Heads You Lose: Why Ablation-Reversible Interpretability Doesn’t Transfer
A mechanism-first reading of why necessary, decodable, and ablation-reversible attention heads still may not carry transferable computation.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Range Anxiety: Why Standoff LWIR Needs More Than One Clean Look
A mechanism-first reading of a Set-Transformer approach that uses range-diverse LWIR measurements to make atmospheric compensation less underconstrained.
Sink or Skill: Why Agent Experience Needs Governance
A practical reading of two agent-learning papers showing why reusable AI experience needs abstraction, valuation, pruning, and transfer testing.
The Path of Least Assurance: Why AI Reliability Lives Between the Steps
A practical reading of three arXiv papers showing why AI systems must be evaluated through their trajectories, intermediate states, and tool-use processes—not just their final outputs.
Flush Before You Trust: The Locality Trick Behind Incremental Sheaf Cohomology
A mechanism-first reading of incremental sheaf cohomology, separating cheap lazy updates from exact global verification.
Graph Work, Not Graph Worship: RAGA Turns RAG Into an Auditable Knowledge Operation
RAGA’s real lesson is not that knowledge graphs magically beat vector RAG, but that enterprise retrieval needs provenance, lifecycle control, and repairable consistency.
Logs Are Not Lineage: The Accountability Layer AI Agents Are Missing
A practical reading of evidence tracing and execution provenance as the infrastructure layer that turns opaque AI-agent activity into auditable, controllable business systems.
Mind the Flux: Why Average Accuracy Fails Where the Towers Aren’t
FLUXtrapolation shows why AI models for sparse environmental systems need deployment-shaped stress tests, not comforting average-error leaderboards.
Mind the Tail: Quantum Rare-Event Sampling Without the Discovery Tax
A mechanism-first reading of how quantum rare-event sampling changes the cost of finding tail scenarios, and why the advantage depends on aggregate rare-tail mass rather than black-swan theatre.
Stop Model Shopping: Build the AI Control Tower
A practical reading of three arXiv papers showing why AI value depends on evaluation, routing, and context-aware interpretation rather than blind faith in a single large model.