The Credit Crunch

This post is an adaptation of a prior post I made on my website. I'm interested to see what holes exist in the position that I'm missing. Epistemic Status: medium confidence. Within the next 6 months, most AI startups will not be able to buy compute. The world’s compute is "sold out". I put "sold out" in quotes, because in the current era, compute is rarely built speculatively. It's not like someone is sitting around with an idle cluster waiting for you to buy it. GPU clouds simply don't work like traditional clouds. In web servers, your customers are SaaS companies who are high-margin businesses. If the cloud raises prices on the SaaS company, the SaaS company isn't happy, but it doesn't go bankrupt. But if the GPU cloud raises prices on the AI lab, the lab may literally be unable to afford it, and thus they are truly price sensitive. When countless speculators deployed H100 clusters to sell on short term, on-demand contracts, customers did not suddenly decide to pay them the $6/hr their models assumed and a number of folks got wiped out. So in every subsequent generation, when you rent a cluster from a cloud, you're always buying a net-new cluster. The cloud takes your contract, goes to the bank, and the bank writes a loan based on the quality of your credit. However, it's becoming increasingly difficult to get capacity online for folks who are not "investment grade". Startups are not investment grade. So, to get capacity, they are asked to pay larger and larger upfront payments. We’ve seen it go as high as 100% of the contract paid up front, which was required because neither the lender nor the cloud could take on any additional credit risk. Meanwhile, investment grade tenants are rare. The few investment grade tenants that remain are getting increasingly downrated as they take on more and more debt and then turn around to sell to buyers of tokens who themselves are not investment grade. This is the credit bottleneck. We expect the investment grade buyers of G