Reasoning That Knows When to Shut Up
Epistemic fidgeting, metacognitive failure in silicon, and why the Qualcomm paper on edge reasoning matters more than its benchmark tables suggest.
Filed under · 7 essays
AI Architecture
Model design, neuroscience-inspired AI, scaling, hardware constraints
The Smuggled Ideas
Four papers that quietly crossed the AI–cognition border — and what got lost in transit.
The Score Went Up. The Model Didn't.
LLM benchmarks are a best guess at genuine model capability: conditional statistics reported as if they were intrinsic traits of the model.
The Context Wars
The quiet discipline that will determine whether AI tells the truth: context engineering, and why failures start in what a model is given to reason about.
What Neuroscience Knows That AI Ignores
Why the next leap in artificial intelligence will come from structure, not scale — and why a century of brain science has already drawn the blueprint.
Continuous Thought Machines? Giving Neural Networks Time to Think
Time as the medium in which computation unfolds, measured and synchronised at the level of individual neurons.
Architecture Wars: How Physics Shapes AI Strategy
The pursuit of AI supremacy has reached an inflection point where fundamental physics, rather than algorithmic ingenuity alone, dictates competitive advantage.