Federated learning is one of several emerging privacy-enhancing technologies steadily gaining traction with its capability to train algorithms on various data sets without exchanging raw data. In fact, the global federated learning market is expected to increase at a compound annual growth rate of 10.5% by 2032. IAPP Principal Researcher, Technology, Katharina Koerner, CIPP/US, and Research and Insight Analyst Brandon LaLonde explore federated learning as a trending technology, implementation while preserving privacy principles, privacy and security challenges, and examples of real-world applications.
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