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Google releases HEIR, an open-source compiler for private AI inference on encrypted data
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Google's HEIR compiler converts pre-trained AI models to run on encrypted inputs, aiming to make homomorphic encryption practical for production inference.
Homomorphic encryption lets servers compute on encrypted data without seeing it, but manual conversion requires cryptographers. HEIR automates that conversion, potentially opening private AI inference to non-experts. However, the computational overhead remains a cost that hardware accelerators are still working to reduce.
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HEIR is an open-source compiler toolchain that converts pre-trained AI models to operate on encrypted inputs.
Google partnered with hardware accelerator companies including Belfort, Niobium, Cornami, and Optalysys to improve latency.
Demos include recommendation, credit card fraud detection, and network threat intrusion, with source code on GitHub.
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