Nathan Lambert：数据中心放缓后，算法效率加速可能接棒
精选理由
Lambert 猜测算力放缓后效率提升会接棒，还引了 METR 的 AECI 数据，关心 scaling laws 的人可以看看。
Nathan Lambert 在推文中提出，大选后数据中心建设可能放缓，通过算法效率提升继续推进 AI 的路径显得更可行。他引用 METR 近期报告中 AECI（算法效率）加速的趋势作为佐证，并认为编程智能体和推理计算的改变正在抵消 scaling laws 中指数级增长的算力需求。他也强调这并不意味着加速必然持续。
原文 · Nathan Lambert
With the data center slowdown coming after the election, I find this post increasingly likely. There’s way more incentive in a path that seems eminently doable. I consider this in line with the acceleration in AECI from the recent METR report. Coding agents and inference compute changes how we work — giving an acceleration in our battle against scaling laws’ exponentials. It doesn’t mean more accelerations are inevitable.
https://t.co/lufhvZ4NXd
