Скачать или смотреть Tiny 27M Parameter AI Shocks the Industry! (here is the future!)

A team of researchers from Google DeepMind, OpenAI, and xAI have introduced a revolutionary new brain-inspired architecture called the Hierarchical Reasoning Model (HRM). Unlike today’s massive LLMs, HRM is a tiny 27-million-parameter system that achieves near-perfect accuracy on tasks like extreme Sudoku puzzles and complex mazes—benchmarks where frontier models score zero.

In this video, we explore why HRM matters, how it challenges the “bigger is better” scaling paradigm, and what it reveals about the future of AI research. We’ll look at:

Why HRM’s two-module design (a high-level “CEO” and a low-level “Worker”) is a breakthrough.

How it combines the strengths of recurrent networks and transformers to overcome past limitations.

Why NVIDIA and other leaders are now saying that smaller, modular AI systems may be the future.

How this shift echoes the long-running debate between AI “scalers” and AI “designers.”

This isn’t just about one new model, it’s about a pendulum swing in AI research, away from brute-force scaling and toward smarter, brain-inspired architectures.

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Related links and sources:

Hierarchical Reasoning Model(HRM): https://arxiv.org/pdf/2506.21734

Small language models are the future of Agentic AI (Nvidia): https://arxiv.org/pdf/2506.02153

Bitter Lesson(Richard Sutton scale-pilling a generation of researchers): http://www.incompleteideas.net/IncIde...

Learn more about the subject(Arvind Nagaraj Medium Blog Post):   / the-loop-is-back-why-hrm-is-the-most-excit...  

Sapient Intelligence: https://www.sapient.inc/

The original Transformer paper (Attention is All You Need): https://arxiv.org/pdf/1706.03762

Visualization of Transformers (3Blue1Brown):    • Attention in transformers, step-by-step | ...  

Curriculum Sampling (New RL technique used in the training of GPT-5): https://www.emergentmind.com/topics/r...

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