Training AI models to convergence is a computationally intensive, complex, and iterative process that requires operating on massive volumes of data. Once trained, these AI models are integrated within enterprise applications to infer or make predictions about new data that they’re presented with. There are a growing number of industries like finance, healthcare, and public sector where the data used for both AI model training and inference is sensitive and/or regulated, such as personally identifiable information (PII). With NVIDIA Confidential Computing, enterprises can ensure confidentiality of data during AI training and inference—whether on-premises, in the cloud, or at the edge.