arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2003.03917cs.AIcs.LGcs.MA
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BitTensor: A Peer-to-Peer Intelligence Market

Yuma Rao, Jacob Steeves, Ala Shaabana, Daniel Attevelt, Matthew McAteer

英文摘要:

As with other commodities, markets could help us efficiently produce machine intelligence. We propose a market where intelligence is priced by other intelligence systems peer-to-peer across the internet. Peers rank each other by training neural networks which learn the value of their neighbors. Scores accumulate on a digital ledger where high ranking peers are monetarily rewarded with additional weight in the network. However, this form of peer-ranking is not resistant to collusion, which could disrupt the accuracy of the mechanism. The solution is a connectivity-based regularization which exponentially rewards trusted peers, making the system resistant to collusion of up to 50 percent of the network weight. The result is a collectively run intelligence market which continual produces newly trained models and pays contributors who create information theoretic value.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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