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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 an incentive mechanism that maximally rewards honestly selected weights, making the system resistant to collusion of up to 50 percent of the network weight. The result is a collectively run intelligence market that continually produces newly trained models and pays contributors who create information theoretic value. 0.1/ INTRODUCTION The production of machine intelligence has come to rely almost entirely on a system of benchmarking, where m

Whitepaper — A Peer-to-Peer Intelligence Market — Bittensor ABOUT WHITEPAPER DOCS DISCORD WALLET EXPLORE Bittensor: A Peer-to-Peer Intelligence Market Yuma Rao 00/ Abstract 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. Howev

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