With Great Data, Comes Great Responsibility
Trillion-dollar industries are unable to leverage their immensely valuable data for AI training and inference due to privacy concerns. The potential for AI-driven breakthroughs—genomic secrets that could cure diseases, predictive insights to eliminate supply chain waste, and chevrons of untapped energy sources—remain locked away. Privacy regulations also closely guard this valuable and sensitive information.
To propel human civilization forward in energy, healthcare, and collaboration, it is crucial to enable AI systems that train and generate inference on data while maintaining full end-to-end privacy. At Bagel, pioneering this capability is our mission. We believe accessing a fundamental resource like knowledge, for both human-driven and autonomous AI, should not entail a compromise on privacy.
We have applied and experimented with almost all the major privacy-preserving machine learning (PPML) mechanisms. Below, we share our insights, our approach, and some research breakthroughs.
