Engineers are designing artificial intelligence (AI)-powered data platforms that transform businesses, show insight into customer behavior, and help leaders plan for the future.
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IBM has the capabilities to complete the AI infrastructure puzzle with data management. It starts with extreme performance but expands to the workflow level for scalable ingest, tagging and workloads that run from edge to core to cloud. This holistic view includes multi-protocol storage support, data orchestration, maintaining only a single copy of the data, backup, archive, data recovery and data life cycle management for storage economics, all underpinned with data security and cyber resiliency.
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NVIDIA has a solution-oriented approach to make AI easy to use and adopt. Their GPUs consistently have the highest-performing compute capabilities available, often making it challenging to feed data quickly enough. To overcome this obstacle, NVIDIA relies on partners like IBM to help provide high-performance storage. NVIDIA offers the toolset data scientists and analysts need and has a GPU direct-to-storage (GDS) capability to improve data performance with GPU memory. NVIDIA also acquired Mellanox in 2020 to add high-end networking capability.
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