How Is Federated Learning Implemented on Phoenix Global?

To improve GPS navigation, MIT researchers are tagging road features on digital maps through Machine learning. Beyond GPS navigation, Machine learning has seen application in many fields ranging from medicine to financial analysis. Machine learning is constantly evolving because it is a science to educate computers to act like humans in real-life situations. The role of the Internet of Things in a revolutionary society cannot be ignored. The Internet of Things can use advanced machine learning (ML) algorithms for its applications. However, because a large amount of data is stored on a central cloud server, using centralized machine learning algorithms is not a viable option due to huge computational costs and privacy leak issues.  In this case, blockchain can improve the privacy of IoT networks, allowing them to decentralize without any central authority. However, it remains a challenging task to use sensitive and massive data stored in a distributed manner for application purposes. To overcome this difficult task, Federated Learning (FL) is a new type of ML. This most promising solution can bring learning to end devices without sharing private data with a central server. In simple terms, Federated Learning allows companies to share data in a “closed-loop system.”  Federated Learning (or Collaborative Learning) As a fully decentralized machine learning technique, Federated Learning is a step up from the ...