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Author Topic: IOEconomy  (Read 1323 times)
BaruchNaPaphos (OP)
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February 20, 2015, 08:01:44 PM
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The international uses for bitcoin are staggering. Control of bitcoin via deeplearning machines and algorithms in my belief is the strongest tool for the elimination of poverty traps in third world countries. Is there any work being done on distributed data analysis? In the same way storj allows for protection from faulty data, through redundancy, is there a system being developed for data analysis that utilizes redundancy for multiple users?
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laurentmt
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February 21, 2015, 12:29:31 AM
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An open network allowing to use massive computing power would be incredible. But to be honest, I'm not sure it can be easily done in an open network.

Proof of work or systems like storj work in an trustless network, because there's an asymmetry between the work to be done and the verification. Doing the work is expensive while verification is cheap (e.g. mining is expensive while checking a PoW is cheap and fast). This asymmetry is important to avoid "cheaters".

Main problem with a trustless distributed network providing computing power for ML: task and verification have the same cost if you want to be 100% sure that the work done is correct and check it by brute-force.

Note that some cryptographic concepts like zero-knowledge proof may help. I'm not sure they're mature enough for everyday use cases but some people on the forum should be able to tell you more about this.

At last, you might be interested by some concepts from project Ethereum (a platform for distributed applications).
Just be aware that these applications are very "simple"... not intended to implement ML algorithms.  Wink
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February 21, 2015, 02:18:37 AM
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Yeah, ethereum seems more applicable to the transfer of physical representation rather than the transfer of data conclusions. =/. It would be useful, whenever it comes about would probably be the method for computer "thinking", I cant think of how a system for data analysis would work either. It seems like the ethereum system would work for getting the analyses done and if the ioeprogram decided who to send data to and did it enough times to be sure that the data was analyzed was correct by comparing differences in analysis looking for statistically significant correlations to determine if an output was bad. Would be slow as you would have to check each level at a centralized computer =/. Too bad we don't live  in the future yet and still have to build it.
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