Federated learning has a major trust problem — here’s how zero-knowledge fixes it 🛡️

Decentralized AI training breaks down when malicious actors compromise the network:
▫️ Corrupted local training — Rogue clients push malicious models to disrupt learning 🦠
▫️ Malicious aggregation — Central aggregators manipulate global updates instead of combining honest data 🚨

Without verification, federated learning remains vulnerable at every stage.

Hayk breaks down why ZK proofs and verification layers are essential to securing decentralized AI.

📺 Watch the full session: https://youtu.be/6VvSunDFMTI?si=dEyq6MTXiuw5kABA