Google is making private AI practical with homomorphic encryption
blog.google
August 14, 2026
4 min read
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Summary
HEIR is an open-source compiler in Google's Private Computing Toolkit that enables cryptographically-secure private AI inference using homomorphic encryption. This tool addresses the balance between privacy and security in AI applications.
Key Takeaways
- Google introduced HEIR, an open-source compiler that enables cryptographically-secure private AI inference using homomorphic encryption.
- Homomorphic encryption allows computations to be performed on encrypted data, enabling services like content recommendations without exposing user information.
- The cost of homomorphic encryption is decreasing, shifting the capability/privacy trade-off to a question of cost rather than feasibility.
- HEIR has gained support from the homomorphic encryption community and has been used in collaborations with multiple universities, resulting in peer-reviewed publications.
Community Sentiment
Positives
- The emergence of homomorphic encryption in AI is a thrilling development, hinting at a future where privacy can coexist with powerful data analysis.
- Big players like Google diving into homomorphic encryption for ML is a sign of progress, even if commercial viability is still a few years off.
Concerns
- High overheads of homomorphic encryption make it commercially unviable for real-world applications right now, raising doubts about its practicality.
- There's skepticism about Google's intentions, with many feeling that they can't be trusted to genuinely prioritize user privacy.
