Better Together – Duality Adds Native Support for Flower for End-to-End Federated Learning

Federated learning has evolved into a dynamic ecosystem encompassing various frameworks like Flower, NVIDIA FLARE, and Duality, each serving distinct purposes but working synergistically. Flower provides a flexible, Pythonic interface ideal for experimentation and custom federated learning logic, while FLARE excels in orchestrating and deploying scalable production workloads. Duality serves as a unifying platform, adding governance, privacy, and security layers that ensure compliant and secure workflows across different data environments. The integration of Flower's capabilities into Duality enables seamless deployment of existing Flower workloads without code alterations, enhancing governance, scalability, and privacy through features like policy enforcement, cryptographic protection, and multi-party orchestration. This collaboration allows organizations to harness the flexibility of open-source frameworks alongside enterprise-grade security, facilitating faster transitions from research to deployment and ensuring compliance and data privacy. Duality's support for Flower exemplifies its mission to create a secure, interoperable platform for collaborative AI that leverages the strengths of the federated learning ecosystem.