There's no escaping the hype surrounding AI these days. Promises of new developments like personal robot assistants and miracle cancer cures are everywhere as executives take every opportunity to tout their AI chips to enthusiastic investors and slightly less enthusiastic consumers.
However, not everyone has been blown away by the AI hype. James Ferguson, founding partner of UK-based macroeconomic research firm MacroStrategy Partnership, fears that investors' AI enthusiasm has created a concentrated market bubble reminiscent of the dot-com era.
“These historically end badly,” Ferguson told Bloomberg's Marine Somerset Web in the latest episode. Marine talks about money. podcast “So anyone who's a little bit long in the tooth and has seen something like this before is tempted to believe it's going to end badly.”
The veteran analyst argued that falsification—the tendency of large language models (LLMs) to invent facts, sources, and more—may prove to be a more complex problem than initially anticipated, leading to AI having There are very few viable applications.
“AI is still, I would argue, completely unproven. And fake it until you make it work in Silicon Valley, but for the rest of us. So, I think a double bite might be more appropriate for AI “If AI can't be trusted… then AI is effectively, in my mind, useless.”
Ferguson also noted that AI could become a cost-effective tool for many businesses because it is so “power hungry.” A recent study by the Amsterdam School of Business and Economics found that by 2027, AI applications alone could consume as much power as the Netherlands.
“Forget about charging Nvidia more for its chips, you also have to pay more to run those chips on your servers. And so you end up with something that's very expensive. And it has yet to prove, except in a few narrow applications, that it pays off.
For investors, particularly those leaning toward AI enthusiasm, Ferguson warned that excessive tech hype based on dubious promises is far from the period before the dotcom crash. Similar. He noted that during both of these periods, market returns were focused on tech stocks that traded on Wall Street's estimates of skyrocketing earnings growth.
But despite those lofty predictions, the dominant hardware giants of the dot-com era, Cisco and Intel, have largely disappointed investors since then. Ferguson argued that today's AI hardware hero, Nvidia, could face a similar fate, especially because of its high profile.
“If you think it can only have so many sales, no matter how high the growth rate is at the moment, if you think maybe it won't be a player in a decade's time, then What is the majority of Nvidia's sales?” Nvidia, he asked, could mean sales investors are paying about 40 times the current price tag.
Despite his argument that AI-related tech stocks like Nvidia are overvalued, Ferguson admits that no one can tell when the bubble will burst. According to the analyst, this dynamic makes many bearish investors feel “compelled to play” the markets, even when stocks look expensive, and that's a great way to get hurt.
“I mean, that's certainly what was happening at the dotcoms. [bubble]For example, where almost anybody who wasn't a retail punter was looking at these things and saying, 'Well, it can't go on, but saying, if it goes on a quarter more and I'm not playing, I'm like, 'I'm going to lose my job,'” he explained.
The good news, according to Ferguson, is that since the current stock market bubble is focused on AI-related stocks, there is still value to be found.
Of course, there will be massive pain for investors if the AI bubble bursts. But then, Ferguson recommends looking at currently unfavored U.S. small-cap stocks, which could benefit from interest rate cuts and are undervalued.
“There is so much value in America, the trouble is finding that value the good old-fashioned way, by hanging around in small caps and looking for businesses that are growing steadily, the good old-fashioned way. ,” They said. said.
This story was originally published on Fortune.com.