the compute-rich can copy the compute-poor, especially if their models are open — there's a reason why big AI labs still follow the academic literature.
【论证自相矛盾】作者在「溢出效应对算力贫方没有不对称优势」的论点中，援引「大实验室也跟踪学术文献」作为证据。但这恰恰说明算法知识的流动是双向的——如果如此，为什么算力贫方的「复制」会被贬低，而算力富方的「跟踪学术」就被当作平衡因素？同样的机制被选择性地用来支持不同的结论。
These could lead to especially large and fast spillovers if there are "four minute mile" effects — after one AI lab makes a breakthrough, other labs realise they can do it too, so they pour effort into reimplementation.
「四分钟一英里」效应是这篇文章最具洞察力的概念引入：1954 年 Roger Bannister 打破四分钟壁垒后，短短 46 天内就有人复制了这一成就——因为大家终于知道「这是可能的」。AI 领域同样如此：o1 发布后，多家实验室在数月内推出了推理模型。这说明知识壁垒有时比技术壁垒更高——知道「能做到」本身，就是最有价值的信息。
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