The Complexity of Scaling in AI

This chapter explores the intricate relationship between computational power and accuracy in image classification, detailing how diminishing returns impact model performance. It discusses the inefficiencies of deep neural networks versus human learning, and highlights the tension between the increasing reliance on AI and the scaling laws that govern its effectiveness. By examining algorithmic advancements and trends in compute, the discussion underscores the challenges and uncertainties inherent in maximizing AI performance.