Organizations in healthcare, finance, and other sensitive industries want to use large AI models without exposing private data to the cloud servers running those models. A cryptographic technique called Secure Multi-Party Computation (MPC) makes this possible. It splits data into encrypted fragments, distributes them across two or more servers that do not share information with each other, and lets those servers compute an AI result without either one ever seeing the raw input. The catch … More → The post Researchers build an encrypted routing layer for private AI inference appeared first on Help Net Security.