Artificial Intelligence (AI) and Deep Learning (DL) are essential business and research tools which provide organizations with valuable insights into their data. However, the complexity of processing and storing this data requires an optimized data path and a storage solution capable of handling these workloads whether in an on-premises datacenter, via the cloud, or a hybrid infrastructure. Legacy storage solutions are not designed for the low-latency, highly parallel, mixed workload requirements found in many stages of the AI data lifecycle.
Building the right AI-enabled environment including compute, networks, applications, and storage takes foresight and planning whether using on- premises, cloud, or a hybrid infrastructure. An AI-enabled datacenter requires intelligent infrastructure that provides flexibility, speed at any scale, and data insight to successfully leverage the value of data. This paper describes how an integrated intelligent infrastructure and optimized data path with AI-enabled storage is required to meet these challenges.