Diversify your AI plays — these are the best alternatives to Nvidia, fund managers say
Nvidia may have enjoyed a red-hot run on the back of the artificial intelligence craze, but many other tech stocks have also benefited. As with any investing theme, diversification is needed. Veteran tech investor Paul Meeks told CNBC Pro that even if Nvidia is a “great story,” it’s “too risky to be in just one” when it comes to AI. Tech giants and semiconductor stocks have captured the attention of investors, given that chips and other systems are needed for the infrastructure expansion of the initial AI phase. CNBC Pro speaks to fund managers to find out the best alternatives to Nvidia that investors can consider. Semiconductors Jordan Cvetanovski, portfolio manager at Sydney-based Pella Funds Management, named Taiwan’s TSMC and Dutch firm ASML as two stocks to buy. Both are listed in the United States. Cvetanovski, who manages the Pella Global Generations Fund, says TSMC is a good way to play growth in tech and AI in particular. “TSMC is arguably one of the cheapest technology companies out there. We don’t have to believe in huge growth numbers to justify their valuation,” he said. “We think it’s a wonderful business, 100% dominant basically and they’ll continue to be dominant.” ASML will also continue to benefit “because without ASML there’s no TSMC, without TSMC there’s no Nvidia,” Cvetanovski said. ASML has a monopoly on EUV lithography machines, which are needed to make advanced processor chips. All three stocks are interdependent: The U.S. chipmaker depends on TSMC to manufacture its graphics processing units. TSMC, in turn, uses machines made by ASML to make the most advanced semiconductors. Cvetanovski believes that Nvidia will continue to dominate the chip industry despite competition from players such as Advanced Micro Devices . Ray Wang, principal analyst and founder of Constellation Research, also named TSMC, saying that it “always wins.” He also believes that AMD will “come close.” A data center play Data centers are also set to benefit from AI, the applications of which are very power-intensive. Cvetanovski named Vertiv as a beneficiary. “AI requires … more data centers, all this demand will require more data centers, more sophisticated cooling systems and all kinds of other things that go with AI investing,” he said. Vertiv is experiencing growth of 10% to 12% and more growth “is still not a huge hurdle for them over the next three to five years,” Cvetanovski said. Super Micro Computer Meeks, who is co-chief investment officer at Harvest Portfolio Management, says Super Micro Computer is his favorite alternative AI stock to play right now. As AI is still in the infrastructure buildout phase, AI products are set to come only in 2025 or 2026, he said. “So with that thesis Super Micro makes customized servers that are used by AI customers, so it uses Nvidia’s chips in their servers and as [Super Micro] sells their servers to folks like Microsoft, and then they put them in a data center. And so Super Micro has done a pretty good job of transitioning its focus to AI customers.” The stock has risen astronomically since last year , but Meeks continues to believe that it and Nvidia will continue to beat earnings estimates. “And as long as they continue to beat the analyst numbers, you know, the stock should rise … Because Wall Street is … what you do versus the expectation,” he told CNBC Pro last week. Big Tech Investors should also own Big Tech stocks that are building their AI businesses, such as Amazon, Alphabet , Meta and Microsoft , according to Meeks. Those would be the main infrastructure plays, as cloud data centers — which these tech giants have — will be needed to train and run AI models, he said. Meeks compared the current stage to the formation of the internet. “The guys that made all the early money were companies like Cisco because they provided the networking for the internet. At that time in the late 90s, America’s largest market cap was Cisco because it was doing the plumbing of the internet.” Many investors want new exciting ideas to buy into but in this case, the “strong gets stronger,” he said. “You want to be with the established companies because they will benefit the most from AI because they can spend the money,” he said, adding that building AI infrastructure is extremely expensive. The next Nvidia? Wang of Constellation Research didn’t only name tech giants like AMD, Amazon and Meta — he also named some startups. The next Nvidia could be a few companies that are specialized in the tensor processing unit space that Google pioneered, he said. These are AI accelerator application-specific integrated circuits developed by Google for neural network machine learning, using Google’s own TensorFlow software, he explained. One name he highlighted is OpenAI CEO Sam Altman’s TPU startup, Tigris. He also named Groq, a Google-funded startup developing custom AI chips for running models.
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