AI: Where Will the Money Come From?

AI: Where Will the Money Come From?

AI: Where Will the Money Come From?
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“A billion here, a billion there, and pretty soon you’re talking about real money.”
- Commonly attributed to Sen. Everett Dirksen, although the saying was often used before.

The quote above now seems quaint. I’m sure that many of us can remember when a billion dollars was an unfathomable amount of money. And in one sense, it still is. It’s hard for the human mind to get around the concept of the billion. A trillion dollars? We throw the word around every day, not realizing that $1 trillion is 1 million millionaires.

It would take 11 days and three hours to count to 1,000,000 one second at a time. It would take 31,700 years to count to a trillion.

Berkshire Hathaway has over one third of $1 trillion in cash ($365 billion). We just saw the first trillion-dollar ETF (Vanguard). SpaceX went public for $1.7 trillion. OpenAI and Anthropic both plan trillion-dollar IPOs. There are 10 companies in the S&P 500 worth over $1 trillion with another four in shouting distance. The equity raises we are seeing are simply staggering the mind. We are going to talk about AI and capital needs: who will get it and who won’t? And the critical question: what will that mean for your portfolio?

But first, and quickly, at the end of the letter I will be talking about the longevity and health webinar that is actually scheduled for October 24, which may be going on while you read this. No worries, you can still listen to or read each of the sessions. Just sign up below. And note that after this I will not be mentioning Lifespan Edge for a very long time, if ever. If you want to follow my longevity journey in a separate format, just click on the link. Now let’s think about AI.

AI: Where Will the Money Come From?

Gemini tells me that the US is on pace to invest $6.7 trillion in data centers by 2030, with $5.2 trillion being AI-specific capacity. The four major AI companies (Microsoft, Amazon, Alphabet and Meta) are expected to be about half of that. Anthropic and OpenAI and SpaceX are all making massive investments.

That is in a world that must fund trillions of dollars of sovereign debt not just in the US but all over the world. Plus, other “normal” business investments which will be even more hundreds of billions, if not trillions. And that brings us to the thrust of today’s letter: who will get access to this money and what are the returns going to be?

First off, there are several types of AI companies. Some use the compute power, some build it and rent it out, some are hyperscalers and cloud providers, some are enormous and some are startups. Their needs and long-term viability are completely different.

First off, the trillion-dollar hyperscalers like Microsoft, Amazon, Meta or Google are not going to have problems raising money. Their debt is investment grade, and they generate collectively $380 billion in free cash flow per year. They are taking that and investing it into AI capital expenditures and borrowing additional money as well. This may impair their future profits for a period of time, but these are massive companies and they can take a “short-term” hit. It will likely affect their share price, but we don’t know whether the market will see that as positive or negative yet. And different companies will have different characteristics and price volatility.

And then there are the “neo clouds.” In the AI world, neo clouds refer to specialized cloud infrastructure providers that focus on delivering AI infrastructure, particularly GPU-as-a-Service (GPUaaS). These providers are designed to meet the demanding AI workloads of enterprises, model builders, and hyperscalers by offering high-performance computing capabilities. The term "neo" is used to describe a new generation of cloud providers that are built specifically to support AI workloads, offering a different approach to cloud computing than traditional hyperscalers. Neo clouds are built around accelerated computing, GPU infrastructure for AI training, fine-tuning, and inference, and they cater to the unique needs of AI workloads, which require dense compute, high-bandwidth networking, fast storage, and carefully engineered interconnects.

Note that these are essentially leasing companies, investing in real estate and GPUs and leasing or renting them out to larger hyperscalers. These Neo clouds use the rental agreement to finance the data centers, but the income doesn’t typically start until they are finished, so there are massive upfront costs that must be borrowed or raised as capital from the market.

This was all fine and good last year. Now investors are beginning to question the potential profitability of the Neo clouds, like CoreWeave, which we touched on last week. Right now, the credit default swap market is projecting a 55% chance that CoreWeave defaults on some of its credit. Basically, if you want to lend money to CoreWeave and hedge it, you must spend $5.5 million to hedge your $10 million loan over five years. That of course makes the interest rate that CoreWeave pays go through the roof. They are now basically junk bonds.

coreweave

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