AI & ML Nature Is Weird

Standard AI models are getting so good at math they can now organize a massive shipping fleet just as perfectly as the world's most specialized software.

April 6, 2026

Original Paper

Analysis of Optimality of Large Language Models on Planning Problems

Bernd Bohnet, Michael C. Mozer, Kevin Swersky, Wil Cunningham, Aaron Parisi, Kathleen Kenealy, Noah Fiedel

arXiv · 2604.02910

The Takeaway

This breaks the common belief that language models are just 'stochastic parrots' that cannot do rigorous logic. It suggests that large-scale reasoning models are developing genuine internal tools for optimal strategic planning.

From the abstract

Classic AI planning problems have been revisited in the Large Language Model (LLM) era, with a focus of recent benchmarks on success rates rather than plan efficiency. We examine the degree to which frontier models reason optimally versus relying on simple, heuristic, and possibly inefficient strategies. We focus on the Blocksworld domain involving towers of labeled blocks which have to be moved from an initial to a goal configuration via a set of primitive actions. We also study a formally equi