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Machine Learning Operationalization in the Enterprise

As enterprises move beyond experimentation to more widespread adoption of AI, a vast majority of them are running into “last mile” issues related to model deployment and management. Gartner predicts that by 2021, at least 50 percent of machine learning models built with the intention of being operationalized will not see the light of day. […] Read More

Enabling a Cloud-Like Experience for On-Premises GPU Infrastructure

In most enterprises today, GPU infrastructure is in high demand for computing-intensive machine learning and deep learning applications. If your organization is embarking on an AI initiative, it’s likely that your data science teams want access to GPU resources for their environments. However, enterprise IT teams face several challenges when managing and provisioning GPU-enabled infrastructure. […] Read More