Scaling Laws

Opening — Why this matters now Long-context models have become the quiet arms race of the LLM ecosystem. Every few months, someone announces another context window milestone—128k, 1M, or “effectively unlimited.” The implication is obvious and seductive: if a model can read everything, it must understand everything. The paper behind this article is less impressed. It asks a colder question: what actually happens inside a model as context grows, and whether more tokens translate into more usable intelligence—or just more noise politely attended to. ...

In the world of physics, when particles in a system become so densely packed or cooled that they lock into place, we call this phenomenon jamming. Sand becoming rigid under pressure, traffic freezing on a highway, or even glass transitioning from fluid to solid—all are governed by this principle. What if the same laws applied to intelligence? A provocative new paper, Consciousness as a Jamming Phase by Kaichen Ouyang, suggests just that: large language models (LLMs) exhibit consciousness-like properties not as a software quirk but as a physical phase transition, mirroring the jamming of particles in disordered systems. ...