Google AI Described New Machine Learning Methods for Generating Differentially Private Synthetic Data

Google AI researchers have developed a new method for creating synthetic datasets that protect user privacy while training predictive models. They use efficient fine-tuning techniques to generate differentially private synthetic data, reducing computational overhead and improving data quality. Their approach has shown that classifiers trained on this synthetic data outperform those trained on other methods, as well as classifiers trained directly on sensitive data using differentially private stochastic gradient descent. This method preserves privacy and maintains high utility for training predictive models, making it valuable for organizations using sensitive data without compromising privacy. To evolve your company with AI, identify automation opportunities, define KPIs, select an AI solution that aligns with your needs, and implement gradually. Consider using the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. For more information, you can visit the AI Lab in Telegram @itinai for a free consultation or follow @itinaicom on Twitter.