Imagine a control system that learns, optimizes in real-time, and integrates seamlessly with both field assets and cloud-native AI platforms.  This is the next chapter of industrial process automation. Already implemented at the largest Oil refinery in the world, Software-defined control systems break the traditional link between hardware and logic. This separation allows for dynamic control, centralized intelligence, and flexible deployment across complex industrial environments. When integrated with time-series foundation models, these systems harness AI for intelligent loop control, advanced process optimization, and even reinforcement learning, driving unprecedented levels of performance in control environments. In the latest episode of the AI in Manufacturing podcast, I sat down with Huize Zhang to explore this transformation. Huize is the Vice President at SUPCON, China’s leading DCS provider, and the founder of FREEZONEX, an open-source IIoT platform.   Here’s the outline of our conversation: -The Control Platform of The Future -Open Standards and Platforms -AI-Driven Optimization in Process Industries -Time-Series Pre-Trained Transformers -Reinforcement Learning in Process Industries -UNS Integration with AI Agents