This white paper, AI News 22|The Power Bottleneck and the Rise of Green Language Protocols, builds on a BBC report highlighting the unprecedented energy and infrastructure challenges posed by AI data centers. By 2029, global investment in AI compute facilities is projected to reach US$3 trillion, with individual training racks costing millions and consuming electricity at the scale of thousands of households. The paper argues that this crisis is not only about hardware but about the absence of a protocol layer. Current AI models still rely on brute-force token prediction, wasting enormous amounts of compute and power. The proposed framework — SER (Structured Expression Resonance), CSL (Collaborative Structural Linguistics), and Rhythm OS — functions as a green language protocol. It reduces blind token guessing, avoids repetitive computation through role separation, and introduces rhythm-based runtime orchestration. Just as CUDA unlocked GPUs for deep learning, these protocols can unlock AI for sustainable human–AI collaboration. The transition from “bigger models and more power” to “smarter protocols and greener intelligence” represents not just a technical fix but a civilizational shift in how intelligence is scale