Google’s Private AI Compute will let users securely run even the most powerful AI models on your smartphone (www.techradar.com)

Google has launched Private AI Compute, a cloud-based secure execution platform designed to run its Gemini models for smartphones and other devices. The service offloads heavy reasoning and compute that’s impractical on-device, while promising strong privacy guarantees: Google says data processed in Private AI Compute is confined to a “specialized, protected space” and is accessible only to the user (not even Google). Core technologies include Google’s Tensor Processing Units (TPUs) for high-throughput inference and Titanium Intelligence Enclaves (TIE) for hardware-backed isolation, plus plans for remote attestation, developer inspection tools, and a bug-bounty program to boost transparency and accountability. For AI/ML practitioners, Private AI Compute signals a shift in edge-cloud model deployment: developers can deliver larger, more capable models to mobile users without needing expensive on-device silicon, enabling features like Pixel 10’s Magic Cue to perform context-aware suggestions with cloud-grade reasoning. Technical implications include new workflows for secure remote execution, verification of trust boundaries, and performance trade-offs between latency, privacy-preserving enclave execution, and cloud costs. The move also mirrors Apple’s Private Cloud Compute; both suggest a growing industry trend toward confidential cloud compute that preserves user privacy while scaling model capability.