问HN：大型语言模型（LLMs）应该如何用于战争？
我最近在一个HN讨论串中问了同样的问题，但这个问题神秘地被投了反对票。对我来说，这个问题依然存在：Anthropic和DOW之间有很多关于将大型语言模型（LLM）技术应用于战争的讨论。具体来说，是关于“完全自主武器和大规模国内监控”。有没有人理解这两个目标如何实现？我觉得LLM似乎并不是合适的工具。自主武器需要一种更快、更可靠且更确定性的人工智能。LLM可能更适合用于大规模监控，但我不太确定它们如何处理海量的数据和有限的上下文窗口（除非它们使用数据本身进行训练）。RAGs可能只能缓解这个问题。有没有人有一些想法？
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I have recently asked the same question in a HN thread, which was mysteriously downvoted. The question remains to me: there is a lot of talk between Anthropic and the DOW about adopting LLM technology for warfare. Specifically, for "fully autonomous weapons and mass domestic surveillance". Does anyone understand how these two goals can be achieved? LLMs don't seem to me the right tool for this. Autonomous weapons would require a much faster and much more reliable and deterministic AI. LLMs might be a better use for mass surveillance, but I am not really sure how they would cope with the massive amount of data and the limited context window (unless they use the data itself for training). RAGs might only mitigate the problem. Does anyone have some ideas?