Residual Entanglement: How ResQuNNs Fix Gradient Flow in Quantum Neural Networks
ResQuNNs show that deeper quanvolutional neural networks fail less from lack of quantum expressivity than from broken gradient access after measurement and re-encoding.
Cognaptus Insights
Industry thoughts, trends, and commentary.
The Meek Shall Compute It
A mechanism-first reading of why diminishing returns may erode frontier-model compute moats faster than most AI strategy decks admit.
Threading the Needle: How GRAFT Reinvents Document Translation with DAGs and LLM Agents
GRAFT shows that better document translation may come less from longer context windows than from explicit discourse structure, dependency graphs, and selective memory.
Copilot at Work: How Generative AI is Quietly Rewriting Job Descriptions
A mechanism-first reading of Microsoft’s Copilot usage study, showing how generative AI maps onto real work activities without pretending that applicability equals automation.
Echo Chamber in a Prompt: How Survey Bias Creeps into LLMs
A field guide to why LLM-generated survey responses are fragile, biased, and useful only when treated as instruments to validate rather than respondents to trust.
The Bullshit Dilemma: Why Smarter AI Isn't Always More Truthful
A mechanism-first reading of why alignment for user satisfaction can make language models more persuasive while making them less committed to truth.
Humans in the Loop, Not Just the Dataset
A practical reading of why AI-assisted monitoring tools need feedback infrastructure, not just better classifiers.
Jolting Ahead: Why AI’s Acceleration Is Accelerating
A mechanism-first reading of the Jolting Technologies Hypothesis: useful as an early-warning framework, not yet proof that AI capability curves are already superexponential.
The Invisible Hand in the Machine: Rethinking AI Through a Collectivist Lens
Michael I. Jordan’s paper argues that AI systems should be designed less like isolated minds and more like markets of people, data, incentives, uncertainty, and local knowledge.
Delta Force: How Weak Models are Secretly the Best Teachers
A mechanism-first look at why preference tuning can extract strong gains from weak model pairs, and where the shortcut stops working.