2026 Event Schedule

AI is reshaping infrastructure demands, but not all models—or silicon—are created equal. This session breaks down the "Four Pillars" of AI infrastructure: workload types, model profiles, silicon choices, and the latency/bandwidth trade-offs that drive design decisions. From training vs. inference requirements to the realities of large language model deployments, we'll explore how to balance performance, cost, and efficiency.

Using real-world case studies—including when API-driven AI costs spiral—we'll examine deployment models (on-premises vs. SaaS/API), chip competition (GPUs, TPUs, ASICs, emerging silicon), and how evolving workloads impact power and cooling strategies. Attendees will leave with a practical framework for aligning AI models to infrastructure, a clear view of the trade-offs between control and cost, and a checklist for future-proofing their data centers as the AI landscape rapidly evolves.