From Theory to Practice: Advances in Real-World Federated Learning with NVIDIA FLARE

Federated learning (FL) enables collaborative AI development without centralizing sensitive data. This talk highlights its real-world use in predicting COVID-19 outcomes while preserving patient privacy and data governance. I then introduce the latest innovations in NVIDIA FLARE, the open-source SDK for production-ready FL. New APIs simplify workflow design, while upgrades such as message quantization, native tensor transfer, and model streaming improve communication efficiency. Combined with privacy-preserving techniques like differential privacy, homomorphic encryption, and confidential computing, FLARE integrates seamlessly with popular training libraries and supports customizable workflows—empowering scalable applications in healthcare, biopharma, financial services, and large-scale language models.