Pioneering Privacy-Preserving Machine Learning Across the Globe
Related Content

Reimagining Fraud Detection through Collaborative Multi-Party GPU Computing
See how BNY Mellon is reimagining fraud detection using Multi-Party Computing crypto technique on GPUs. Read more →

Privacy Challenges in Extreme Gradient Boosting
Read this joint Inpher – Amazon Sciences blog post to see how MPC can help build better predictions for multiple sclerosis (MS) using confidential data while guaranteeing patient privacy. Read more →

Privacy & Precision: Data Analysis & Machine Learning with Secret Computing
Injecting noise, as with Differential Privacy, is one way to maintain privacy but often impacts model accuracy. So can you build precise ML models while preserving privacy? Read this whitepaper to learn how. Read more →