dailyai.report

Nathan Lambert predicts the performance gap between open and closed models will narrow by mid-2026. He argues that synthetic data and distillation will accelerate this convergence. This trend suggests that proprietary moats will shrink. Practitioners should expect high-tier capabilities to migrate toward open-source weights, reducing reliance on expensive closed APIs for complex tasks.