The question is total addressable market, and the current tech giants are the anchor for what capturing something mildly useful for everyone in the whole world gets you, which is on the order of $100bn per year. If AIs don’t get much better than they are now, it’s plausible this is where the winning AI companies land for a while (at least they probably don’t get to trillion dollar capex budgets). If AIs do get much better, then the anchor shifts to some portion of the global job market, which is in tens of trillions per year.
For now, a $200bn project every two years to build 5 GW worth of datacenters with the newest compute hardware (for a single AI company) seems plausible in a steady state ($140bn compute hardware, $60bn non-compute infrastructure). At which point it might slowly get to 10 GW in 2030s as the longer-term non-compute infrastructure no longer needs to be built anew every two years together with the compute hardware (once the total power and cooling requirements stop changing too much and it becomes possible to reuse the older datacenter campuses and only refresh the compute hardware).
But even for the 5 GW datacenter campuses, there isn’t currently enough talk about building them in 2028 to be sure they’ll be built on-trend, it sounds like 2 GW in 2028 is more likely and the 5 GW sites (serving a single AI company) will only appear in 2029-2031. Though 1 GW in 2026 also wasn’t clearly foreshadowed back in 2023, and 5 GW in 2028 is both on-trend and in principle financially plausible if growth continues, so maybe it still happens.
Knowing the TAM would clearly be useful for deciding whether or not to continue investing in compute scaling, but trying to estimate the TAM ahead of time is very speculative, whereas the revenues from yesterday’s investments can be observed before deciding whether to invest today for more revenue tomorrow. Therefore I think investment decisions will be driven in part by revenues, and that people trying to forecast future investment decisions should make forecasts about future revenues, so that we can track whether those revenue forecasts are on track and what that implies for future investment forecasts.
I haven’t done the revenue analysis myself, but I’d love to read something good on the revenue needed to justify different datacenter investments, and whether the companies are on track to hit that revenue.
The question is total addressable market, and the current tech giants are the anchor for what capturing something mildly useful for everyone in the whole world gets you, which is on the order of $100bn per year. If AIs don’t get much better than they are now, it’s plausible this is where the winning AI companies land for a while (at least they probably don’t get to trillion dollar capex budgets). If AIs do get much better, then the anchor shifts to some portion of the global job market, which is in tens of trillions per year.
For now, a $200bn project every two years to build 5 GW worth of datacenters with the newest compute hardware (for a single AI company) seems plausible in a steady state ($140bn compute hardware, $60bn non-compute infrastructure). At which point it might slowly get to 10 GW in 2030s as the longer-term non-compute infrastructure no longer needs to be built anew every two years together with the compute hardware (once the total power and cooling requirements stop changing too much and it becomes possible to reuse the older datacenter campuses and only refresh the compute hardware).
But even for the 5 GW datacenter campuses, there isn’t currently enough talk about building them in 2028 to be sure they’ll be built on-trend, it sounds like 2 GW in 2028 is more likely and the 5 GW sites (serving a single AI company) will only appear in 2029-2031. Though 1 GW in 2026 also wasn’t clearly foreshadowed back in 2023, and 5 GW in 2028 is both on-trend and in principle financially plausible if growth continues, so maybe it still happens.
Knowing the TAM would clearly be useful for deciding whether or not to continue investing in compute scaling, but trying to estimate the TAM ahead of time is very speculative, whereas the revenues from yesterday’s investments can be observed before deciding whether to invest today for more revenue tomorrow. Therefore I think investment decisions will be driven in part by revenues, and that people trying to forecast future investment decisions should make forecasts about future revenues, so that we can track whether those revenue forecasts are on track and what that implies for future investment forecasts.
I haven’t done the revenue analysis myself, but I’d love to read something good on the revenue needed to justify different datacenter investments, and whether the companies are on track to hit that revenue.