Irwan discusses the inherent difficulties in extrapolating machine learning techniques as they scale, highlighting a fundamental issue rather than mere reproducibility problems. He emphasizes that the lack of rigorous baselines complicates research, particularly given the high costs and time involved in conducting experiments. The conversation reveals a shift from meticulous study designs to navigating through noise to find effective solutions.
