Open Internet by MindsNet

Adoption of Privacy-Preserving Techniques in Production ML Systems

The adoption of privacy-preserving techniques in production ML systems faces significant challenges. Industry practitioners are uncertain about the real-world effectiveness of techniques like differential privacy, federated learning, and on-device inference. Key concerns include engineering hurdles, performance impacts, and infrastructure costs.

Computing & Technology, Computer Science, Machine Learning