
The episode discusses the need for an AI controller to manage grid operations and its potential impact on energy infrastructure.
The energy transition conversation focuses on what connects to the grid. Far less attention goes to whether anyone is coordinating what those assets do once connected. AI training runs swing hundreds of megawatts in seconds as GPUs checkpoint and restart a profile that looks like a generator tripping offline. At distribution level, millions of inverter-based resources create localised variability that overwhelms individual circuits even when aggregate models look healthy. The planning tools in use today were designed for neither problem. Host Bridget van Dorsten is joined by Kay Aikin, CEO and Founder of Dynamic Grid, energy engineer, grid architecture advisor to the DOE-supported GridWise Architecture Council, and contributor to the UN Environmental Program's building decarbonisation work. Kay unpacks what an AI training facility actually does to the grid with full GPU load for hours or days, then a drop to ten percent in seconds during checkpointing. She talks about how at the scale now planned, the Stargate project in Texas alone could represent ten percent of ERCOT disappearing in four seconds. The behaviour is stochastic and cannot be modelled with traditional statistical…
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