We can reason back from the quantity of money to how much Altman expects to do with it. Suppose we know for a fact that it’s will soon be possible to replace some percentage of labor with an AI that has negligible running cost. How much should we be willing to pay for this? It gets rid of opex (operating expenses, i.e. wages) in exchange for capex (capital expenses, i.e. building chips and data centers). The trade between opex and capex depends on the long term interest rate and the uncertainty of the project. I will pull a reasonable number from the air, and say that the project should pay back in ten years. In other words, the capex is ten times the avoided annual opex. Seven trillion dollars in capex is enough to employ 10,000,000 people for ten years (to within an order of magnitude).
That’s a surprisingly modest number of people, easily absorbed by the churn of the economy. When I first saw the number “seven trillion dollars,” I boggled and said “that can’t possibly make sense”. But thinking about it, it actually seems reasonable. Is my math wrong?
This analysis is so highly decoupled I would feel weird posting it most places. But Less Wrong is comfy that way.
I think this would only work if the investors themselves would save the operation costs of those 10^7 people which seems unlikely—if Sam wants to create AGI and sell that as a service, he can only capture a certain fracture of the gains, while the customers will realize the remaining share.
You’re right. My analysis only works if a monopoly can somehow be maintained, so the price of AI labor is set to epsilon under the price of human labor. In a market with free entry, the price of AI labor drops to the marginal cost of production, which is putatively negligible. All the profit is dissipated into consumer surplus. Which is great for the world, but now the seven trillion doesn’t make sense again.
We can reason back from the quantity of money to how much Altman expects to do with it.
Suppose we know for a fact that it’s will soon be possible to replace some percentage of labor with an AI that has negligible running cost. How much should we be willing to pay for this? It gets rid of opex (operating expenses, i.e. wages) in exchange for capex (capital expenses, i.e. building chips and data centers). The trade between opex and capex depends on the long term interest rate and the uncertainty of the project. I will pull a reasonable number from the air, and say that the project should pay back in ten years. In other words, the capex is ten times the avoided annual opex. Seven trillion dollars in capex is enough to employ 10,000,000 people for ten years (to within an order of magnitude).
That’s a surprisingly modest number of people, easily absorbed by the churn of the economy. When I first saw the number “seven trillion dollars,” I boggled and said “that can’t possibly make sense”. But thinking about it, it actually seems reasonable. Is my math wrong?
This analysis is so highly decoupled I would feel weird posting it most places. But Less Wrong is comfy that way.
I think this would only work if the investors themselves would save the operation costs of those 10^7 people which seems unlikely—if Sam wants to create AGI and sell that as a service, he can only capture a certain fracture of the gains, while the customers will realize the remaining share.
You’re right. My analysis only works if a monopoly can somehow be maintained, so the price of AI labor is set to epsilon under the price of human labor. In a market with free entry, the price of AI labor drops to the marginal cost of production, which is putatively negligible. All the profit is dissipated into consumer surplus. Which is great for the world, but now the seven trillion doesn’t make sense again.