This seems to omit a critical and expected limitation as a process scales up in the number of people involved—communication and coordination overhead.
If there is low hanging fruit, but everyone is reaching for it simultaneously, then doubling the number of researchers won’t increase the progress more than very marginally. (People with slightly different capabilities implies that the expected time to success will be the minimum of different people.) But even that will be overwhelmed by the asymptotic costs for everyone to find out that the low-hanging fruit they are looking for has been picked!
Is there a reason not to think that this dynamic is enough to explain the observed slowdown—even without assuming hypothesis 3, of no more low-hanging fruit?
This is an interesting theory. I think it makes some different predictions to the low hanging fruit model.
For instance, this theory would appear to suggest that larger teams would be helpful. If intel are not internally repeating the same research then them increasing their number of researchers should increase the discovery rate. If instead a new company employs the same number of new researchers then this will have minimal effect on the world discovery rate if they repeat what Intel is doing.
A simplistic low hanging fruit explanation does not distinguish between where the extra researchers are located.
Yes, this might help somewhat, but there is an overhead / deduplication tradeoff that is unavoidable.
I discussed these dynamics in detail (i.e. at great length) on Ribbonfarm here.
The large team benefit would explain why most innovation happens near hubs / at the leading edge companies and universities, but that is explained by the other theories as well.
This seems to omit a critical and expected limitation as a process scales up in the number of people involved—communication and coordination overhead.
If there is low hanging fruit, but everyone is reaching for it simultaneously, then doubling the number of researchers won’t increase the progress more than very marginally. (People with slightly different capabilities implies that the expected time to success will be the minimum of different people.) But even that will be overwhelmed by the asymptotic costs for everyone to find out that the low-hanging fruit they are looking for has been picked!
Is there a reason not to think that this dynamic is enough to explain the observed slowdown—even without assuming hypothesis 3, of no more low-hanging fruit?
This is an interesting theory. I think it makes some different predictions to the low hanging fruit model.
For instance, this theory would appear to suggest that larger teams would be helpful. If intel are not internally repeating the same research then them increasing their number of researchers should increase the discovery rate. If instead a new company employs the same number of new researchers then this will have minimal effect on the world discovery rate if they repeat what Intel is doing.
A simplistic low hanging fruit explanation does not distinguish between where the extra researchers are located.
Yes, this might help somewhat, but there is an overhead / deduplication tradeoff that is unavoidable.
I discussed these dynamics in detail (i.e. at great length) on Ribbonfarm here.
The large team benefit would explain why most innovation happens near hubs / at the leading edge companies and universities, but that is explained by the other theories as well.