Inspired by the efficiency of financial markets, we propose that a market system can be used to effectively produce machine intelligence. This paper introduces a mechanism in which machine intelligence is valued by other intelligence systems peer-to-peer across the internet. Peers rank each other by training neural networks that are able to learn the value of their neighbours, while scores accumulate on a digital ledger. High-ranking peers are rewarded with additional weight in the network. In addition, the network features an incentive mechanism designed to resist collusion. The result is a collectively run machine intelligence market that continually produces newly trained models and rewards participants who contribute information-theoretic value to the system.