Differentially Private Synthetic Data Generation via Foundation Model APIs

Explore the cutting-edge research on generating differentially private synthetic data using foundation model APIs in this 56-minute Google TechTalk presented by Sivakanth Gopi. Dive into the challenges and potential of leveraging large foundation models as black boxes, utilizing only their inference APIs to create high-quality synthetic data while maintaining privacy. Learn about the innovative Private Evolution (PE) framework and its promising results, including significant improvements in FID scores for CIFAR10 dataset. Gain insights into the speaker's background, the abstract of the talk, and the comprehensive syllabus covering topics such as generative neural networks, differential privacy, diffusion models, and the intrinsic dimension of data.