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Advancing Private AI Compute with secure, server-side memory

Google DeepMind describes an architectural update to its Private AI Compute platform that adds a persistent, server-side memory layer for AI assistants without sacrificing on-device-level privacy. User data is sealed in encrypted storage in the cloud, with decryption keys held only on personal devices; a hardware-isolated "secure enclave" temporarily decrypts data to serve a request, saves new context, and re-encrypts it, enabling continuity across sessions and devices (e.g. resuming a task started on smart glasses on a laptop). The post also announces a tamper-proof public record of the server software, an updated technical whitepaper, and results of an independent security audit for community verification.

TL;DR DeepMind's Private AI Compute now supports encrypted, persistent cross-device memory via hardware-isolated cloud enclaves, keeping decryption keys on-device.
Also seen from another angle🛡️ Security →

Organisations named here

Technologies named here

  • Private AI Compute

Techniques named here

  • Secure server-side memory layer
  • Secure enclave processing
  • Stateless hardware-isolated cloud enclaves
  • Tamper-proof public software record