中文翻译
@luke_judges 没错，正是杰文斯悖论(Jevons Paradox)。如果成本下降，就会消耗更多的训练/推理资源。另外，我认为 Talaas 似乎被过度炒作了，但为小型静态模型进行硬件固化(hardwiring)确实非常酷。也许适用于边缘(edge)用例。但不适用于需要巨大吉瓦(GW)级功耗的前沿(frontier)模型。
· 供应链分析
杰文斯悖论致AI算力需求增，Talaas硬件固化适合边缘而非前沿模型。
英文原文
@luke_judges Yep spot on, jevons paradox. Just use up more training/inference if costs drops. Also my opinion is taalas seems overhyped but hardwriring a small static model is incredibly cool. Maybe for edge use cases. But not for frontier models which require enormous GW power usage.