《路透》：中国军方利用OpenAI、Anthropic模型蒸馏发展AI

《路透》检视逾 80 篇中国学术论文与专利文件后发现，中国军事研究人员长期运用美国 OpenAI 与 Anthropic 等领先人工智慧（AI）公司开发的模型输出成果，训练国产 AI 系统，借此强化中国的国防能力。

报导指出，这项此前未被报导的发现，罕见揭露中国军事与安全相关机构如何借助美国最先进 AI 模型，作为快速开发专用系统的捷径。

尽管美国持续限制中国取得先进晶片及其他战略技术，但中国相关单位仍试图利用现有 AI 能力加速自身技术发展。

文件显示，中国研究机构广泛采用一种名为「模型蒸馏」的技术。该方法是利用强大 AI 系统产生的输出结果，训练规模较小、用途更专门化的 AI 模型，使其能在本地端部署运行，而不需要从零开始打造尖端 AI 系统所需的庞大运算资源。

《路透》检视的资料，包括由位于华盛顿的詹姆斯敦基金会（Jamestown Foundation）汇整的研究报告，显示模型蒸馏技术已被与中国人民解放军及其他军事机构相关的研究人员广泛采用。

相关论文显示，中国国防机构将美国领先 AI 模型视为两种重要资源：一方面可作为技术洞察来源，另一方面也能协助缩小与美国竞争对手之间的技术差距。

目前争议焦点并不在于「模型蒸馏」技术本身，因为这是一种业界广泛使用的方法，而是在于未经授权的模型能力提取行为。

这项议题也已成为美中即将展开 AI 治理与安全对话前的重要争议焦点。美国官员指控，部分中国机构利用模型蒸馏技术，从美国 AI 模型中提取关键能力，可能削弱美方出口管制措施，并侵犯智慧财产权。

中国则否认相关指控，反批华盛顿正在推动 AI「霸权主义」，同时声称美国企业也采取过类似做法。

此外，中国 AI 开发商也驳斥外界认为其技术突破依赖外国模型的说法。中国 AI 新创公司月之暗面（Moonshot）上周便否认川普政府关于其 Kimi K3 模型透过模型蒸馏技术打造的指控，表示该模型主要源自公司自身的技术创新。

詹姆斯敦基金会研究员 Sunny Cheung 分析超过 60 篇相关论文后表示，中国军事科学家正有系统地撷取西方 AI 模型的推理过程，并将其调整应用于监控、网路战与战术决策等领域。

Cheung 表示：「教导一个模型给出正确答案是一回事，但让它学会答案背后的推理过程，难度要高得多。」

他指出：「这些论文显示，与中国军方相关的研究人员正试图将西方模型中昂贵且具专有性的推理能力，转移到他们能够控制并在本地部署的小型系统中。」

《路透》已对相关学术文献进行查证，并另外确认了约 24 起与军方相关的案例研究。

其中一篇去年由中国人民解放军 96941 部队研究人员发表的论文指出，该部队曾利用 OpenAI 的 GPT-3.5 处理敏感军事软体原始码。

研究人员表示，第三方 AI 模型不适合处理机密资讯。为了解决这项限制，他们先利用 GPT-3.5 对软体程式码进行摘要整理，再使用这些摘要内容训练中国自主开发的 AI 模型，使其能完全在中国军事网路内部运行。

白宫、美国国防部、中国外交部、中国人民解放军以及 OpenAI 均未回应置评请求。

中国扩大 AI 蒸馏应用从社群监控延伸至无人作战系统

《路透》与詹姆斯敦基金会对相关论文的检视显示，中国研究人员利用模型蒸馏技术的范围相当广泛，应用领域从内容监控一路延伸至军事部署。

在与中国武器产业关系密切的中北大学，研究人员曾利用 Anthropic 旗下 Claude 3 Haiku 生成合成训练资料，用于打造社群媒体监控与内容审查用途的文字分类模型。

Anthropic 表示，公司并未向中国或受北京控制的企业提供 Claude 商业使用权限，并透过监控系统侦测违反政策的行为。

该公司补充指出，经过蒸馏后的模型可能会失去原始系统所具备的安全防护机制，进而导致敏感能力被转移至 Anthropic 无法控制的模型中。

此外，中国人民解放军国防科技大学（National University of Defense Technology）2024 年发表的一篇论文指出，研究人员利用模型蒸馏技术，缩小一套影像处理模型的规模，使其能部署于无人机上。

这让无人机即使在通讯中断的情况下，仍能即时分析影像资料，并支援导航与目标判定等决策。

此外，中国人民解放军军事科学院（Academy of Military Sciences）的研究人员也利用模型蒸馏技术，让目标识别模型能在战术级硬体设备上运行。

该研究于今年稍早发布，内容描述相关模型被应用于包含无人机、军舰与无人潜艇的模拟海上作战环境中。

中国押注 AI 模型蒸馏追赶美国但技术能力仍存限制

中国正积极采用模型蒸馏技术，试图在尖端 AI 竞赛中追赶美国，同时因华盛顿对高阶晶片实施出口管制，面临先进运算资源受限的挑战。

中国中央与地方政府近年大力推动「模型轻量化」与边缘运算，并透过补贴与研究资金支持相关技术发展，目标是让 AI 模型能够在无人机、卫星及其他运算能力有限的设备上运行。

