NVIDIA Confidential Computing preserves the confidentiality and integrity of AI models and algorithms that are deployed on Blackwell and Hopper GPUs. Independent software vendors (ISVs) can distribute and deploy their proprietary AI models at scale on shared or remote infrastructure from edge to cloud....
La tecnologia NVIDIA Confidential Computing tutela la riservatezza e l'integrità dei modelli e degli algoritmi IA distribuiti su GPU Blackwell e Hopper. I fornitori di software indipendenti (ISV) possono ora distribuire e implementare i modelli IA proprietari su larga scala, su infrastruttura co...
CUDA Toolkit 12.4 Enhances Support for NVIDIA Grace Hopper and Confidential Computing The latest release of CUDA Toolkit, version 12.4, continues to push accelerated computing performance using the latest NVIDIA GPUs. This post explains the new... ...
NVIDIA Confidential Computing uses CPUs and NVIDIA GPUs to protect the data in use, rendering it invisible and inaccessible by malicious actors and even the owners of the host machines. NVIDIA Hopper architectureintroducedConfidential Computingcapabilities and theNVIDIA Blackwell architec...
Confidential computing is a way of processing data in a protected zone of a computer’s processor, often inside a remote edge or public cloud server, and proving that no one viewed or altered the work.
“Our collaboration with NVIDIA has been pivotal in launching Azure confidential VMs with NVIDIA H100 Tensor Core GPUs,” said Vikas Bhatia, head of product for Azure confidential computing at Microsoft. “This work combines Microsoft’s expertise in building out the cloud infrastructure necessary to...
Intel and Nvidia deliver Confidential Computing technologies that establish independent TEE’s on the CPU and GPU, respectively. For a customer, this presents an attestation challenge, arguably requiring attestation from two different services to gather the evidence needed to verif...
However, NVIDIA has recently brought confidential computing capabilities to the H100 Tensor Core GPU and Microsoft has made this technology available in Azure. This has the potential to protect the entire confidential AI lifecycle—including model weights, training data, and inference workloads. ...
Until recently, confidential computing only worked on central processing units (CPUs). However, NVIDIA has recently brought confidential computing capabilities to the H100 Tensor Core GPU andMicrosoft has made this technology availablein Azure. This has the potential to protect the entire confidential...
Confidential computing can address both risks: it protects the model while it is in use and guarantees the privacy of the inference data. The decryption key of the model can be released only to a TEE running a known public image of the inference server (e.g., t...