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Another idea is to dedicate cpu cycles to something else that is easier to distribute, and then use the proceeds for massive amounts of gpu for academic use.

Crypto is an example.



This creates indirection costs and counterparty risks that don't appear in the original solution.


There is also indirection cost by taking something that is optimized to run on GPU’s within the data center and distributing that to individual PCs.


this would be very wasteful


So is trying to distribute training across nodes compared to what can be done inside a data center.




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