MC2: Secure Collaborative Analytics for Machine Learning

Machine Learning (ML) has gained prominence in recent years because of its ability to be applied across scores of industries and solve complex problems effectively. Yet, research shows that nearly 90% of AI/ML models never actually make it into production or hit the market. The main challenge is that ML/AI models require huge volumes of high-quality, accurate, and timely data to be effective, but organizations have long been reluctant to share sensitive information due to security and privacy concerns. Personal data is becoming more pervasive, causing privacy concerns to grow. As a result, global data protection laws have become stricter, and organizations face increasingly higher noncompliance risks. Mitigating such concerns and taking AI/ML to the next level requires a new approach to collaboration -- secure collaborative learning.