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Explore how to implement privacy-preserving machine learning for connected vehicles in this 31-minute conference talk. Discover the critical importance of protecting personal and sensitive data generated by modern vehicles while enabling advanced ML capabilities. Learn about Trusted Execution Environments (TEEs) and Azure Confidential Computing as solutions for maintaining data privacy throughout the entire machine learning pipeline in cloud environments. Understand the innovative approach to recreating vehicle environments in the cloud where sensitive information remains protected during model training, inference, and deployment phases. Gain insights from Mercedes-Benz R&D North America's real-world implementation of secure, privacy-respecting personalized systems designed for next-generation connected vehicles, presented by Senior Data Scientist Frankie Cancino.
