Duality announces the addition of a hardware-based security technology, trusted execution environments (TEEs or Secure Enclaves), for privacy protected AI development in AWS, GCP, or Azure.
Privacy Preserving Machine Learning (PPML) is a technique to prevent data leakage in machine learning algorithms. PPML employs many privacy-enhancing strategies to allow multiple input sources to collaboratively train ML models without exposing private or sensitive data. Artificial intelligence (AI) dominates the digital transformation in business today. 86% of CEOs reported that AI was considered...
As data continues to grow exponentially, so does its potential to derive value. Ensuring that the data sets remain private compounds our ability to learn and gain insights from the wealth of data at our disposal. Privacy Enhancing Technologies (PETs) enable data scientists to derive powerful insights from large, valuable data sets without deleting or...
The field of Data Science is in the spotlight today. It combines deep knowledge and cutting edge technology from multiple disciplines to solve the most difficult problems facing the world today. In celebration of International Women’s Day 2022, we asked the talented women at Duality what they love about their careers and which big problems...
Upcoming Webinar: The Future of Research is Agentic: Why Secure AI Assistants Are a Game Changer – July 22
