The Wealthiest Investors Can’t Get Enough of This Artificial Intelligence (AI) Stock

Artificial Intelligence (AI) was the word — or “words” — last year as investors piled into companies specializing in this hot technology. And for good reason. Today’s $200 billion AI market is forecast to reach a mind-blowing $1 trillion by the end of the decade, meaning companies and investors who get in early could score a major victory.

Why is AI stirring up such excitement? The technology has the potential to relieve humans of many tasks, helping people and companies gain in efficiency — and it can even lead to the development of game-changing products such as high-performance autonomous vehicles and new life-saving drugs. In recent times, companies powering, selling, or using this technology have seen their stock prices surge, gaining in the triple-digits and boosting the performance of all three benchmark indexes — the S&P 500, the Nasdaq, and the Dow Jones Industrial Average. These indexes each climbed in the double-digits last year.

Considering all of this, it’s no surprise that the wealthiest investors have been buying shares of AI stocks like hotcakes. In fact, semiconductor stocks are among the most popular tech stocks owned by billionaires, research by The Motley Fool shows. And the wealthiest investors can’t get enough of the following AI player…

Image source: Getty Images.

In a Motley Fool analysis of 16 hedge funds run by billionaires — including David Shaw’s D.E. Shaw & Co., Paul Tudor Jones’ Tudor Investment Corp., and Bruce Kovner’s Caxton Associates — Nvidia (NASDAQ: NVDA) is one of the most popular holdings. It appeared in the top 10 tech holdings of 10 of the funds last year. Other favorites included Alphabet, Meta Platforms, and Microsoft.

Why has Nvidia proven to be so popular among billionaires? Nvidia has something expert investors like, and that’s dominance it its field and a secure moat, or competitive advantage. Here are the details. This tech powerhouse makes the world’s fastest graphics processing units (GPUs), or chips that power key AI tasks like the training and inferencing of large language models (LLMs)….

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