I think an important consideration being overlooked is how comptetntly a centralised project would actually be managed.
In one of your charts, you suggest worlds where there is a single project will make progress faster due to “speedup from compute almagamation”. This is not necessarily true. It’s very possible that different teams would be able to make progress at very different rates even if both given identical compute resources.
At a boots-on-the-ground level, the speed of progress an AI project makes will be influenced by thosands of tiny decisions about how to:
Manage people
Collect training data
Prioritize research direcitons
Debug training runs
Decide who to hire
Assess people’s perfomance and decide to should be promoted to more influential positions
Manage code quality/technical debt
Design+run evals
Transfer knowledge between teams
Retain key personnel
Document findings
Decide what internal tools to use/build
Handle data pipeline bottlenecks
Coordinate between engineers/researchers/infrastructure teams
Make sure operations run smoothly
The list goes on!
Even seemingly minor decisions like coding standards, meeting structures and reporting processes might compound over time to create massive differences in research velocity. A poorly run organization with 10x the budget might make substantially less progress than a well-run one.
If there was only one major AI project underway it would probably be managed less well than the overall best-run project selected from a diverse set of competing companies.
Unlike the Manhattan project—there’s already sufficently strong commercial incentives for private companies to focus on the problem, it’s not already clear exactly how the first AGI system will work, and capital markets today are more mature and capable of funding projects at much larger scales. My gut feeling is if AI was fully consolidated tomorrow—this is more likely to slow things down than speed them up.
I agree that it’s not necessarily true that centralising would speed up US development!
(I don’t think we overlook this: we say “The US might slow down for other reasons. It’s not clear how the speedup from compute amalgamation nets out with other factors which might slow the US down:
Bureaucracy. A centralised project would probably be more bureaucratic.
Reduced innovation. Reducing the number of projects could reduce innovation.”)
Interesting take that it’s more likely to slow things down than speed things up. I tentatively agree, but I haven’t thought deeply about just how much more compute a central project would have access to, and could imagine changing my mind if it were lots more.
I think an important consideration being overlooked is how comptetntly a centralised project would actually be managed.
In one of your charts, you suggest worlds where there is a single project will make progress faster due to “speedup from compute almagamation”. This is not necessarily true. It’s very possible that different teams would be able to make progress at very different rates even if both given identical compute resources.
At a boots-on-the-ground level, the speed of progress an AI project makes will be influenced by thosands of tiny decisions about how to:
Manage people
Collect training data
Prioritize research direcitons
Debug training runs
Decide who to hire
Assess people’s perfomance and decide to should be promoted to more influential positions
Manage code quality/technical debt
Design+run evals
Transfer knowledge between teams
Retain key personnel
Document findings
Decide what internal tools to use/build
Handle data pipeline bottlenecks
Coordinate between engineers/researchers/infrastructure teams
Make sure operations run smoothly
The list goes on!
Even seemingly minor decisions like coding standards, meeting structures and reporting processes might compound over time to create massive differences in research velocity. A poorly run organization with 10x the budget might make substantially less progress than a well-run one.
If there was only one major AI project underway it would probably be managed less well than the overall best-run project selected from a diverse set of competing companies.
Unlike the Manhattan project—there’s already sufficently strong commercial incentives for private companies to focus on the problem, it’s not already clear exactly how the first AGI system will work, and capital markets today are more mature and capable of funding projects at much larger scales. My gut feeling is if AI was fully consolidated tomorrow—this is more likely to slow things down than speed them up.
I agree that it’s not necessarily true that centralising would speed up US development!
(I don’t think we overlook this: we say “The US might slow down for other reasons. It’s not clear how the speedup from compute amalgamation nets out with other factors which might slow the US down:
Bureaucracy. A centralised project would probably be more bureaucratic.
Reduced innovation. Reducing the number of projects could reduce innovation.”)
Interesting take that it’s more likely to slow things down than speed things up. I tentatively agree, but I haven’t thought deeply about just how much more compute a central project would have access to, and could imagine changing my mind if it were lots more.