不过，专家也提醒，模型蒸馏技术存在明显限制。同时，随着中国 AI 模型逐渐缩小与美国同类模型之间的差距，中国军事研究人员也开始关注模型蒸馏可能带来的安全风险。

今年 1 月，中国人民解放军陆军工程大学研究人员发表一篇论文，探讨「无资料蒸馏」的威胁。这种方法可在无需直接取得模型核心参数的情况下，透过逆向工程方式推测并重建模型能力。

为防范这类漏洞，研究人员提出防御机制，试图遮蔽模型公开输出中可能暴露的隐藏逻辑资讯。

然而，经过蒸馏后的模型通常只能继承原始模型部分特定能力，无法完全复制尖端 AI 系统所具备的广泛智慧。

AI 资料公司 Sapien 共同创办人 Trevor Koverko 表示，蒸馏模型的能力仍低于其作为「教师模型」的原始系统。

他指出：「最好的理解方式，是将其视为把部分特定能力转移到成本更低、可在本地控制的系统中，而不是实现对尖端 AI 技术的真正自主化。」

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null, "title": "《路透》：中国军方利用OpenAI、Anthropic模型蒸馏发展AI", "shortTitle": "《路透》：中国军方利用OpenAI、Anthropic模型蒸", "tagId": "", "attr": "", "articleView": null, "source": null, "author": "网络", "description": "《路透》揭露，中国军事研究人员疑利用 OpenAI 与 Anthropic 等美国先进 AI 模型输出，透过模型蒸馏技术训练国产 AI 系统，应用于监控、网路战、无人机与军事决策，引发美中 AI 安全与技术管制争议。", "img": "https://cimg.cnyes.cool/prod/news/6555748/l/4971e2469de2ffc0708a04b610733a35.jpg", "content": "《路透》检视逾 80 篇中国学术论文与专利文件后发现，中国军事研究人员长期运用美国 OpenAI 与 Anthropic 等领先人工智慧（AI）公司开发的模型输出成果，训练国产 AI 系统，借此强化中国的国防能力。\n<img src=\"https://cimg.cnyes.cool/prod/news/6555748/l/4971e2469de2ffc0708a04b610733a35.jpg\" alt=\"《路透》：中国军方利用OpenAI、Anthropic模型蒸馏发展AI\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\">\n\n\n报导指出，这项此前未被报导的发现，罕见揭露中国军事与安全相关机构如何借助美国最先进 AI 模型，作为快速开发专用系统的捷径。\n\n尽管美国持续限制中国取得先进晶片及其他战略技术，但中国相关单位仍试图利用现有 AI 能力加速自身技术发展。\n\n文件显示，中国研究机构广泛采用一种名为「模型蒸馏」的技术。该方法是利用强大 AI 系统产生的输出结果，训练规模较小、用途更专门化的 AI 模型，使其能在本地端部署运行，而不需要从零开始打造尖端 AI 系统所需的庞大运算资源。\n\n《路透》检视的资料，包括由位于华盛顿的詹姆斯敦基金会（Jamestown Foundation）汇整的研究报告，显示模型蒸馏技术已被与中国人民解放军及其他军事机构相关的研究人员广泛采用。\n\n相关论文显示，中国国防机构将美国领先 AI 模型视为两种重要资源：一方面可作为技术洞察来源，另一方面也能协助缩小与美国竞争对手之间的技术差距。\n\n目前争议焦点并不在于「模型蒸馏」技术本身，因为这是一种业界广泛使用的方法，而是在于未经授权的模型能力提取行为。\n\n这项议题也已成为美中即将展开 AI 治理与安全对话前的重要争议焦点。美国官员指控，部分中国机构利用模型蒸馏技术，从美国 AI 模型中提取关键能力，可能削弱美方出口管制措施，并侵犯智慧财产权。\n\n中国则否认相关指控，反批华盛顿正在推动 AI「霸权主义」，同时声称美国企业也采取过类似做法。\n\n此外，中国 AI 开发商也驳斥外界认为其技术突破依赖外国模型的说法。中国 AI 新创公司月之暗面（Moonshot）上周便否认川普政府关于其 Kimi K3 模型透过模型蒸馏技术打造的指控，表示该模型主要源自公司自身的技术创新。\n\n詹姆斯敦基金会研究员 Sunny Cheung 分析超过 60 篇相关论文后表示，中国军事科学家正有系统地撷取西方 AI 模型的推理过程，并将其调整应用于监控、网路战与战术决策等领域。\n\nCheung 表示：「教导一个模型给出正确答案是一回事，但让它学会答案背后的推理过程，难度要高得多。」\n\n他指出：「这些论文显示，与中国军方相关的研究人员正试图将西方模型中昂贵且具专有性的推理能力，转移到他们能够控制并在本地部署的小型系统中。」\n\n《路透》已对相关学术文献进行查证，并另外确认了约 24 起与军方相关的案例研究。