Geoffrey Seiler, The Motley Fool
5 min read
The stock market got crushed on Thursday, Nov. 5, led lower by artificial intelligence (AI) semiconductor stocks. The pullback followed the U.S. midterm elections, in which Democrats captured both the House and the Senate, as well as key governorships in states like Texas and Pennsylvania. Following the results, many newly elected officials spoke out against the ongoing data center build-out, calling for a moratorium.
However, any further weakness in AI infrastructure stocks could pave the way for an incredible buying opportunity that could help make investors a fortune. Hyperscalers (owners of large data centers) and chip companies have already pre-emptively been planning for a potentially more difficult political environment. Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG), Microsoft, and Amazon have all been investing to expand their data centers overseas, and the backlash in the U.S. could increase this push. Meanwhile, companies are looking at the potential of moving data centers both offshore and into outer space. Earlier this year, China built the world’s first offshore wind-powered undersea data center, while SpaceX is aggressively pursuing plans to put data centers in space.
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AI companies are also exploring other ways to navigate the impending political shift in the U.S. Alphabet is teaming up with Bloom Energy on a self-sufficient AI data center with carbon capture that doesn’t use any grid power in the Republican stronghold of Wyoming. Meanwhile, Nvidia (NASDAQ: NVDA) is reportedly looking to buy and repurpose old telecom buildings into small data centers. These structures already have access to power and should face a lot less red tape in getting permits.
As such, just because the political climate has shifted against AI data centers, don’t expect the AI infrastructure build-out to suddenly slow down. With that in mind, let’s look at two AI chip stocks that could help make you a fortune on this pullback.
1. Nvidia
Nvidia remains the leading AI infrastructure company, as its graphics processing units (GPUs) are still the primary chips used to power AI workloads. The company has a wide moat in the training market, as most of the original AI code was written on its CUDA software platform and optimized for its chips. The company has also locked up the most future supply of high bandwidth memory (HBM), which all but assures it will maintain its leadership position.
