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When a chief executive asks for trillions, not billions, when raising funds you know a sector may be getting a bit too hot.
当一位首席执行官在筹集资金时要求数万亿而不是数千亿，你就知道某个行业可能变得过热了。
In the long run, generative artificial intelligence will transform many industries and the way people work. But a report that OpenAI chief executive Sam Altman is talking to investors about an artificial intelligence chip project has raised a lot of questions.
从长远来看，生成式人工智能将改变许多行业和人们的工作方式。但是，OpenAI首席执行官萨姆•奥尔特曼(Sam Altman)正在与投资者讨论一个人工智能芯片项目，引发了很多问题。
A person familiar with the talks was cited as saying the project could require raising as much as $7tn. Scoring even a fraction of that figure — more than the combined gross domestic products of the UK and France — would seem a stretch, to put it mildly.
据一位熟悉谈判的人士称，该项目可能需要筹集多达7万亿美元。即使只能达到这个数字的一小部分，也将是一个巨大的挑战，姑且这么说吧，这个数字超过了英国和法国的国内生产总值之和。
Nonetheless, it reflects just how hot the interest in AI, and the chips that power it, has become. The historical parallel that record-high AI-related stock valuations and fundraising targets bring to mind is the boom and bust in telecom stocks during the dotcom bubble era.
然而，这反映出人工智能及其驱动力量的芯片的热度有多高。创纪录的人工智能相关股票估值和筹资目标所带来的历史类比，让人想起了互联网泡沫时代电信股的繁荣与崩溃。
Back then, investors had expected the internet to transform the world. Telecoms companies and hardware suppliers would then be big winners. The problem was the sector’s valuations were pricing in that transformation to come almost overnight. Now, a similar level of optimism is driving investment in AI-related companies.
当时，投资者曾期待互联网能改变世界。届时，电信公司和硬件供应商将成为大赢家。问题是，该行业的估值几乎在一夜之间就为这种转变定价。现在，类似程度的乐观情绪正在推动对人工智能相关公司的投资。
When the internet first became widely used, networking hardware was king. Servers needed to be built and connected using routers. Companies began building and buying hardware on the basis that extreme demand for servers would continue indefinitely. Telecom gear stocks such as Cisco surged more than 30-fold in the years to its 2000 peak.
当互联网首次被广泛使用时，网络硬件是王者。服务器需要使用路由器进行构建和连接。公司开始基于对服务器的极高需求将硬件建设和购买作为基础。思科(Cisco)等电信设备公司的股票在2000年达到顶峰时增长了超过29倍。
But the collapse of the telecoms industry came earlier than expected — taking just four years to go from boom to bust — and much faster than the internet changed our lives. Oversupply pushed more than 20 telecom groups into bankruptcy by 2002. Shares plunged.
但是电信行业的崩溃比预期要早——从繁荣到崩溃只用了四年时间——而且比互联网改变我们的生活速度更快。供应过剩导致2002年有20多家电信集团破产。股价暴跌。
Now, in the world of AI, chips are king. Thus, the rush for AI companies to own more of the chipmaking supply chain is understandable. As AI models become larger, more chips are needed. A continuing shortage adds urgency.
现在，在人工智能的世界中，芯片是王者。因此，人工智能公司争相拥有更多的芯片供应链是可以理解的。随着人工智能模型变得越来越大，需要更多的芯片。持续的短缺使情况更加紧迫。
Yet how long these shortages will last is debatable. It has been just two years since the world’s car industry was brought to almost a standstill because of a severe shortage of automotive chips. It took less than a year for that crunch to ease. Today, the supply of auto chips has not only normalised but many types are in a glut.
然而，这些短缺将持续多久还存在争议。距离全球汽车行业因为汽车芯片严重短缺而几乎陷入停滞，仅仅过去了两年。那次危机的缓解只用了不到一年的时间。如今，汽车芯片的供应不仅已经恢复正常，而且许多类型的芯片都供过于求。
The biggest risk of throwing too much cash, too fast, at AI chips is overcapacity. That is already a problem for older-generation chips. With the current sector downturn lasting longer than expected, Samsung had to slash production last year to deal with a deepening chip glut. Japanese peer Kioxia posted a record $1.7bn loss for the three quarters to December. Adding to this, more than 70 new fabrication plants are being built.
向人工智能芯片投入过多资金过快的最大风险是产能过剩。这已经是老一代芯片面临的问题。由于当前行业低迷的时间比预期更长，三星(Samsung)去年不得不削减生产以应对日益加剧的芯片供应过剩。日本同行西部数据(Kioxia)在截至12月的三个季度中录得创纪录的17亿美元亏损。此外，还有70多个新的制造工厂正在建设中。
Meanwhile, global silicon wafer shipments fell 14.3 per cent last year. Part of that is because of a cyclical downturn in the chip sector and a decline in demand for consumer electronics. But a slump in global chipmaking equipment billings, which fell more than a tenth in the third quarter, suggests future chip sector growth will remain at a more normalised level than what the AI boom has made us believe.
与此同时，全球硅片出货量去年下降了14.3%。部分原因是芯片行业的周期性下滑和消费电子需求的下降。但全球芯片制造设备的账单下滑超过十分之一，预示着未来芯片行业的增长将保持在比人工智能繁荣时期更为正常的水平。
Another problem is that chips quickly become commoditised. Take, for example, the older 40nm chips used in home appliances. These are hardly in short supply today, but they too were scarce, cutting-edge resources when they were launched in 2008. As capital equipment depreciates, the price of older-generation chips falls.
另一个问题是芯片很快变得普遍化。以家电中使用的旧的40纳米芯片为例。如今这些芯片并不短缺，但在它们于2008年推出时，它们也是稀缺的、尖端的资源。随着资本设备的折旧，旧一代芯片的价格也会下降。
Chips get faster and software more efficient every year. It took just two years for chips to upgrade from 7nm technology to the advanced 5nm used in the latest Nvidia chips. That rapid technological progress means companies may end up spending much less on chips in the future than they forecast today.
芯片的速度越来越快，软件也越来越高效。从7纳米技术升级到最新的英伟达(Nvidia)芯片所使用的先进的5纳米技术，仅用了两年的时间。这种快速的技术进步意味着，未来公司在芯片上的支出，可能会比他们今天的预测要少得多。
It is true there are clear differences between the dotcom era and the AI boom. For example, OpenAI’s revenues have already surpassed $2bn on an annualised basis, joining the ranks of tech’s fastest-growing platforms in history months after its launch. Today’s companies also have more ways to make profits.
确实，互联网泡沫时代和人工智能繁荣时期之间存在明显的差异。例如，OpenAI的年收入已经超过了20亿美元，成为历史上增长最快的科技平台之一。如今的公司也有更多的盈利方式。
But as with the early days of the internet, broader enterprise adoption of AI remains some way off. The transformation triggered by AI may take many years longer than today’s stock prices and funding expectations suggest. Hype and overinvestment are a dangerous combination. The way to avoid a similar fate to overhyped peers from the 1990s is to remember history repeats.
然而，就像互联网的早期一样，企业广泛采用人工智能还有一段时间。人工智能引发的转型可能比今天的股价和资金预期所暗示的时间要长得多。炒作和过度投资是一种危险的组合。避免与20世纪90年代被过度炒作的同行遭遇类似命运的方法，是记住历史会重演。
