# Nathan Lambert：开源模型是能力扩散的关键底座

- 来源：Nathan Lambert (@natolambert)
- 发布时间：2026-09-26 04:47
- AIHOT 分数：42
- AIHOT 链接：https://aihot.news/items/cmuhfyzs604agrojn7rfo1qk1
- 原文链接：https://x.com/natolambert/status/2103587282188206286

## AI 摘要

Nathan Lambert 认为，RSI 不会是非黑即白的切换，开源模型栈才是能力在全球快速扩散的关键，若国家不掌控扩散底座，这些动态将远更难控制。他是在回应 @Shalev_lif 发布的超级智能网络防御战略 Secure Acceleration，该战略呼吁打造有竞争力的美国开源模型、将遏制列为国家安全优先事项，并在不影响 AI 发展的前提下保护前沿模型权重与 RSI。

## 正文

Too many people assume that as RSI kicks in, open weight models don't matter. In practice, RSI won't be a binary and the open-source stack becomes how many capabilities are rapidly diffused globally.

If you don't control the substrate of diffusion (open models) these dynamics are far less controllable as country.

I consider this a common blind spot of some safety oriented thinking.

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