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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.
當一位首席執行長在籌集資金時要求數萬億而不是數千億，你就知道某個行業可能變得過熱了。
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.
從長遠來看，生成式人工智慧將改變許多行業和人們的工作方式。但是，OpenAI首席執行長薩姆•奧爾特曼(Sam Altman)正在與投資者討論一個人工智慧晶片項目，引發了很多問題。
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.
據一位熟悉談判的人士稱，該項目可能需要籌集多達7兆美元。即使只能達到這個數字的一小部分，也將是一個巨大的挑戰，姑且這麼說吧，這個數字超過了英國和法國的國內生產總值之和。
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，這反映出人工智慧及其驅動力量的晶片的熱度有多高。創紀錄的人工智慧相關股票估值和籌資目標所帶來的歷史類比，讓人想起了網路泡沫時代電信股的繁榮與崩潰。
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.
當時，投資者曾期待網路能改變世界。屆時，電信公司和硬體供應商將成爲大贏家。問題是，該行業的估值幾乎在一夜之間就爲這種轉變定價。現在，類似程度的樂觀情緒正在推動對人工智慧相關公司的投資。
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.
當網路首次被廣泛使用時，網路硬體是王者。伺服器需要使用路由器進行構建和連接。公司開始基於對伺服器的極高需求將硬體建設和購買作爲基礎。思科(Cisco)等電信設備公司的股票在2000年達到頂峯時成長了超過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.
但是電信行業的崩潰比預期要早——從繁榮到崩潰只用了四年時間——而且比網路改變我們的生活速度更快。供應過剩導致2002年有20多家電信集團破產。股價暴跌。
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.
現在，在人工智慧的世界中，晶片是王者。因此，人工智慧公司爭相擁有更多的晶片供應鏈是可以理解的。隨著人工智慧模型變得越來越大，需要更多的晶片。持續的短缺使情況更加緊迫。
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，這些短缺將持續多久還存在爭議。距離全球汽車行業因爲汽車晶片嚴重短缺而幾乎陷入停滯，僅僅過去了兩年。那次危機的緩解只用了不到一年的時間。如今，汽車晶片的供應不僅已經恢復正常，而且許多類型的晶片都供過於求。
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.
向人工智慧晶片投入過多資金過快的最大風險是產能過剩。這已經是老一代晶片面臨的問題。由於當前行業低迷的時間比預期更長，三星(Samsung)去年不得不削減生產以應對日益加劇的晶片供應過剩。日本同行西部數據(Kioxia)在截至12月的三個季度中錄得創紀錄的17億美元虧損。此外，還有70多個新的製造工廠正在建設中。
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.
與此同時，全球矽片出貨量去年下降了14.3%。部分原因是晶片行業的週期性下滑和消費電子需求的下降。但全球晶片製造設備的賬單下滑超過十分之一，預示著未來晶片行業的成長將保持在比人工智慧繁榮時期更爲正常的水準。
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.
另一個問題是晶片很快變得普遍化。以家電中使用的舊的40奈米晶片爲例。如今這些晶片並不短缺，但在它們於2008年推出時，它們也是稀缺的、尖端的資源。隨著資本設備的折舊，舊一代晶片的價格也會下降。
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.
晶片的速度越來越快，軟體也越來越高效。從7納米技術升級到最新的輝達(Nvidia)晶片所使用的先進的5納米技術，僅用了兩年的時間。這種快速的技術進步意味著，未來公司在晶片上的支出，可能會比他們今天的預測要少得多。
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.
確實，網路泡沫時代和人工智慧繁榮時期之間存在明顯的差異。例如，OpenAI的年收入已經超過了20億美元，成爲歷史上成長最快的科技平臺之一。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，就像網路的早期一樣，企業廣泛採用人工智慧還有一段時間。人工智慧引發的轉型可能比今天的股價和資金預期所暗示的時間要長得多。炒作和過度投資是一種危險的組合。避免與20世紀90年代被過度炒作的同行遭遇類似命運的方法，是記住歷史會重演。
