Reed’s view
Fear is rising that the AI bubble is about to burst under the weight of mounting debt, as my colleague Liz Hoffman detailed yesterday, including this great quote from an unnamed data-center financier: “We’re not an ATM for your dystopian future.”
Perhaps lenders have grown tired of funding the data center buildout, but money is not going to be the thing that finally causes the AI train to go off the rails. Everything is bottlenecked. It’s not just chips, memory, and EUV machines. It’s refrigeration units that cool the GPUs and the raw materials needed to make components, like glass.
If it weren’t for this bottlenecked supply chain, it’s likely AI revenues and user numbers would be growing much faster. Every time companies reach a new level of token efficiency, some new use case for AI is born that burns through ever more compute, proving Jevons Paradox. My favorite example of late: Decompiling video games to create mashups, something that used to take people years to do manually can now be done by AI in a weekend. It may be the thing that finally turns Gen-Zers into fans of AI.
The total addressable market of AI is roughly 100% of the earth’s population, and demand for it will continue to soar. The enterprise market has only dipped its toes into AI, and the consumer hasn’t even begun to dive in. Anthropic told investors this week that it’s making 85% gross margins. Even if that number is a gross exaggeration, this is a cash cow business. They’ll service their debt obligations, in other words.
I agree with the lender who lamented being an ATM for the AI industry, but probably for a different reason. Why would you want to lend money for measly interest payments when you could invest and get a massive return? There’s a reason hyperscalers and neoclouds reached for debt: It’s relatively cheap.
Notable
- Data center firms say that talent and power are two of the main bottlenecks challenging the AI buildout today, Bloomberg reported.