RCR’s AI Infrastructure Forum – From training to inferencing: Scaling AI sustainably

AI demand is growing at a pace never seen before. Data centers, chipsets, power grids, and supply chains are being stretched to their limits as the race to scale accelerates. We are learning as we build—yet the cost, complexity, and environmental impact highlight the need for smarter, more sustainable approaches.

Through expert presentations, cross-industry panels, and analyst insights, the forum explores the full stack of AI infrastructure. We’ll examine strategies for upgrading legacy data centers, designing greenfield facilities, scaling edge deployments, and ensuring multi-site synchronization and operational efficiency. We’ll also tackle the political, regulatory, and societal pressures shaping how AI infrastructure is deployed worldwide.

RCR’s AI Infrastructure Forum 2025 brings together the full ecosystem to define the roadmap for building AI’s backbone and confront this defining challenge: expanding AI infrastructure sustainably, efficiently, and at scale.

Spirent will be participating in two sessions:

Automating the entire network lifecycle: Leveraging AI within the infrastructure
A presentation by Anil Kollipara

Topics include: Overcoming hybrid cloud and legacy hardware integration challenges; Using unified observability to detect threats and optimize performance; Building self-healing, event-driven networks that prevent outages; Standardization and consolidation for efficient, resilient operations; AI-driven analytics to enhance automation and resilience in data center operations; Simplifying network.

Stress-testing networks for AI workloads
A presentation by Stephen Douglas

Topics include: Why AI workloads stress networks differently: burstiness, uplink intensity, synchronization across sites; Performance and reliability: ensuring throughput, low latency, and resilience at scale; Security risks: AI-driven attacks, adversarial traffic, and data poisoning across inference pipelines; Testing approaches: traffic emulation, digital twins, large-scale stress tests, and AI-assisted monitoring.