The Painted Window
Why Claude's Self-Reports Aren't What They Look Like
There's a particular kind of conversation that happens thousands of times a day between humans and AI systems, and
Theory
Foundational concepts in information theory, compression, and epistemic integrity.
The "You" Problem: What AI Consciousness Discourse Gets Wrong
A new field has emerged with remarkable speed. It has journals, taxonomies, conferences, and a growing body of literature. It concerns itself with the psychology of artificial intelligence — with whether AI systems have
Causal Structure, Derived Geometry, and the Problem of Time: A Preliminary Framework
Preliminary statement. Formalization is ongoing.
For several years I have been developing a theoretical framework in which causal structure is ontologically fundamental: more fundamental than spacetime, more fundamental than quantum mechanics, and more
Open-Loop Generation: On the Architectural Basis of LLM Output Errors
A recent paper from Tsinghua University identifies what it calls H-Neurons — a sparse subpopulation of neurons whose activation patterns predict hallucination events in large language models [1]. The finding is real and probably
The Measurement Problem in AI Risk: Why Output Variance Doesn't Capture Epistemic Drift
Anthropic's recent paper "The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?" makes an important empirical observation: frontier models show increasing output variance