Google has unveiled Private AI Compute, a new privacy-focused cloud system designed to power advanced AI features while safeguarding user data. The technology closely mirrors Apple’s Private Cloud Compute, extending Google’s AI processing capabilities to the cloud without compromising privacy.
The company says the system allows AI tasks that exceed a device’s on-board processing power to be executed securely in the cloud — without exposing sensitive data to Google or third parties.
“For decades, Google has developed privacy-enhancing technologies to improve AI use cases,” the company wrote in a blog post. “Private AI Compute combines our most capable Gemini models with the same security and privacy assurances you expect from on-device processing. It’s part of our commitment to deliver AI with safety and responsibility at the core.”
Built for Security and Isolation
Private AI Compute operates on custom Tensor Processing Units (TPUs) integrated with Titanium Intelligence Enclaves (TIE), hardware-based secure environments designed to isolate and protect user data. These enclaves act as a sealed “fortified space” for processing AI workloads. Devices connect using remote attestation and encrypted channels, ensuring that even Google’s engineers and administrators cannot access the underlying user information.
Coming First to Pixel 10
The system will debut with the Pixel 10 lineup, powering a new wave of cloud-assisted AI experiences. Among them are enhancements to Magic Cue, a contextual assistant that provides real-time suggestions, and an upgraded Recorder app that can summarize transcripts in multiple languages. Both rely on Google’s Gemini models, which require more computational power than what is available on-device.
A Direct Parallel to Apple’s Private Cloud Compute
Google’s new approach mirrors Apple’s Private Cloud Compute, which launched last year as part of the company’s Apple Intelligence ecosystem. Apple’s system uses custom servers built with Apple silicon, operating as verifiable, sealed environments for AI tasks. Both companies are moving toward hybrid AI architectures — balancing the speed and privacy of on-device AI with the computational scale of the cloud.
The Bigger Picture
Private AI Compute marks another step in Google’s broader effort to position Gemini as a privacy-conscious AI ecosystem capable of competing with Apple’s tightly integrated AI framework. By anchoring its system in hardware-based security and encrypted data flows, Google is signaling that it intends to make privacy not just a compliance feature, but a competitive advantage.
