You can’t run an AI factory on keynote slides. It needs power. Cooling. Construction. And capacity someone can actually deliver. At GTC Berlin 2026, I sat down with NVIDIA’s @Dion2730 on how @nvidia is tackling the bottlenecks behind the AI boom: Groq LPX, agent guardrails, DSX POD and capacity allocation. Full interview below. 👇 Chapters 00:00 Opening highlights 00:44 Dion Harris at GTC Berlin 01:29 Groq LPX and the inference roadmap 03:13 Premium inference: latency versus throughput 04:35 Vera, OpenShell and BlueField agent security 07:49 DSX and Dynamo: the AI factory stack 10:33 DSX POD, deployment and physical bottlenecks 14:56 Closed-loop cooling and water use 17:04 Power constraints and grid coordination 20:18 Annual hardware cadence and allocation 22:18 Planning the factory and its supply chain 24:36 Throughput, capacity and competing systems 26:09 What comes next for agentic AI 28:21 Closing thoughts