探讨大模型在军事领域的应用潜力与实现路径
On the Military Applications of Large Language Models
- 用GPT类模型自检其军事应用可能性
- 验证云服务可快速构建可行军事应用
- 总结生成与摘要能力对军事场景的直接价值
本文探讨自然语言处理与大语言模型在军事领域的应用及实施方式，这些模型因生成式预训练变换器（GPT）的出现及OpenAI对ChatGPT等基础模型的大规模预训练而广受关注。首先，我们通过基于GPT的语言模型（如Microsoft Copilot）自问其潜在军事用途，并对其回答进行批判性评估。其次，研究商业云服务（如Microsoft Azure）如何被便捷用于构建此类应用，并评估其可行性。结果表明，语言模型的摘要与生成特性可直接支持多种大规模军事应用，其他功能则可能在特定场景中发挥作用。
原文摘要 · Abstract (English)
In this paper, military use cases or applications and implementation thereof are considered for natural language processing and large language models, which have broken into fame with the invention of the generative pre-trained transformer (GPT) and the extensive foundation model pretraining done by OpenAI for ChatGPT and others. First, we interrogate a GPT-based language model (viz. Microsoft Copilot) to make it reveal its own knowledge about their potential military applications and then critically assess the information. Second, we study how commercial cloud services (viz. Microsoft Azure) could be used readily to build such applications and assess which of them are feasible. We conclude that the summarization and generative properties of language models directly facilitate many applications at large and other features may find particular uses.
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