Nathan Lambert：组织架构对训练好模型的价值被严重低估
Lambert 说训练模型没多少秘方，组织效率抵得上数倍算力，还拿 Llama 和 xAI 重组举例，观点很实在。
Nathan Lambert 重申其 18 个月前发表的 Interconnects 文章观点：组织架构和团队协作能力是训练 LLM 的关键因素。他以 Llama 和 xAI 的组织重组为例，说明低效团队会导致推倒重建。他认为训练模型没有太多秘方，大部分收益来自持续执行和合理分配算力，一个高效组织抵得上数倍算力的投入。
I think it's vastly underrated how important org chart and team functionality is to building a good LLM. Over 18 months old, and still one of my favorite all time Interconnects posts. It's why we still often see orgs crumble and need to get rebuilt (e.g. Llama/xAI) and why I believe underdogs can still catch up. Having an effective org and team is worth multiple multiples in compute.
I also think there isn't that much secret sauce to building models. Yes, sure there are some tricks, but most of the gains come from consistent execution and using your compute wisely.
