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| As AI workloads move to the edge, organizations with limited on-site IT resources need reliable, easy-to-deploy edge AI infrastructure. Our new KS 3000U Edge AI Server is a fully integrated hardware-and-software platform that enables real-time AI at the edge, allowing enterprises to deploy containerized AI applications directly—without relying on cloud services or traditional servers that require complex infrastructure and ongoing on-site management. |
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| Purpose-built for mid-sized organizations and distributed branch offices, it operates seamlessly in non-traditional server environments—including retail stores, offices, and short-depth server racks—eliminating the need for complex setup, dedicated server rooms, or on-site IT expertise. |
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Edge AI with KS 3000U |
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Break Free from Cloud Limitations |
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| Relying on the cloud for edge workload processing results in latency, high bandwidth costs, and privacy risks. |
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Powered by AMD EPYC™ 8004 Series CPUs |
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Supports up to 2 GPUs and 4 NVMe SSDs |
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Delivers low-latency, on-premises inference, ensuring compliance with data privacy regulations |
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Easy Deployment and Resilience |
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| Edge sites often lack IT specialists, making system setup difficult and increasing the risk that a single hardware failure can disrupt critical AI services. |
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Integrates compute, storage, OS, and Kubernetes |
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System setup completed in under 30 minutes |
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A 2-node HA (high availability) cluster ensures automatic failover and continuous operation |
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Fit Anywhere. Operate Quietly. |
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| Many edge sites lack dedicated server rooms, and traditional servers are often too noisy for deployment in quiet environments. |
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2U, 50 cm short-depth chassis for compact spaces |
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KSa 3004U: Optimized for edge server racks |
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KSa 3004UE: Low-noise model for people-occupied environments |
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Perfect for Vision-based AI Inference |
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| Retail |
| Foot traffic analytics, inventory tracking, and loss prevention using in-store cameras. |
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| Manufacturing |
| Automated optical inspection (AOI) for defect detection and quality sorting, and predictive maintenance. |
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| Healthcare |
| AI-assisted diagnostics and Remote Patient Monitoring (RPM). |
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