AI is collapsing the cost of cognitive labor. The innovations and macroeconomic phenomena that are causing these changes are noisy and obscured in the information silos of the modern world. This is the most significant macroeconomic shift since the 1970s offshoring of manufacturing. There are implications across software, energy, and monetary systems.
Inputs
To train models and do inference on trained models you of course need GPUs. The GPU market is wildly inefficient and because there is not really a GPU battery (you can kind of argue bitcoin is), a lot of compute is wasted. Traditionally when a company wants to get a bunch of GPUs to train a new model or serve inference, their only option was to get a long term contract. These contracts normally are many millions of dollars and for long periods of time.
The data centers prefer this for the same reason a landlord prefers a long term lease as opposed to month-to-month: it reduces risk. When you build a data center everything is a cost of capital game, you take out a loan based on a depreciation curve of the GPUs. Initially all the revenue is just paying back the loan, then everything is electricity and premium. Data centers in general don't want to hold onto the GPUs because they depreciate in value, unlike say a home. Thus the customer is often left holding the bag, unable to fully saturate the cluster and required to make these large payments. We at SF Compute built a liquid GPU spot market in attempt to solve these problems.
There is much more to be said about the material and energy inputs to manufacturing chips and running clusters (more on that later). But the low hanging fruit is improving GPU utilization.
Outputs
Over the past several decades software created this magical land of scalable high margin businesses. The US indexed heavily on the internet and offshored manufacturing. This birthed about 50 years of a roaring software economy.
Before software came along at all, most businesses were low margin, high volume businesses. The only exception was consulting. Everything was a COGS game. Software was an economic anomaly that, because of the cognitive moat, could defend massive scalable high margins (B2B SaaS). Software is manufactured consulting. This also gave birth to the attention economy where companies optimized against the consumer's best interest in the name of immense profit.
The 50 Year Bubble
Not too long ago a number of companies raising money as neo clouds pulled a big con on a bunch of venture capitalists and maybe themselves too. They looked at traditional CPU-based clouds and the large software margins that come from them and said "hey, I'm going to do that with GPUs for AI." The problem here is that for AI companies training models or serving inference there is actually very little software margin. This is because the quality of your model scales with the number of GPUs used to train it. So each additional GPU makes the product better, not some software feature on top of it. And so lots of these companies that raised capital claiming margins of CPU clouds have been and are continuing to blow up or pivot.
Eroding Moats
What does it mean when the technical moat of high-margin B2B SaaS companies goes away? These are the companies that have been fueling the largest amount of economic growth in the world over the past 50 years.
When the cost to produce software goes down it becomes easier to compete with software companies. When there is more competition, margins get squeezed, and companies really have to begin to justify their margins. This is good because it will really require consumer applications to start to offer a higher quality of service. Brain rot is not a strong enough consumer value proposition.
This will mainly happen by building mechanisms to improve market inefficiencies. The way to create value is to bundle existing things together. Some examples of how you can use efficient markets to bring the costs of goods down:
- Ride share app market: let Uber, Lyft, Waymo, Tesla compete in real time on price for the customer
- Message aggregator: Why does the consumer have 10 messaging apps wtf? (also then can't sell ads to them)
- Money aggregator: Consumer finance is terrible. Can we make a one stop shop full service application for users?
These are only now possible with the advent of AI being the tip of the spear to end the decade long web scraping war. Agents > humans means the humans don't have to put up with the enshittification of the internet anymore. The dead internet theory is panning out in real time.
The Pattern
What happens in a macroeconomic landscape when the cost of labor goes down? The last time this happened was in the 1970s when the US offshored a lot of its manufacturing. What happened to the economy then? Energy skyrocketed, in particular oil. This was the beginning of the era of oil. Labor arbitrage creates energy demand. Capital flows to scarcity.
The world has an increasing demand for energy. Large datacenter buildouts demand way more electricity than is being produced in the US. Historically energy surpluses have always coincided with periods of prosperity in human civilization. Energy scarcity has correlated with conflict. Today there are two new big energy players other than oil: solar and nuclear. The cost to produce solar has been decreasing drastically year over year. Its COGS are going down, setting it up to be a huge player in high volume low margin energy production. Uranium on the other hand is facing a drastic quantifiable supply gap. Demand of 180M lbs/year vs. supply of 140M lbs/year creates a 40M+ lb structural deficit.
For fifty years software let us forget that margins come from somewhere. The cost of cognition is now denominated in kilowatt hours. We're all in the COGS game again — the only question is whether you're selling commodities or buying scarcity. On a long enough time horizon, this is the good part of capitalism: the cost of living goes down.