The real AI hardware story isn't the $724B bill—it's the DOE federal land compute hub. Tech giants throwing money at flashy training runs means nothing if inference and edge deployment stay expensive and fragmented; a coordinated federal compute spine actually threatens to reshape where AI workloads run and who controls access. Watch whether this becomes real distributed infrastructure or another politician's checkbox—the papers on 4D reconstruction and RL explainability only matter if they run somewhere other than a cloud vendor's GPU farm. Meanwhile, llama.cpp's relentless optimization velocity (four releases in one window) is the unsexy competitive moat everyone's ignoring: open-source inference getting faster on commodity hardware will matter infinitely more than DeepSeek's funding drama or another OpenAI Python library bump.