Cramer: Earnings season is when the data center bears got a dose of reality

By CNBC Television

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Key Concepts

  • Data center spending
  • AI infrastructure
  • Generative AI models
  • False narratives in the market
  • Earning season as a clarifying event
  • Nvidia's role in AI infrastructure
  • Data center bears vs. bulls
  • Vertiv, Cadence Design Systems, Supermicro
  • Microsoft and Meta's data center investments
  • Monetizing AI
  • Short selling and market bias

Data Center Spending Narrative and Correction

The speaker opens by stating his love for earning season because it exposes false narratives in the market. He focuses on the false narrative surrounding the end of data center spending, which began on "Deep Sea Monday" (January 27th) when a Chinese firm claimed to have created a generative AI model using fewer computing resources. This claim led to a sell-off of AI infrastructure stocks, including Nvidia. The speaker found this frustrating because there was no clear evidence to support the idea that the AI infrastructure thesis was flawed.

Sticking with the AI Infrastructure Thesis

Despite the market downturn, the speaker's firm stuck with the AI infrastructure stocks, believing that hundreds of billions of dollars would be spent on new data centers. He mentions an interview with Nvidia CEO Jensen Huang, who stated that demand for Nvidia's high-end chips was stronger than ever. The speaker felt like an "idiot" for remaining positive as the market continued to decline.

Earnings Season and the Vindication of the Bullish Stance

Earnings season proved the speaker's firm correct. Vertiv, a company that makes the "fiscal guts" of data centers (power control systems), reported a fantastic quarter on April 23rd, stating that its business had accelerated since the fourth quarter. They also mentioned a brimming order book. Cadence Design Systems, a big partner of Nvidia, also reported amazing numbers on April 28th.

Supermicro's Misdirection and Subsequent Reversal

On April 29th, Supermicro, another Nvidia partner, pre-announced weaker numbers, causing another sell-off in data center-related stocks. However, this proved to be a misdirection.

Microsoft and Meta's Continued Investment

The speaker highlights that Microsoft and Meta revealed they were continuing to spend big on data centers. Microsoft cited data center constraints, while Meta's Mark Zuckerberg stated that the investment was lucrative for monetizing Meta's AI site.

Amazon's AWS and Market Skepticism

Even though Amazon's AWS guidance was not well-received by Wall Street, the speaker believes they are not backing away from AI infrastructure spending. The speaker notes that the stocks he had been highlighting "bust out" after these announcements, making the previous "torture" worthwhile.

Examining the Media's Negative Coverage

The speaker questions why the media was so negative on the data center spending narrative. He wonders if they asked enough questions and why they didn't believe Jensen Huang. He suggests that some of the "bears" who were constantly interviewed had a bias rooted in shorting the AI complex. He believes that the potential for profit was too great for the bears to let facts get in the way of their narrative.

Continued Opportunity in the AI Infrastructure Complex

The speaker believes it's not too late to own members of the AI infrastructure complex, even though he expects the "bears" to return, citing Amazon Web Services' "light line." He accuses them of trying to make money at the expense of investors and wishes they would explain their negativity when the facts don't support it.

Conclusion

The speaker concludes by stating that there is always a bull market somewhere and promises to find it. The main takeaway is that the narrative of declining data center spending was false, and the market correction during earnings season validated the bullish stance on AI infrastructure stocks. The speaker also criticizes the media for perpetuating the false narrative, suggesting that bias and the potential for profit influenced their coverage.

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