Everything on Inference Optimization

Outer refinement loops are the primary driver of performance gains in recursive models. Iterative self-correction at inference time yields significant accuracy improvements without increasing model complexity.

Impact: Provides a low-cost method to boost model accuracy by simply increasing inference-time compute, rather than retraining larger models.

— from Recursive AI Models Outperform Scaling Laws · Y Combinator Startup Podcast· May 01, 2026