Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to achieve artificial general intelligence, engineers have centralized AI development and training to accelerate progress, even at the risk of single-point failures and data privacy violations. Alternatively, decentralized frameworks have struggled to match the robustness of centralized systems—what if one of the heads has bad intentions?
New federated learning algorithm enables private, robust, and fast AI development
