Decentralized Learning and Proof-of-Training

Decentralized learning approaches aim to train machine learning models across multiple devices or nodes without relying on centralized data aggregation, thereby preserving privacy and data ownership.

The Autonomys Network’s underlying Subspace Protocol is uniquely positioned to facilitate decentralized learning as it addresses several challenges that impede the practical implementation of decentralized AI storage/compute-sharing DePIN.