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deepmind.googlearticle

Advancing Private AI Compute with secure, server-side memory

Google DeepMind describes an architectural update to its Private AI Compute platform that adds persistent, cross-device memory for AI assistants while keeping data confidential: user data is stored encrypted in the cloud with decryption keys held only on the user's own devices, and requests are processed inside hardware-isolated "secure enclaves" that decrypt data only transiently in isolated memory. Alongside the update, Google published a technical whitepaper, a tamper-proof public record of the server software for device-side attestation, and results from an independent third-party security audit, inviting outside verification of the design.

TL;DR Google details a secure-enclave, key-on-device architecture for persistent AI-assistant memory in its Private AI Compute platform, backed by a whitepaper and independent audit.
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Technologies named here

Techniques named here

  • Secure enclave / hardware-isolated cloud processing
  • Persistent encrypted memory with immediate re-encryption
  • Remote/tamper-proof software verification