The store will not work correctly when cookies are disabled.
AppleCare+
By proceeding you are agreeing to be bound by the Terms and Conditions of Sale and the AppleCare+ Terms & Conditions. These are standard terms on which we intend to rely. For your own benefit and protection it is important that you read the Terms and Conditions of Sale, the AppleCare+ Terms and Conditions, the Key Facts Document and the Initial Disclosure Document carefully before you do so. If you do not understand anything, or have any questions, please call the Apple Contact Centre www.apple.com/uk/support/.
I am resident in the United Kingdom, but I do not reside on the Isle of Man or the Channel Islands.
Are you looking for a unique modular storage platform for the next decade of machine intelligence? Do you want to accelerate your data-first modernization and be AI-ready and eliminate tiered data pipelines, infrastructure silos, inefficient scaling and scale-out limitations, complex management, and low productivity? HPE GreenLake for File Storage MP offers enterprise performance at AI scale to accelerate the most data-intensive applications with a resilient architecture designed to scale to exabyte capacities; a simpler, intuitive cloud operational experience with radically simple file data management and rich data services; enhanced productivity of data scientists and line of business application owners with faster time to insights; and more value from all your data with a simple setup and a global namespace for collaboration for competitive advantage.
What is new supporting point: Higher compute and storage density options with HPE Alletra Storage MP modules for AI and large-scale, performance-oriented unstructured data lakes [5] Ultra-efficient all-NVME with inline similarity data reduction (de-deduplication and compression) that works even for previously compacted data End-to-end HPE GreenLake experience for unstructured data management Acceleration of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) training and inferencing in conjunction with the consolidation of other workloads
