"Google announced Private AI Compute, a system designed to process AI requests using Gemini cloud models while aiming to keep user data private. The company describes Private AI Compute as a technology built to "unlock the full speed and power of Gemini cloud models for AI experiences" and claims it "allows you to get faster, more helpful responses, making it easier to find what you need, get smart suggestions and take action.""
"The system uses an AMD-based hardware Trusted Execution Environment (TEE) for CPU and TPU workloads to "encrypt and isolate memory and processing from the host." The company expanded its Titanium Hardware Security Architecture to TPU hardware starting with the sixth-generation Google Cloud TPU, known as Trillium, to meet Private AI Compute's requirements. The architecture also establishes encrypted communication channels between trusted nodes using protocols including Noise and Application Layer Transport Security ( ALTS)."
Private AI Compute processes AI requests using Gemini cloud models while keeping user data private. The system uses AMD-based hardware Trusted Execution Environments (TEE) for CPU and TPU workloads to encrypt and isolate memory and processing from the host. Titanium Hardware Security Architecture was extended to TPU hardware starting with sixth-generation Google Cloud TPU, Trillium, to meet Private AI Compute requirements. Encrypted communication channels between trusted nodes use protocols including Noise and Application Layer Transport Security (ALTS). Trusted nodes are attested to verify integrity, shielding user data from broader infrastructure. Inputs, model inferences, and computations are kept only as long as needed to fulfill queries.
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