Optimistic Rollups Secure Decentralized Federated Learning Model Integrity
This mechanism secures decentralized AI model aggregation by applying optimistic rollup fraud proofs to validate off-chain model weight updates, ensuring global model integrity.
Zero-Knowledge Proof of Training Secures Decentralized Federated AI
A new Zero-Knowledge Proof of Training consensus leverages zk-SNARKs to cryptographically verify model accuracy without exposing private data, solving the fundamental privacy-accuracy trade-off in decentralized AI.
Decentralized Identity Protocols Achieve Mainstream Validation through Real-World Partnerships
DID is transitioning from a theoretical primitive to a foundational layer, leveraging biometric proof-of-personhood to secure platform economies and user data.
