Mashable 01月28日
DeepSeek could dethrone OpenAIs ChatGPT. Heres why
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中国AI公司DeepSeek以更低成本、更高定制化的开源产品,震惊了美国AI巨头,引发行业震动。DeepSeek的R1模型不仅成本低廉,效率更是美国顶级模型的50倍,一天之内就登顶应用商店榜首,导致英伟达市值大幅缩水。DeepSeek的成功挑战了美国在AI领域的领导地位,迫使美国公司重新审视其发展策略。文章指出,美国AI公司不能仅依赖保护主义政策,而应推出更具竞争力的开源产品,适应市场需求,否则可能面临被市场淘汰的风险。

🚀DeepSeek以开源模式和高效低成本的产品迅速崛起,打破了美国在AI领域的垄断地位,其R1模型在效率上远超美国同行。

💰DeepSeek的崛起对美国科技巨头,特别是英伟达造成了巨大冲击,其股价因DeepSeek的竞争而大幅下跌,也暴露了美国AI企业过度依赖高成本硬件的弊端。

🌱DeepSeek的开源模式为企业提供了更灵活的定制选项,并降低了AI的使用成本,这可能会改变整个AI市场的格局,使得更多企业可以低成本使用AI。

🌍文章强调,美国AI公司不能仅仅依赖保护主义政策,而应该积极拥抱开源和创新,推出更具竞争力的产品,适应全球市场对高效、低成本AI的需求。

A Chinese manufacturer just shocked a larger, complacent U.S. rival with a cheaper product that is significantly more customizable. News at 11.

In many industries, in the 21st century so far, this statement would not in fact be news; it would be such a familiar tale, few would bother mentioning it. But the old tale is noteworthy in this latest instance, thanks to the industry being Artificial Intelligence. Which, ironically, now seems to be an industry that was not very intelligent about obvious developments coming down the pike.

DeepSeek has taken off at a difficult time in the U.S., and not just politically. A divided country was just coming to grips with what AI means for business, for jobs, and whether the promised returns would be worth the investment that has been ploughed into (and by) U.S. companies. One thing few seemed to question was that a U.S. business would always be in the lead. No matter who was in or out, an American leader would emerge victorious in the AI marketplace — be that leader OpenAI's Sam Altman, Nvidia's Jensen Huang, Anthropic's Dario Amodei, Microsoft's Satya Nadella, Google's Sundar Pichai, or for the true believers, xAI's Elon Musk.

ChatGPT appeared to have a grip on the public imagination, and Altman seemed to be the most media savvy public face of the AI salesmen, so — presuming he could stop having weird feuds over celebrity voices and isn't found liable for allegedly abusing his sister — probably him?

Now here comes Liang Wenfeng, founder and CEO of DeepSeek, with a face so unknown there isn't even, at time of writing, a photo on his Wikipedia entry, nor does the mighty Getty archive contain any picture of him. (He did show up at a Beijing Symposium last week, should you want to know what he looks like.) DeepSeek doesn't swim in the media-facing, market-facing waters of the posturing U.S. AI giants. All it has is a better product — a faster, way cheaper product that fulfills a promise Altman forgot: It's open source.

And in the flattened world of the internet, turns out, that's all you need.

A day in the life of DeepSeek

One day, that's all it took. One day for DeepSeek to vault to the top of the app charts on Apple and Google. One day for Nvidia's Jensen Huang to lose nearly $21 billion of his net worth, thanks to the biggest single-day loss for any stock ever.

Reports that DeepSeek may have been partly trained on sanctions-busting Nvidia chips didn't stop the slide, because DeepSeek's secret sauce is that it simply doesn't need as much computing power as other Large Language Models. DeepSeek isn't just cheaper and more customizable, it is up to 50 times more efficient than the top U.S. models. Which could be good news for the environment, and bad news for Nvidia, let alone any U.S. tech giant which have been gearing up their data center budgets and massively overspending on Nvidia chips (in other words, pretty much all of them — except Apple, which has wisely put Apple Intelligence to work mostly on the device itself.)

"Nvidia has basically been getting rich selling shovels in the midst of a gold rush," AI expert Gary Marcus, one of the deepest skeptics of the U.S. AI approach, wrote as DeepSeek news poured in, "but may suddenly face a world in which people suddenly require far fewer shovels ... building $500 billion worth of power and data centers in the service of those chips isn't looking so sensible either."

Indeed, an increasing number of companies may be able to avoid paying for cloud-based AI services at all. At costs of pennies on the dollar, executives will be able to download an open-source LLM that can be customized to fit their database and data needs. It doesn't need to be the absolute fastest and smartest AI, it just needs to be competitive with the fastest and smartest — which DeepSeek's R1 model apparently is.

So what has ChatGPT, and by extension Altman, got on its side? Why, in this fast-moving tech consumer world, where a competitor is only an app store tap away, would anyone stick with the app they know? Sure, many will for a while, but relying on the inertia of your customer base in the face of close-to-free alternatives is a great way to ... become the next AOL. ChatGPT's fall from grace could arguably happen faster than its ascendency in 2022, which in itself was practically overnight.

Which is not to say that U.S. AI companies are sunk. After all, they have an ongoing cyberattack and a protectionist U.S. government in their corner. Today's Washington is willing to pass the CHIPS act to prevent Chinese companies from accessing the latest U.S. chip technology, which evidently did not work, but it is also willing to ban TikTok, the kind of blunt tool that would work to stunt DeepSeek's scary-fast growth. Suspicions over what China could do with all the U.S. customer data its companies are acquiring are rife, and can always be stoked.

But what are you going to do? Keep banning every Chinese LLM that undercuts a bloated U.S. rival? At a certain point, that's playing whack-a-mole, and it ignores the point. If the market wants a super-cheap, super-efficient open-source AI, then American companies need to be the ones who provide them.

If Altman doesn't release a supposedly superior GPT 5 soon, and if he doesn't want OpenAI to be heading for the kind of long-term decline that has affected so many haughty U.S. tech companies in the past, then he needs to join DeepSeek and Meta in the ranks of AI makers that release open-source products.

And maybe concentrating on the carbon footprint of your AI model — a pretty good proxy for how inefficient it is — isn't such a bad idea after all.

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