在短時間內產生高度集中的熱量，所以需要大量的水資源進行冷卻。
以微軟和谷歌為例，2022年，微軟一共用掉了約17億加侖（約64億升）水，相當于可以填滿約2500個奧運會規格的泳池；而谷歌的數據中心和辦公室則用掉了總計56億加侖（約212億升）水，相當于8500個奧運會規格的游泳池。
In its latest environmental report, Microsoft disclosed that its global water consumption spiked 34% from 2021 to 2022 (to nearly 1.7 billion gallons, or more than 2,500 Olympic-sized swimming pools), a sharp increase compared to previous years that outside researchers tie to its AI research.
Google’s water consumption has also increased after growing AI efforts. As per Google’s 2023 Environmental Report, the tech giant used 5.6 billion gallons of water last year.
數據顯示，現在人工智能所需要的算力預計每100天就會翻一番，并且在未來五年內可能會增長超過一百萬倍。研究人員預計，到2027年，全球范圍內的AI需求可能會需要消耗掉66億立方米的水資源，相當于丹麥年總用水量的4至6倍或英國年總用水量的一半。
According to recent studies, “operational water withdrawal of global AI may reach 4.2 – 6.6 billion cubic meters in 2027”, representing “4 – 6 times more than the total annual water withdrawal of Denmark or half that of the United Kingdom”.
據《紐約時報》此前報道，一項研究分析稱，到2027年，人工智能服務器每年的用電量將在85到134太瓦時（Twh）之間。這相當于阿根廷、荷蘭和瑞典一年的用電量，約占目前全球用電量的0.5%。
In a middle-ground scenario, by 2027 A.I. servers could use between 85 to 134 terawatt hours (Twh) annually. That’s similar to what Argentina, the Netherlands and Sweden each use in a year, and is about 0.5 percent of the world's current electricity use.
《紐約時報》：“人工智能可能很快需要相當于整個國家的電力另據歐洲電視臺，對訓練人工智能至關重要的數據中心，其能源消耗占全球能源消耗的近1%。這個數字在未來幾年還會上升。
Data centers, essential for AI training, account for almost 1% of the world's energy consumption. This figure is set to rise over the next few years.
然而，這些數據中心排放的二氧化碳量取決于它們所在國家是用煤炭、天然氣還是可再生能源發電。在微軟和艾倫人工智能研究所資助的一篇論文中，研究人員表明，通過變更人工智能的訓練地點，有可能將操作的二氧化碳排放量減少75%。
But these centres emit varying amounts of CO2 depending on whether their base country produces its electricity from coal or gas, for example, or from renewable energies. In a paper funded by Microsoft and the Allen Institute for Artificial Intelligence, researchers showed that by modifying the training location of an AI, it was possible to reduce the operation's CO2 emissions by 75%.
不過，報道指出，盡管人工智能會對環境產生影響，但它在對抗全球變暖方面也發揮著正面作用。例如，人工智能可以幫助氣象學家預測極端天氣事件，或優化工業流程以減少二氧化碳排放。
Despite their environmental impact, AIs have a role to play in the fight against global warming. For example, they can help meteorologists predict extreme weather events, or optimise industrial processes to reduce CO2 emissions.
如今，開發者面臨的挑戰是透明度。大多數公開的人工智能大模型，都沒有透露這些模型是在哪里訓練的，或者使用它們的碳成本。
The particular challenge for developers today is transparency. Most publicly available AI models do not reveal where the models were trained, or the carbon cost of using them.
報道認為，當用戶了解到這些信息時，他們可以做出更明智的選擇。例如，在使用ChatGPT解答一些基礎問題前，可以先在瀏覽器搜索下問題答案，因為瀏覽器搜索所消耗的能源更少。
歐洲新聞電視臺：“ChatGPT比傳統的互聯網搜索耗能更多”When users do have this information, they can make their own informed choices. For example, before bombarding ChatGPT with basic questions, we can just do a simple browser search, which is less power-hungry.
綜合來源：央視財經，歐洲新聞電視臺，紐約時報，美聯社
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