Shawn Wang推文
模拟是新的扩展定律：为什么我最终理解了 Smallville 和 Simile 的愿景
作者起初认为“模拟是新的扩展定律”只是营销夸张，但在采访中逐渐认真起来。他意识到，当模型自动化了大部分 ML 研究和 AI 工程后，最后的障碍是模拟人类和人类反馈。Smallville 当时没有商业应用，但 Simile 团队正在做这件事，并已在财富 100 强中找到产品市场契合。作者很高兴自己错了。
译文
我认为，说“模拟是新的扩展定律”很容易，把它当作营销夸张之词也很容易，但在这段采访进行到一半时，你能听到我从略带调侃的语气变得极其严肃。我晚了两年才意识到这一点，但终于明白了为什么@karpathy和@drfeifei会支持@joon_s_pk、@msbernst、@percyliang等人——当时的Smallville没有任何商业应用，但如果你认真对待RSI，从模型自动化ML研究和AI工程中越来越大的部分来看，最后的*障碍就是模拟人类和人类反馈，而Simile显然是做这件事的团队，即使在这么早的阶段，他们已经在财富100强企业中找到了产品市场契合度。我从未如此高兴自己当初的判断是错的。*或者说倒数第二个！:) 更多内容即将在Science播客上推出。
I think its easy to say "Simulation is a new scaling law" and treat it as marketing hyperbole, but midway along this interview you can hear me go from somewhat shitposting to very very serious. I am 2 years late to this but finally understand why @karpathy and @drfeifei backed @joon_s_pk @msbernst @percyliang et al - Smallville at the time had zero commercial applications, but if you take RSI seriously, from models automating increasingly large parts of ML research and AI engineering, the last* barrier is simulating humans and human feedback, and Simile is obviously the team to do this and already finding PMF at Fortune 100s even at this early stage. I've never been so happy to be so wrong. *or second last ! :) more soon on the Science pod