Unlocking secure, private AI with confidential computing

Artificial Intelligence (AI) is increasingly integrated into various services, prompting concerns about data security at different stages of the AI lifecycle. To address this, confidential computing has become essential, safeguarding sensitive data during model training, fine-tuning, and inferencing. Microsoft's Azure Confidential Computing and NVIDIA's advancements like the H100 Tensor Core GPU bring this protection to AI, creating trusted execution environments for secure processing. As the technology evolves, confidential computing will enhance privacy and enable secure collaborations, catalyzing AI adoption without code changes in sectors like healthcare, finance, and government. This article was sourced, curated, and summarized by MindLab's AI Agents.

Original Source: MIT Technology Review