Google showcased HEIR, an open-source compiler toolchain and development platform added to its Private Computing Toolkit that converts AI models to run cryptographically-secure private inference on encrypted data.

Key Details

• Google introduced HEIR (Homomorphic Encryption Intermediate Representation) to enable cryptographically-secure private AI inference on encrypted data without revealing underlying user information
• HEIR converts pre-trained AI models operating on unencrypted data into models operating on encrypted inputs, aiming to provide a one-click encrypted inference solution for production applications
• Google partnered with homomorphic encryption hardware accelerator companies including Belfort, Niobium, Cornami, and Optalysys
• Google demonstrated four private inference applications compiled with HEIR: a deep learning recommendation model, credit card fraud detection, network traffic anomaly detection, and a hotword detector
• HEIR has supported collaborations across academic institutions including Georgia Tech, Carnegie Mellon, UC Santa Barbara, Illinois Institute of Technology, Purdue, University of Edinburgh, Tsinghua University, and New York University

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