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25 Jun 2025Form Number
LP2245PDF size
8 pages, 391 KBSubscribed to LP2245.
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Abstract
Organizations are increasingly moving their AI workloads to edge where data is generated and to achieve real time inference for making instantaneous decisions and to avoid challenges with latency, bandwidth and privacy requirements in cloud-based architectures. High-definition video streams, sensor data and other data intensive resources consume more bandwidth and processing time and processing this data locally at Edge reduces complexities in data movement and privacy and security requirements.
This solution brief outlines optimal performance and availability for AI workloads at the edge running on Lenovo ThinkAgile HX360 V2 Edge utilizing Nutanix software stack.
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