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
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
Standard evaluations tell you whether your AI system performs. They don’t tell you whether it still knows what it’s talking about.
The distinction matters because performance and epistemic reliability can decouple
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
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
