AI is no longer limited by training—it’s inference that defines real-world impact. For any AI application—whether a chatbot, recommendation engine, or vision system—success or failure depends on how well it serves users in real time. Inference is the life-and-death stage of AI: if responses are too slow, too costly, or inconsistent across regions, adoption stalls.

Today’s AI applications are increasingly born global, designed to reach users everywhere from day one. Yet scaling inference worldwide exposes critical bottlenecks: underutilized GPUs driving up costs, and complex cross-region deployment creating latency gaps and inconsistent user experiences.

This session will explore why inference at scale is the next frontier of AI, the barriers AI applications face when going global, and how Zenlayer Distributed Inference can enable real-time AI experiences anywhere in the world.