AI and the Network: Optimizing Network Design and Operations to Meet AI Demands

Cloud-native network architectures provide required scalability and flexibility

High throughput and sophisticated multi-tenant traffic management are crucial for AI applications.

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AI has a voracious data hunger and requires robust data center networking that delivers the performance needed to leverage its full capabilities.

This report explores how optimal network design and operations can reduce costs while boosting performance and maximizing utilization of precious GPU resources. High throughput and sophisticated multi-tenant traffic management are crucial for AI applications, which demand rapid processing of large data volumes. Advanced traffic engineering, enabled by SDN frameworks, allows for dynamic resource allocation, ensuring high-priority AI tasks receive the necessary bandwidth.

Additionally, cloud-native network architectures provide required scalability and flexibility and steer clear of legacy system pitfalls. This alignment between AI needs and network capabilities maximizes current technological investments and future-proofs enterprises against evolving AI demands.