AI Showcase: Innovations to Scale AI Data Centers | Keysight

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Validate AI data centers with system-wide visibility

AI is pushing networks to their limits — trillion-parameter models, millions of GPUs, and nonstop upgrade cycles.

For network architects, the pressure is immense: one weak link can disrupt everything.

Discover three innovations that let you validate every data path and every network component at 1.6T speeds — with deep insight across all layers.

Ready to upgrade with full-system confidence? Watch the on-demand webinar on the latest AI data center test solutions — free and on your schedule.

Explore AI data center test use cases

Keysight AI Data Center Builder

How to emulate AI data center workloads

Learn how KAI Data Center Builder emulates real-world AI workloads to test every data path in your system at scale.

An image of a laptop displaying interconnect performance

How to validate 1.6T Ethernet network performance

Learn how Keysight 1.6T Network Performance Tester emulates Ethernet traffic at speeds up to 1.6 Tbps to ensure system-level reliability, stability, and interoperability.

A laptop displaying a screenshot of advanced photovoltaic inverter test software for evaluating single and multi-input inverters

How to optimize 1.6T transceiver manufacturing tests

Learn how Keysight 1.6T Optical Transceiver Tester accelerates 1.6T transceiver development and manufacturing tests.

Fuel your AI data center knowledge

Check out our curated papers on the latest trends in AI data centers.

White Papers 2025.04.10

AI at Full Throttle

AI at Full Throttle

This white paper discusses the challenges and solutions related to high-speed Ethernet networks in the context of rapidly growing AI applications. It highlights the critical need for advanced networking technologies to support the increasing demands of AI workloads.

2025.04.10

White Papers 2025.03.12

800G / 1.6T Data Center Transceiver Test

800G / 1.6T Data Center Transceiver Test

This white paper delves into AI data center trends, addressing how hyperscale data center architects and operators must scale networks from 400G to 800G / 1.6 terabit (1.6T) Ethernet to meet these demands. This guide explores key strategies to increase interconnect bandwidth, ensure interoperability and reliability, and reduce test time, power, and cost.

2025.03.12

White Papers 2025.02.27

Improving Scalability in AI Data Center Clusters

Improving Scalability in AI Data Center Clusters

As AI models grow more complex and larger, effectively scaling data center clusters has evolved into a mission-critical priority for organizations aiming to stay competitive. This white paper explores the rise of AI clusters, highlights the key scaling challenges — particularly within network infrastructure — and demonstrates how advanced emulation solutions can help you overcome these obstacles.

2025.02.27

White Papers 2025.04.18

AI Infrastructure: Optimized for Model Training

AI Infrastructure: Optimized for Model Training

This white paper discusses the critical infrastructure needed for efficient AI model training, emphasizing the role of network capabilities in handling vast data flows and minimizing delays. It outlines challenges in model training and innovative solutions that can enhance performance.

2025.04.18

Ready to scale your AI data centers?

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