#UWC26: Optimizing AI Inference Performance: Testing Networks at Scale

Check out videos from Upperside Conference's recent World Congress (formerly known as MPLS World Congress): https://ngi.fyi/mpls26yt

Daniel Munteanu, Senior Technical Product Manager at Keysight Technologies, discusses the critical challenges facing AI inference deployments in production networks. As AI transitions from development to production, organizations face mounting pressure to optimize their infrastructure investments amid supply chain constraints. Munteanu examines the technical requirements spanning network transport, security layers, and AI inference server stacks that determine deployment success. He introduces Keysight's approach to addressing these challenges through emulation and analytics testing capabilities designed to validate infrastructure performance before production deployment.

- How AI inferencing is reshaping production network requirements
- The critical importance of infrastructure optimization in AI deployments
- Key performance and security considerations across the AI stack
- How emulation and analytics platforms help identify bottlenecks and inefficiencies
- Strategies for testing and benchmarking AI inference infrastructures at scale

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Видео #UWC26: Optimizing AI Inference Performance: Testing Networks at Scale канала NextGenInfra