NVIDIA Confidential Computing to Help Expand Apple's Private Cloud Compute

NVIDIA GPUs to support server-side inference for Apple Intelligence, announced at WWDC. NVIDIA GPUs with Confidential Computing are now used for confidential inference in Apple's Private Cloud Compute (PCC), as it expands beyond Apple's data centers to Google Cloud. Unveiled during Apple's annual WWDC gathering for developers from around the globe, NVIDIA GPUs will support server-side inference for Apple Foundation Models , custom-built by Apple and Google, leveraging the technologies behind the Gemini family of models.

NVIDIA is collaborating with Apple and Google to support some of the next-generation Apple Intelligence features, using NVIDIA Blackwell GPUs with Confidential Computing integrated into Private Cloud Compute's hardware security architecture running on Google Cloud. Confidential Computing Matters for the Era of AI Experiences NVIDIA Confidential Computing provides a hardware-based security layer for accelerated AI workloads. The technology protects data while it's being processed by isolating workloads in trusted execution environments and enabling systems to cryptographically verify that the infrastructure has not been tampered with before any sensitive data is sent to the server.

For end users, NVIDIA Confidential Computing means that no one, not even the system's builders, can look at their data, chats or conversations. Adoption of NVIDIA Confidential Computing at this scale reflects a broader shift in AI infrastructure: As AI experiences combine on-device and cloud-based processing for their tasks, there's a need for high-performance, server-side inference while maintaining strong privacy and security guarantees. How Confidential Computing Enforces Privacy and Trust NVIDIA Confidential Computing reflects NVIDIA's commitment to trustworthy AI and includes these key capabilities: Hardware-rooted trust , helping establish that systems are running on genuine, untampered NVIDIA GPUs.

Encrypted communication paths , helping protect data as it moves between components. Remote attestation , enabling software to verify the security state of the platform before releasing sensitive data. Support for accelerated AI inference and training , helping organizations run privacy-sensitive workloads without moving away from GPU performance.

These capabilities are increasingly relevant for AI services that need to process sensitive information while maintaining strong user privacy controls. Learn more about NVIDIA Confidential Computing and NVIDIA AI cybersecurity solutions.