Large-Scale Test-Time Compute

Noam Brown's thesis that model capability is now a function of inference budget (tokens/cost/time): with good scaffolding modern models keep improving for weeks before plateauing, so 'how capable is the model?' is ill-posed without naming the budget — a root cause that breaks benchmarking, safety evals, and fast-takeoff forecasts; plus the first budget-matched test of *where* to spend the marginal token, where independent parallel sampling beats both sequential refinement and letting a meta agent rewrite the harness