Google is promoting HEIR, an open-source compiler project aimed at making homomorphic encryption more usable for AI inference, according to a Google Security blog post surfaced on Hacker News. Google describes HEIR as the latest addition to its Private Computing Toolkit and says the tool is designed to let developers run computations on encrypted data rather than requiring plaintext access. HEIR stands for Homomorphic Encryption Intermediate Representation. In Google’s description, it is a compiler toolchain and development platform for homomorphic encryption, with a specific focus on converting pre-trained AI models that normally operate on unencrypted data so they can operate on encrypted inputs instead. The privacy mechanic is straightforward in concept but difficult in implementation: homomorphic encryption allows a server to process ciphertext and return encrypted outputs without seeing the underlying information. Google gives the example of a cloud service providing content recommendations without being able to inspect the user features that drive those recommendations. The hard part is cost and complexity. Google acknowledges that homomorphic encryption carries nontrivial overhead, and says manually converting existing programs to use it efficiently generally requires cryptographic expertise. HEIR is meant to move that work into compiler tooling, with Google’s stated ambition of making encrypted inference easier for non-experts to incorporate into production applications. The post also places HEIR alongside Google’s broader privacy technology work, including differential privacy, private set membership, private information retrieval and secure enclaves on Google Cloud. Google emphasizes that, unlike hardware-based approaches, homomorphic encryption’s privacy guarantees are cryptographic rather than dependent on a trusted execution environment. Google says it announced its intentions around HEIR in 2023 and that the homomorphic encryption community has since engaged with the project. The company also says it has partnered with hardware accelerator companies working on homomorphic encryption, naming Belfort, Niobium, Cornami and Optalysys, and plans to demonstrate latency benefits from those accelerators in the near future. What the cluster does not provide is independent validation. There are no third-party benchmarks, latency numbers, deployment counts or customer examples in the supplied material, so the strongest supported conclusion is that Google has released and is promoting HEIR as open-source infrastructure for encrypted inference—not that it has already made homomorphic encryption broadly economical in production. Who benefits: Developers building privacy-sensitive AI services could benefit if HEIR lowers the barrier to using homomorphic encryption. Hardware accelerator vendors named by Google may also benefit if encrypted inference workloads become more common. Who's exposed: Teams relying on conventional cloud inference for sensitive user data remain exposed to privacy, compliance and trust constraints.