Federated Learning (FL) systems evolve in heterogeneous and ever-evolving environments that challenge their performance. Under real deployments, the learning tasks of clients can also evolve with time, which calls for the integration of methodologies such as Continual Learning. To enable research reproducibility, we propose a set of experimental best practices that precisely capture and emulate complex learning scenarios. Our framework, Freddie, is the first entirely configurable framework for Federated Continual Learning (FCL), and it can be seamlessly deployed on a large number of machines thanks to the use of Kubernetes and containerization. We demonstrate the effectiveness of Freddie on two use cases, (i) large-scale FL on CIFAR100 and (ii) heterogeneous task sequence on FCL, which highlight unaddressed performance challenges in FCL scenarios.

Job automation, algorithmic bias, and technological development are the first thoughts that spring to mind when we think of Artificial Intelligence. But at the same time, AI can be used in many fun and interesting ways. Here, we discuss ten fun AI tools that you must try out. Besides being a great way to kill boredom, they demonstrate how advanced AI has already become. Semantris is one of the many Google-powered AI experiments.

People love singing with Freddie Mercury, but can you sing like Freddie too? We made an AI-powered singing challenge to find out. This experiment uses new, on-device machine learning models developed by Google Research to see how close your timbre, pitch, and melody are to Freddie's. Your audio doesn't get uploaded to servers to be analyzed, so your vocals stay private. FreddieMeter was made with The Mercury Phoenix Trust, a charity founded by Brian May, Roger Taylor, and their manager Jim Beach in memory of Freddie Mercury, who died in 1991 from AIDS-related causes.