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But DeepSeek’s breakthrough on cost challenges the “bigger is better” narrative that has driven the AI arms race in recent years by showing that relatively small models, when trained properly, can match or exceed the performance of much bigger models.
但是DeepSeek在成本方面的突破挑战了近年来推动AI军备竞赛的“越大越好”的叙事，它让人们看到，如果训练得当，相对较小的模型也可以达到或超过更大模型的性能。
That, in turn, means that AI companies may be able to achieve very powerful capabilities with far less investment than previously thought.
这继而意味着AI公司可能用比之前想象的少得多的投资来达到非常强大的能力。
And it suggests that we may soon see a flood of investment into smaller AI start-ups, and much more competition for the giants of Silicon Valley.
这表明我们可能很快就会看到大量投资涌入规模较小的AI初创企业，而硅谷巨头们将面临更多竞争。
(Which, because of the enormous costs of training their models, have mostly been competing with each other until now.)
（由于训练模型的成本巨大，到目前为止，基本上是巨头之间互相竞争。）
There are other, more technical reasons that everyone in Silicon Valley is paying attention to DeepSeek.
此外还有其他技术性原因使得整个硅谷都在关注DeepSeek。
In the research paper, the company reveals some details about how R1 was actually built, which include some cutting-edge techniques in model distillation.
在研究论文中，DeepSeek透露了关于R1实际建构方式的一些细节，其中包括模型蒸馏方面的一些尖端技术。
(Basically, that means compressing big AI models down into smaller ones, making them cheaper to run without losing much in the way of performance.)
（模型蒸馏基本上是指将大型AI模型压缩成较小的模型，使运行成本更低，而且不会在性能方面损失太多。）
DeepSeek also included details that suggested that it had not been as hard as previously thought to convert a “vanilla” AI language model into a more sophisticated reasoning model, by applying a technique known as reinforcement learning on top of it.
DeepSeek还在论文里包括了一些细节，表明将一个“平淡无奇”的AI语言模型转换为更精密复杂的推理模型并不像之前想象的那么困难，方法是在其基础上应用一种叫做“强化学习”的技术。
(Don’t worry if these terms go over your head — what matters is that methods for improving AI systems that were previously closely guarded by American tech companies are now out there on the web, free for anyone to take and replicate.)
（如果这些术语让你摸不着头脑，也不用担心，重要的是以前被美国科技公司严格保密的改进AI系统的方法现在已经在网络上公开，任何人都可以免费获取和复制。）
Even if the stock prices of American tech giants recover in the coming days, the success of DeepSeek raises important questions about their long-term AI strategies.
即使美国科技巨头的股价在未来几天内回升，DeepSeek的成功也引发了关于它们的长期AI战略的重要问题。
If a Chinese company is able to build cheap, open-source models that match the performance of expensive American models, why would anyone pay for ours?
如果一家中国公司能够打造出价格低廉、开源的模型，且其性能可与昂贵的美国模型相媲美，那么还有谁会为我们的模型买单呢？
And if you’re Meta — the only U.S. tech giant that releases its models as free open-source software — what prevents DeepSeek or another start-up from simply taking your models, which you spent billions of dollars on, and distilling them into smaller, cheaper models that they can offer for pennies?
如果你是Meta（唯一一家将其模型作为免费开源软件发布的美国科技巨头），有什么能阻止DeepSeek或其他初创公司直接拿走你花费数十亿美元开发的模型，并将其蒸馏成更小、更便宜的模型，然后以极低的价格提供给用户呢？
DeepSeek’s breakthrough also undercuts some of the geopolitical assumptions many American experts had been making about China’s position in the AI race.
DeepSeek的突破也削弱了许多美国专家对中国在AI竞赛中的地位所做的一些地缘政治假设。
First, it challenges the narrative that China is meaningfully behind the frontier, when it comes to building powerful AI models.
首先，它挑战了这样一种说法，即在构建强大的AI模型方面，中国远远落后于前沿。
For years, many AI experts (and the policymakers who listen to them) have assumed that the United States had a lead of at least several years, and that copying the advancements made by American tech firms was prohibitively hard for Chinese companies to do quickly.
多年来，许多AI专家（以及听取他们意见的政策制定者）一直认为，美国至少领先数年，而且中国公司要迅速复制美国科技公司取得的进步是极其困难的。
But DeepSeek’s results show that China has advanced AI capabilities that can match or exceed models from OpenAI and other American AI companies, and that breakthroughs made by U.S. firms may be trivially easy for Chinese firms — or, at least, one Chinese firm — to replicate in a matter of weeks.
但DeepSeek的成果表明，中国拥有先进的AI能力，可以与OpenAI等其他美国AI公司的模型相媲美或超越它们，以及对于中国公司——至少对于这一家中国公司——来说，美国公司取得的突破可能轻轻松松就可以在几周内复制。
