Recursive AI Models Outperform Scaling Laws
An analysis of Hierarchical and Tiny Recursive Models demonstrating that inference-time recursion and latent memory outperform parameter scaling. These architectures achieve state-of-the-art results on complex reasoning tasks with a fraction of the compute, signaling a shift in AI development strategy.
