AI for Domains (AID)
News & features
The Crossroads of Innovation and Privacy: Private Synthetic Data for Generative AI
| Gbola Afonja, Robert Sim, Zinan Lin, Huseyin Atahan Inan, and Sergey Yekhanin
Synthetic data could potentially help address some privacy concerns with AI model development and training, but it comes with limitations. Researchers at Microsoft are exploring techniques for producing more realistic data with strong privacy protections.
Privacy Preserving Machine Learning: Maintaining confidentiality and preserving trust
| Victor Ruehle, Robert Sim, Sergey Yekhanin, Nishanth Chandran, Melissa Chase, Daniel Jones, Kim Laine, Boris Köpf, Jaime Teevan, Jim Kleewein, and Saravan Rajmohan
Machine learning (ML) offers tremendous opportunities to increase productivity. However, ML systems are only as good as the quality of the data that informs the training of ML models. And training ML models requires a significant amount of data, more…