Infrastructure Reality After AI

Infrastructure Reality After AI

The Infrastructure Reality After AI Works

QT Singapore

Hosted by Factor

Overview

As AI moves from innovation to a core business capability, infrastructure shifts from a background concern to a strategic enabler or constraint. As AI use cases scale and deliver value, organizations must recognize the important differences across AI workloads—from building and adapting models to using them in day-to-day operations—each shaping technology and infrastructure decisions with materially different consequences.

Against this backdrop, data sovereignty, regulatory obligations, and the physical distance between data and compute increasingly influence performance and operating costs, were responsiveness drives differentiation.

Drawing on real-world experience across hyperscalers, neo-cloud/sovereign cloud providers, colocation, and on-premise environments, this roundtable examines how leaders are navigating the trade-offs of workload placement as AI scales.

What to expect

Agenda

Partners

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