The Maddening "Ground Hog Day" Markets Pt 2
Ever since Artificial Intelligence (AI) was introduced to the public with OpenAI’s unveiling of its ChatGPT Large Language Learning Model (LLM) in November 2022, AI has been the dominant investment theme: AI-related stocks have accounted for 75% of market gains, 80% of corporate profits, and 95% of capital expenditures.
Put simply, the bull market in stocks that began at the end of 2022 has effectively been one gigantic bet on AI.
It’s critical to note that this “bet” is primarily on AI’s potential as opposed to any actual results (to date, AI has yet to result in a large-scale boost to corporate productivity or corporate profits). And this is not a small bet: trillions of dollars in capital are being allocated based on this.
There’s a second major issue that further complicates this situation: over 98% of Wall Street has little to no understanding of the actual technology behind AI. These are financial guys trying to model extremely sophisticated technology and its potential future economic implications.
In its simplest rendering, you have people who don’t really understand technology allocating trillions of dollars in capital based on a new, complicated technology that is currently being introduced throughout corporate America with varying degrees of success (while over 90% of Fortune 500 companies have introduced AI to their operations, only 39% have seen a measurable impact on operating profits).
If this situation sounds fragile to you, you’re not wrong. With so much riding on the potential of something, and so few players in the space actually understanding the technology behind that potential, any “bump in the road” for the AI revolution will result in significant market volatility.
In the last four years, there have been no shortage of “bumps”. Some of the larger ones were:
- China’s DeepSeek introducing an LLM that appeared to run on fewer chips, suggesting that Nvidia (the largest company in the world) would have less business.
- Alphabet introducing an LLM that ran on its own chips instead of Nvidia’s.
- Quarterly results for multiple AI-related hyperscalers (Oracle, Meta, Microsoft) suggesting that the companies were spending too much building out their AI-networks.
- OpenAI, Nvidia, and other AI-related companies signing “circular deals” through which they invest in AI startups which then use the capital to buy OpenAI/Nvidia/etc.’s services.
- Concerns pertaining to the accuracy of AI models (hallucinations, hive mind/ group think).
In the last two weeks, the AI story ran into a major “bump” when a report from Bloomberg suggested that Meta (META) would be launching a cloud service to rent out its surplus AI infrastructure.
META has been one of, if not THE single biggest player in the AI buildout. In the last three years, META CEO Mark Zuckerberg:
- Spent roughly a quarter TRILLION dollars on META’s AI buildout.
- Poached numerous AI experts from other tech firms, offering compensation packages of eight or even nine figures.
- Made its largest ever deal ($14 billion) to bring Alexandr Wang over from Scale AI to lead its Superintelligence Labs effort.
In simple terms, META has been extremely aggressive in its AI buildout efforts. In this context, the fact that META is now stating that it has surplus AI infrastructure suggests the company has overestimated the actual demand for its AI services. Given how important META has been as an AI hyperscaler, this has very negative implications for AI demand as a whole.
AI-related companies, particularly those involved in AI infrastructure (Coreweave, Nebius, Micron Technology, Marvell Technology, etc.) collapsed 5%-10% in a single day. The carnage didn’t stop there: many AI-companies are down 20%-50% in the last week and a half.
What’s stunning about all of this is that it’s not clear that the Bloomberg report was even accurate. Yesterday, Meta announced that it is breaking ground on a 1-GigaWatt data center in Canada and that it intends to DOUBLE its computing capacity.
Meta is building its first big Canadian data center as AI expansion crosses the border
Meta’s AI expansion is heading north of the border.
The company said in a blog post on Wednesday that it’s building its first data center in Canada, a 1 gigawatt facility in the province of Alberta that will cost Meta about $9 billion and take two to three years to construct. It’s Meta’s 33rd data center overall and the latest in the company’s effort to rapidly build out to meet demand for artificial intelligence infrastructure and services.
Meta to put AI chip into production in September as it looks to double computing capacity, memo shows
Meta Platforms (META.O), opens new tab plans to start manufacturing an artificial intelligence chip from September as part of its plan to boost overall computing power to 14 gigawatts next year, showed an internal memo reviewed by Reuters…
Meta this year plans to deploy seven gigawatts of computing infrastructure, the memo showed. It plans to double that number in 2027, the memo said.
The firm expects to spend as much as $145 billion on AI infrastructure this year, a significant portion of Big Tech's more than $700 billion projected outlay on the technology.
Let me ask you… why would Meta be DOUBLING its compute power over the next year if current compute demand is so low that it already needs to start renting out its spare capacity?
Put another way… did someone “plant” the Bloomberg story about Meta’s cloud service as a means of hurting the company? I don’t know. But the fact this story was published in the very China-friendly Bloomberg and Meta rapidly leaked an internal memo that defies it raises plenty of questions.
The point I’m trying to make here is that once again, the AI story is hitting a “bump in the road.” And because so much of the market is weighted towards tech (AI/ Big Tech/ Mag-7 stocks account for 36% of the S&P 500’s weight), this is causing some volatility.
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Graham Summers, MBA
Chief Market Strategist
Phoenix Capital Research