The Weirdly Small AI That Cracks Reasoning Puzzles [HRM]

How can we build AI that can solve reasoning puzzles? A recent paper, "Hierarchical Reasoning Model," shocked the AI community with promising results on Sudoku, maze puzzles, and ARC-AGI benchmarks. This video provides an overview of the Hierarchical Reasoning Model. 00:00 Reasoning tasks 00:22 Hierarchical Reasoning Models' results 01:07 Problem setup 02:00 Transformer 02:37 Chian-of-thought reasoning 03:14 Recurrent models 04:31 HRM - Architecture 06:12 HRM - Gradient approximation 07:48 Specialized vs general models References: - Hierarchical Reasoning Model: https://arxiv.org/abs/2506.21734 - End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking https://arxiv.org/abs/2202.05826 - Scaling up test-time compute with latent reasoning: A recurrent depth approach: https://arxiv.org/abs/2502.05171 - Looped Transformers are Better at Learning Learning Algorithms, https://arxiv.org/abs/2311.12424 - Looped Transformers as Programmable Computers, https://arxiv.org/abs/2301.13196 Video made with Manim: https://www.manim.community/