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为什么人工智能泡沫将进一步膨胀?
AI bubble set to inflate further
There are several truisms when it comes to tech bubbles. One is that it’s often difficult to see one when you are inside it: each individual spending or investment decision can seem rational, even if the net effect looks extreme.
说到科技泡沫,有几个不言自明的道理。其中之一是,当你身处其中时,往往很难察觉到它:每个个人的支出或投资决策看起来都可能是合理的,即使总体效果看起来很极端。
When there’s general agreement that a bubble is forming, it often has much further to inflate and investors who bail early miss out. And after a bubble has burst, it can take years to work out whether it was just the product of hype or the precursor to an even bigger tech boom ahead.
当普遍认为泡沫正在形成时,它往往还有很大的膨胀空间,而提前退出的投资者会错失机会。而当泡沫破裂后,需要花费数年时间来判断它是炒作的产物还是更大的科技繁荣的前兆。
As US tech companies enter their latest earnings season, a distinct giddiness has started to creep into tech valuations on Wall Street. The middle of 2024 was always destined to be something of an “air pocket” for generative artificial intelligence. The investment boom triggered by the technology has been all too visible, but it takes time for all that new capacity to be put to productive use by the tech industry’s end customers. Wall Street’s patience is about to be put to the test.
随着美国科技公司进入最新的季度财报季,华尔街对科技估值开始出现明显的兴奋感。2024年中期一直注定是生成式人工智能的一个“空窗期”。由该技术引发的投资热潮已经非常明显,但科技行业的最终客户需要时间来充分利用所有这些新的能力。华尔街的耐心即将面临考验。
Software companies, which are best positioned to capture the value of the new technology by embedding it as features in their existing products, are struggling under a stock market cloud.
通过将新技术作为功能嵌入到现有产品中,软件公司处于捕捉新技术价值的最佳位置,但它们却在股市阴云下苦苦挣扎。
Nor has AI led to any compelling new services for consumers, even if Apple recently promised to sprinkle the technology liberally across its devices. For many people, discovering ChatGPT brought a frisson of interest. But unlike the first time they picked up an iPhone, used Google’s search box or found their friends on Facebook, it hasn’t changed their digital lives.
即使苹果(Apple)最近承诺在其设备上广泛使用这项技术,人工智能也没有为消费者带来任何引人注目的新服务。对许多人来说,发现ChatGPT带来了一丝兴趣。但与他们第一次拿起iPhone、使用谷歌(Google)搜索框或在Facebook上找到朋友的情况不同,它并没有改变他们的数字生活。
At best, this points to a lag in the widespread take-up of generative AI. At worst, it shows that the technology isn’t as transformative as tech companies have claimed. The longer the pause, the more glaring the gulf between investment boom and lacklustre end demand will become.
充其量,这表明生成式人工智能的普及进展缓慢。最坏的情况是,这表明技术并不像科技公司所声称的那样具有变革性。停滞的时间越长,投资热潮与乏善可陈的终端需求之间的鸿沟就越明显。
Accentuating this is the narrowness of the base on which this investment boom has been mounted. Nvidia said late last year that cloud companies — a market dominated by a handful of big players — accounted for more than half its sales of data centre chips. Any hint from the big tech companies during this earnings season that they are moderating their spending would deal a serious blow.
突显这一点的是投资热潮所依赖的基础狭窄。去年底,英伟达(Nvidia)表示,云计算公司(由少数几家大型企业主导的市场)占其数据中心芯片销售额的一半以上。在本财报季,如果大型科技公司暗示它们正在放缓支出,将对其造成沉重打击。
Yet as tech companies prepare to announce their latest earnings, all the signs are that the boom is still in full swing. Many business customers have barely begun their first pilot projects using the technology and will be increasing their testing of the technology in the coming months, even if it’s unclear what ultimate uses they will find for it. Pouring money into large language models and the infrastructure to support them has also become a strategic necessity for the big tech companies themselves. If machines that can “understand” language and images represent an entirely new computing platform, as many in the tech world expect, then all the big players will need a stronger foothold in the technology.
然而,随着科技公司准备宣布最新的收益报告,所有的迹象表明这个繁荣仍在全面发展。许多商业客户刚刚开始他们的第一个试点项目,使用这项技术,并将在未来几个月增加对该技术的测试,即使他们不清楚最终会用它来做什么。投入大量资金用于大型语言模型和支持它们的基础设施,对于大型科技公司来说也已经成为战略上的必要。如果能够“理解”语言和图像的机器代表了一个全新的计算平台,正如科技界的许多人所预期的那样,那么所有的大公司都需要在这项技术上有一个更强大的立足点。
It’s also worth noting that these companies have more than enough financial firepower to maintain and even escalate the battle. The combined operating cash flow of Apple, Microsoft, Alphabet, Amazon and Meta jumped 99 per cent in the past five years, reaching $456bn in 2023. That was more than enough to accommodate capital spending that ballooned by 96 per cent to $151bn.
值得注意的是,这些公司拥有足够的财力来维持甚至升级这场战斗。苹果、微软(Microsoft)、Alphabet、亚马逊(Amazon)和Meta的合并营业现金流在过去五年中增长了99%,达到了2023年的4560亿美元。这已经足够应对资本支出的增长,资本支出增长了96%,达到了1510亿美元。
Meanwhile, the next big product cycle for chipmaker Nvidia, based on its new Blackwell chip architecture, isn’t even due to begin until the second half of this year. The lower costs this promises for training and running large AI models have guaranteed a stampede from customers, even as demand for its earlier generation of chips remains strong.
与此同时,芯片制造商英伟达基于其新的Blackwell芯片架构的下一个重大产品周期,甚至要等到今年下半年才开始。这种承诺的低成本用于训练和运行大型人工智能模型,已经确保了客户的蜂拥而至,即使对其早期一代芯片的需求仍然强劲。
There’s a paradox here common to all new tech platforms. As the cost of using the new technology plunges, customers could theoretically get away with buying less. But rapidly falling costs usually lead to new uses being found, and demand instead soars. As with everything to do with generative AI, this is happening at warp speed, and it is hard to tell how closely this will mirror other disruptive tech cycles.
这里存在着一个对所有新技术平台都普遍存在的悖论。随着使用新技术的成本急剧下降,理论上客户可以少买一些。但是成本的快速下降通常会导致发现新的用途,需求反而飙升。就像与生成式人工智能有关的一切一样,这一切都以极快的速度发生,很难说这将如何与其他颠覆性技术周期相似。
At some point, of course, all of this investment has to earn a return. If not, then the chief executives who have been pushed by their boards and by fear of competition to demand their companies find uses for generative AI will eventually lose patience and move on. But all indications are that we’re not at that point yet.
当然,在某个时候,所有这些投资都必须获得回报。如果没有,那么那些被董事会和竞争压力推动,要求他们的公司找到生成式人工智能用途的首席执行官最终会失去耐心并离开。但所有迹象表明,我们还没有达到那个时候。