Inference is where generative AI meets the real world. Models are trained behind the scenes, but they become the main attraction in live deployments where they run millions of times. Many industry executives and observers assumed inference would follow a simpler, more predictable deployment path. We've experienced an inflection point: from infrastructure to business model, from sustainability to performance, inference is where value is created - or lost.
Inference alters how we plan capacity, allocate capital, design workloads, and organize operational teams.
In this report, Schneider Electric and World Wide Technology have collaborated to equip decision-makers with the context and clarity needed to act. To understand the necessary considerations for inference to scale reliably, efficiently, and with agility.
Included in this whitepaper:
Five types of inference workloads and the unique needs that lay the groundwork for IT and infrastructure
