The race toward industrial-scale “general intelligence” is no longer primarily constrained by algorithms but by compute and energy. Frontier AI labs and hyperscalers are reaching the limits of available electricity, grid capacity, cooling, and semiconductor throughput. Efficiency—not size—will determine who can deploy general intelligence at scale. Metrics such as tokens-per-watt and tokens-per-FLOP now signal real productivity per unit of energy and compute. This episode examines how the shift toward energy- and compute-bounded AI development is reshaping technology, economics, geopolitics, and governance, and provides recommendations to ensure sustainable scaling.