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Google outlines secure server-side memory for Private AI Compute

Google DeepMind described a planned persistent-memory layer for Private AI Compute, using encrypted storage and device-held keys to support cross-device context. The announcement is an architecture update, not evidence of general product availability.

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Google DeepMind diagram of encrypted client-to-cloud flow through secure enclaves to server-side memory
Google DeepMind’s architecture diagram for device keys, secure enclaves and server-side memory · Credit: Google DeepMind View source

Google DeepMind published a technical update on September 23 describing server-side persistent memory for its Private AI Compute platform. The design is intended to carry selected context across devices while using encrypted storage and secure enclaves for cloud-side processing.

Keys remain on the user's devices, Google says

In Google’s described design, the information needed for assistance is stored in a per-user encrypted layer, with the cryptographic keys held on personal devices. An authenticated encrypted channel sends a request to an isolated cloud enclave, where data is temporarily decrypted for inference and then re-encrypted with any new context.

A technical design, not a general launch

Google says devices will be able to verify authentic, unaltered server software through a tamper-resistant public record and that the update includes results from an independent cybersecurity audit. The post points to a technical brief and verification materials, but the architecture’s deployment status and practical privacy guarantees were not independently tested here.

Sources