\n\n其中一篇去年由中国人民解放军 96941 部队研究人员发表的论文指出，该部队曾利用 OpenAI 的 GPT-3.5 处理敏感军事软体原始码。\n\n研究人员表示，第三方 AI 模型不适合处理机密资讯。为了解决这项限制，他们先利用 GPT-3.5 对软体程式码进行摘要整理，再使用这些摘要内容训练中国自主开发的 AI 模型，使其能完全在中国军事网路内部运行。\n\n白宫、美国国防部、中国外交部、中国人民解放军以及 OpenAI 均未回应置评请求。\n\n<h6>中国扩大 AI 蒸馏应用从社群监控延伸至无人作战系统</h6>\n\n《路透》与詹姆斯敦基金会对相关论文的检视显示，中国研究人员利用模型蒸馏技术的范围相当广泛，应用领域从内容监控一路延伸至军事部署。\n\n在与中国武器产业关系密切的中北大学，研究人员曾利用 Anthropic 旗下 Claude 3 Haiku 生成合成训练资料，用于打造社群媒体监控与内容审查用途的文字分类模型。\n\nAnthropic 表示，公司并未向中国或受北京控制的企业提供 Claude 商业使用权限，并透过监控系统侦测违反政策的行为。\n\n该公司补充指出，经过蒸馏后的模型可能会失去原始系统所具备的安全防护机制，进而导致敏感能力被转移至 Anthropic 无法控制的模型中。\n\n此外，中国人民解放军国防科技大学（National University of Defense Technology）2024 年发表的一篇论文指出，研究人员利用模型蒸馏技术，缩小一套影像处理模型的规模，使其能部署于无人机上。\n\n这让无人机即使在通讯中断的情况下，仍能即时分析影像资料，并支援导航与目标判定等决策。\n\n此外，中国人民解放军军事科学院（Academy of Military Sciences）的研究人员也利用模型蒸馏技术，让目标识别模型能在战术级硬体设备上运行。\n\n该研究于今年稍早发布，内容描述相关模型被应用于包含无人机、军舰与无人潜艇的模拟海上作战环境中。\n\n<h6>中国押注 AI 模型蒸馏追赶美国但技术能力仍存限制</h6>\n\n中国正积极采用模型蒸馏技术，试图在尖端 AI 竞赛中追赶美国，同时因华盛顿对高阶晶片实施出口管制，面临先进运算资源受限的挑战。\n\n中国中央与地方政府近年大力推动「模型轻量化」与边缘运算，并透过补贴与研究资金支持相关技术发展，目标是让 AI 模型能够在无人机、卫星及其他运算能力有限的设备上运行。\n\n不过，专家也提醒，模型蒸馏技术存在明显限制。同时，随着中国 AI 模型逐渐缩小与美国同类模型之间的差距，中国军事研究人员也开始关注模型蒸馏可能带来的安全风险。\n\n今年 1 月，中国人民解放军陆军工程大学研究人员发表一篇论文，探讨「无资料蒸馏」的威胁。这种方法可在无需直接取得模型核心参数的情况下，透过逆向工程方式推测并重建模型能力。\n\n为防范这类漏洞，研究人员提出防御机制，试图遮蔽模型公开输出中可能暴露的隐藏逻辑资讯。\n\n然而，经过蒸馏后的模型通常只能继承原始模型部分特定能力，无法完全复制尖端 AI 系统所具备的广泛智慧。\n\nAI 资料公司 Sapien 共同创办人 Trevor Koverko 表示，蒸馏模型的能力仍低于其作为「教师模型」的原始系统。\n\n他指出：「最好的理解方式，是将其视为把部分特定能力转移到成本更低、可在本地控制的系统中，而不是实现对尖端 AI 技术的真正自主化。」\n<div class=\"related-articles seo-links\">\n <h4>相关阅读</h4>\n <ul>\n <li><a href=\"/new/AI/article-9292.html\" title=\"参考港灵活杠杆框架！韩拟修法赋监管「紧急降杠杆权」 2倍ETF遇险可瞬降至1倍\">参考港灵活杠杆框架！韩拟修法赋监管「紧急降杠杆权」 2倍ETF遇险可瞬降至1倍</a></li>\n <li><a href=\"/new/AI/article-20562.html\" title=\"美国催设厂路透：SK海力士开出涉中国条件\">美国催设厂路透：SK海力士开出涉中国条件</a></li>\n <li><a href=\"/new/AI/article-4492.html\" title=\"华尔街解读韩半导体超大扩张：信号意义大于短期催化实际年增净产能仅个位数\">华尔街解读韩半导体超大扩张：信号意义大于短期催化实际年增净产能仅个位数</a></li>\n <li><a href=\"/new/AI/article-9521.html\" title=\"三大记忆体厂2027年产能提前售罄恐成史上最缺一年\">三大记忆体厂2027年产能提前售罄恐成史上最缺一年</a></li>\n <li><a href=\"/new/AI/article-10172.html\" 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