Why Frontier Models Stay Spiky
Frontier models stay spiky because useful work is contextual and counterfactual paths are ungradable. Post-training quality is a grader problem, not a pretraining-size problem.
Frontier models stay spiky because useful work is contextual and counterfactual paths are ungradable. Post-training quality is a grader problem, not a pretraining-size problem.