New AI architecture delivers 100x faster reasoning than LLMs with just 1,000 training examples

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all while being significantly smaller and more data-efficient.

The architecture, known as the Hierarchical Reasoning Model (HRM), is inspired by how the human brain utilizes distinct systems for slow, deliberate planning and fast, intuitive computation. The model achieves impressive results with a fraction of the data and memory required by today’s LLMs. This efficiency could have important implications for real-world enterprise AI applications where data is scarce and computational resources are limited.

The limits of chain-of-thought reasoning

When faced with a complex problem, current LLMs largely rely on chain-of-thought (CoT) prompting, breaking down problems into intermediate text-based steps, essentially forcing the model to “think out loud” as it works toward a solution.

While CoT has improved the reasoning abilities of LLMs ...