For decades, Google has developed privacy-enhancing technologies (PETs) to improve a wide range of AI-related use cases. Today, we’re taking the next step in building helpful experiences that keep users safe with Private AI Compute in the cloud, a new AI processing platform that combines our most capable Gemini models from the cloud with the same security and privacy assurances you expect from on-device processing. It’s part of our ongoing commitment to deliver AI with safety and responsibility at the core.

AI is evolving to become even more helpful, personal and proactive. It’s moving from completing simple requests to AI that can anticipate your needs with tailored suggestions or handle tasks for you at just the right moment. This progression in capability requires advanced reasoning and computational power that at times goes beyond what’s possible with on-device processing.

That’s why we built Private AI Compute: to unlock the full speed and power of Gemini cloud models for AI experiences, while ensuring your personal data stays private to you and is not accessible to anyone else, not even Google. Private AI Compute allows you to get faster, more helpful responses, making it easier to find what you need, get smart suggestions and take action.

How Private AI Compute protects your data in the cloud

As a pioneer in the field of responsible AI, Private AI Compute in the cloud is our next step in AI processing technology. It builds off of the industry-leading security and privacy safeguards that we embed to keep you in control of your experiences and your data safe, guided by our Secure AI Framework, AI Principles and Privacy Principles.

Private AI Compute is a secure, fortified space for processing your data that keeps your data isolated and private to you. It processes the same type of sensitive information you might expect to be processed on-device. Within its trusted boundary, your personal information, unique insights and how you use them are protected by an extra layer of security and privacy in addition to our existing AI safeguards.

Private AI Compute is built on a multi-layered system that is designed from the ground up around core security and privacy principles:

• One integrated Google tech stack: Private AI Compute runs on one seamless Google stack powered by our own custom Tensor Processing Units (TPUs). World-class privacy and security is integrated into this architecture with Titanium Intelligence Enclaves (TIE). This design enables Google AI features to use our most capable and intelligent Gemini models in the cloud, with our high standards for privacy and the same in-house computing infrastructure you already rely on for Gmail and Search.
• No access: Remote attestation and encryption are used to connect your device to the hardware-secured sealed cloud environment, allowing Gemini models to securely process your data within a specialized, protected space. This ensures sensitive data processed by Private AI Compute remains accessible only to you and no one else, not even Google.

Using Private AI Compute for more helpful, private AI experiences

Private AI Compute enables on-device features to perform with extended capabilities while retaining their privacy assurance. Using this technology, Magic Cue is getting even more helpful with more timely suggestions on the latest Pixel 10 phones. And with the help of Private AI Compute, the Recorder app on Pixel is able to summarize transcriptions across a wider range of languages.

This is just the beginning. Private AI Compute opens up a new set of possibilities for helpful AI experiences now that we can use both on-device and advanced cloud models for the most sensitive use cases. We look forward to sharing more updates, and you can review our technical brief to learn more about how Private AI Compute advances AI privacy.

https://blog.google/technology/ai/google-private-ai-compute/