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Jim Cramer on why he remains bullish on data center growth

In this post:

  • Jim Cramer explained why data centers might still have potential in the market, even as investors are worried about Trump’s tariffs and overspending on AI.
  • The Mad Money host also pointed out that there was no concrete evidence yet to suggest a slowdown in the growth of AI infrastructure.
  • Cramer claimed Microsoft might just be starting to build fewer data centers on behalf of partner OpenAI despite pulling back on some of its early stage projects.

Jim Cramer, CNBC’s Mad Money host, explained why the data center theme might still have growth potential—even as investors struggled with Trump’s tariffs, the threat of recession, and possible overspending on AI. He noted that there were no signs the growth of AI infrastructure would slow down in the coming months. 

Cramer recently expressed his opinion on why the data center story was ‘very much alive and well,’ adding that he was still ‘trying to figure out how things got so twisted against this group,’ which he thought was ‘really incredible.’ He also mentioned that executives from Amazon and Nvidia previously denied that spending on data centers was on the decline.

Cramer was also encouraged by Microsoft, which he claimed may just be starting to build fewer data centers on behalf of partner OpenAI since the startup had already began raising funds. 

Cramer unravels why data centers still have room for growth

According to Jim Cramer, current market data suggested that big tech companies were still investing heavily in AI infrastructure despite the recent downturn in AI-related stocks. He referred to strong earnings results so far this season for companies connected to the data center sector, mentioning that Vertiv—which makes power and cooling equipment for the data center—easily surpassed estimates. 

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Cramer also revealed that GE Vernova managed ‘a substantial beat’, with the power company’s performance indicating that strong demand for data centers drove gas turbine sales and boosted its nuclear business. He further identified stocks in several AI buildout sectors, including semiconductor companies, data center builders, outfits responsible for servers and networking equipment, power utilities, climate control businesses, and industrials.

“These are very much cyclical companies, so you can’t just buy them if you think we’re headed into a recession … But if we get a reprieve on some of … these tariff issues and investors return to the AI trade, I just gave you everything that’s going to fly again.”

~ Jim Cramer

Cramer emphasized owning stocks from Broadcom, Arm Holdings, CoreWeave, Arista Networks, Cisco Systems, Constellation Energy, Vistra, Carrier Global, Trane Technologies, Cummins, and Dover if the data center theme grew strongly.

DeepSeek ignites fears of AI bust with low-cost language breakthrough

Investors grew concerned at the beginning of the year that the AI boom would turn bust after learning that Chinese startup DeepSeek developed a large language model that is purportedly as advanced as the dominant competitors but required much less energy and money. 

The revelation from DeepSeek reportedly triggered a ‘drastic shift in the tone of the market’ and sent AI stocks that had seen immense gains for the better part of a year plummeting—including AI giant Nvidia, which set a record by losing roughly $600 billion in a single session. Other AI stocks have also declined more recently as Wall Street continues to worry about the economic impact of President Donald Trump’s sweeping tariff policies and the potential for a recession.

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Microsoft CEO Satya Nadella said the DeepSeek new model was super impressive in terms of how they had “effectively done an open-source model” that did “this inference-time compute”and was ‘super-compute efficient’. Speaking at the World Economic Forum held in Davos, Switzerland, at the start of the year, Nadella emphasized that “We should take the developments out of China very, very seriously.

DeepSeek unveiled its free, open-source large language model (LLM) in late December, claiming that it took only two months and less than $6 million to build using reduced-capability H800s chips from Nvidia.

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Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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