An AI-enabled data center must be able to concurrently and efficiently service the entire spectrum of activities involved in the AI and DL process, including data ingest, training, and inference. The IT infrastructure supporting an AI-enabled datacenter must adapt and scale rapidly, efficiently, and reliably, as data volumes grow and application workloads become more intense, complex, and diverse. It must seamlessly and continuously handle transitions between different phases of experimental training and production inference in order to provide more accurate answers, faster. In short, the IT infrastructure is key to realizing the full potential of AI, and DL in business and research.
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