第2878期:The US should avoid lagging behind China in AI

But China discounts energy costs for a chip company by 50%. That's right. They provide free transportation for employees to come out to the factory.但中国会将芯片公司的能源成本打五折。没错。他们还为员工提供免费的上下班交通，让他们去工厂。That's right. I mean, you don't, you can't do that. Our energy cost is more expensive than theirs in the first place.没错。我的意思是，你不能、也做不到这样。首先，我们的能源成本本来就比他们贵。Absolutely. And then they discount it 50%. And so it's probably, we'll probably call it four to eight times the cost.确实如此。然后他们再打五折。所以我们这边的成本可能要高出四到八倍。So tell me, how do you feel about this great competition with China? I mean, the government is putting enormous resources underneath their champion. We don't do that in this country. You know, how do you feel about that?那么告诉我，你怎么看待与中国之间的这场激烈竞争？我的意思是，中国政府在他们的“冠军企业”背后投入了巨大的资源。而在我们国家，我们不会这么做。你怎么看？Well, before I get there, don't let me not answer that question. I'm dying to answer it. But let me handicap the next two layers.好吧，在我回答之前，你别担心，我一定会回答这个问题，我非常想回答。但让我先分析接下来的两个层面。The model layer, the model layer, United States frontier models, our frontier models are unquestionably world class.首先是模型层，模型层。美国的前沿模型，我们的前沿模型毫无疑问是世界一流的。We are probably, call it six months ahead. However, out of the 1.4 million models, most of them are open source. China is well ahead, way ahead on open source.我们大概领先六个月左右。然而，在全球 140 万个模型中，大部分是开源的。而在开源领域，中国遥遥领先，领先得非常明显。Now, the reason why open source is so important is because without open source, startups can't thrive, university researchers can't do research, you can't teach AI, scientists can't use AI.开源之所以如此重要，是因为没有开源，初创企业无法发展，大学研究人员无法研究，你无法教授 AI，科学家也无法使用 AI。Basically, all of the industry around your economy have no ability to fundamentally advance themselves unless you have open source. Without Linux, where would we be? Without Kubernetes, without PyTorch, all of these different types of technologies that made AI thrive are all open source.基本上，除非有开源，否则你经济中的各行业都无法从根本上取得进步。没有 Linux，我们会在哪里？没有 Kubernetes，没有 PyTorch？所有让 AI 繁荣发展的这些技术全都是开源的。They are well ahead of us on open source. And then the layer above that, applications.他们在开源上远远领先我们。接下来，在更上层的是应用层。If you were to do apollof their society and ours, and you ask them, is AI likely to do more good than harm? They're going to say, in their case, 80% would say AI will do more good than harm.如果你在他们的社会和我们的社会做一个调查，问大家：AI 是“利大于弊”还是“弊大于利”？在他们那边，可能有 80% 的人会说 AI 利大于弊。In our case, it'd be the other way around. And so that tells you something that's very, very important.在我们这边，结果则完全相反。所以这说明了一个非常非常重要的事情。Socially, socially, we need to be careful not to describe AI in these science fiction movie ways of describing AI and causing people so much concern.在社会层面上，我们必须谨慎，不能用科幻电影那种方式去描述 AI，导致公众产生巨大的恐惧。We want to be concerned, but we also want to be practical. AI is about automation.我们当然应该保持关注，但也要保持务实。AI 本质上是关于自动化的。And that area, I think that we need to be careful not to fall behind in the application and the diffusion of AI, because in the end, whoever applies the technology first and most wins that industrial revolution.而在这个领域，我认为我们必须小心，不要在 AI 的应用与普及方面落后。因为最终，谁最先、最多地应用这项技术，谁就会赢得那场工业革命。As you know, electricity was invented in the UK, but the United States applied it faster, more broadly, and as a result, look where we are.你知道，电是英国发明的，但美国更快、更广泛地应用了电力技术，因此看看我们今天的发展。And so we have to be a little mindful. And so anyways, I just handicapped that stack.所以我们必须有所警惕。总之，我刚才对这个技术栈做了整体分析。And I don't think it's—it's important when you're looking at AI not to see it as a holistic thing. It's really not about ChatGPT versus DeepSeek.我不认为——重要的是，当你看待 AI 时，不要把它当成一个整体。它并不是 ChatGPT 对 DeepSeek 的简单对比。You have to look at it across all of the stacks and across all of the industries.你必须从所有技术层、所有产业层面去看它。Does that make sense? It's a little bit more complicated than one simple answer.这样说有道理吗？这件事比一个简单的回答要复杂得多。