AI developers in the United States and leaders at Microsoft are currently arguing about the legality and ethics of 'model distillation' and who should own institutional data.

美國的 AI 開發者與微軟領導層目前正就「模型蒸餾」的合法性與倫理問題，以及誰應擁有機構數據而展開爭論。

The geopolitical side of this conflict focuses on claims by Anthropic and OpenAI that Chinese companies are using 'distillation.' This is the process of training smaller AI models using the answers from more advanced ones to catch up technologically. For example, Anthropic claimed that Alibaba used 25,000 fake accounts to take millions of outputs from the Claude chatbot. US officials describe this as industrial theft that helps China avoid US restrictions on high-end computer chips. Consequently, the US government believes its technological lead has dropped from 18 months to only 6 to 9 months, which could help other nations develop advanced cyber-tools.

這場衝突的地緣政治方面，焦點在於 Anthropic 與 OpenAI 指控中國公司使用「蒸餾」技術。這個過程是指利用較先進模型的答案來訓練較小的 AI 模型，以便在技術上趕上。例如，Anthropic 指稱阿里巴巴使用了 25,000 個假帳號，從 Claude 聊天機器人中獲取了數百萬次輸出結果。美國官員將此描述為工業盜竊，幫助中國規避美國對高端電腦晶片的限制。因此，美國政府認為其技術領先優勢已從 18 個月下降至僅 6 到 9 個月，這可能會幫助其他國家開發先進的網路工具。

At the same time, there is a corporate disagreement regarding data ownership. Microsoft CEO Satya Nadella has argued that some AI labs are being hypocritical because they use public data for training but stop others from using distillation. Nadella emphasized that businesses are paying twice: first through service fees and second by giving away their 'intelligence exhaust,' which refers to the prompts and corrections that improve the AI. This creates a risk where AI providers could become competitors to their own clients by learning their private business secrets.

與此同時，企業之間對於數據所有權也存在分歧。微軟執行長 Satya Nadella 主張某些 AI 實驗室表現得十分虛偽，因為他們使用公開數據進行訓練，卻阻止他人使用蒸餾法。Nadella 強調，企業目前在支付兩次代價：首先是服務費，其次是交出他們的「智能廢氣」，即指用於改進 AI 的提示詞與修正建議。這造成了一種風險，即 AI 供應商可能透過學習客戶的私密商業機密，最終成為其客戶的競爭對手。

As a result, more companies are moving toward 'data sovereignty.' Many businesses now prefer 'on-premise' open-source models, which allow them to keep control of their own data and avoid relying on a single provider. While the US government wants to pass new laws, such as the AI Overwatch Act, to tighten export controls, industry leaders like Nadella believe it is more important to create clear boundaries to protect intellectual property.

因此，越來越多的公司正轉向「數據主權」。許多企業現在更傾向於「本地部署」的開源模型，這使他們能夠掌控自己的數據，並避免依賴單一供應商。雖然美國政府希望通過新法律（如《AI 監控法案》）來收緊出口管制，但像 Nadella 這樣的行業領袖認為，建立清晰的界限以保護知識產權更為重要。

The current situation is a struggle between US national security efforts to stop foreign AI distillation and a corporate push for open-source independence to prevent data misuse.

目前的局面是美國國家安全旨在阻止外國 AI 蒸餾的努力，與企業追求開源獨立以防止數據濫用之間的博弈。