Decentralized AI promises openness, resilience, and censorship resistance. Yet one stubborn obstacle stands in the way of real adoption: privacy. Enterprises hesitate to deploy valuable models if anyone running a node can inspect the weights. Users hesitate to submit sensitive inputs if those inputs might be read, logged, or copied by unknown operators. Regulators add another layer of pressure, requiring strict guarantees around data handling and auditability. If a decentralized network canno...