Kitchen Confidential: FoodMonitor and the Compliance AI Reality Check
FoodMonitor shows why real compliance AI needs auditable evidence, not just video understanding with a rulebook attached.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Memory Foam: When AI Stops Storing Everything and Starts Learning From It
A business-focused reading of two new arXiv papers showing why long-horizon AI needs grounded abstraction, validated experience, and selective internalisation rather than ever-larger memory stores.
Mind the Readout: Why AI Gets Smarter When We Stop Worshipping the Output
A business-focused synthesis of three arXiv papers showing why AI reliability depends on representation, readout, and compute discipline—not just bigger outputs or heavier architectures.
Mixed Feelings: When LLM Batching Stops Being Obviously Better
A systems paper shows why mixed batching is not a universal default for LLM inference, and why bandwidth-aware scheduling may matter more than scheduler fashion.
Relight at Your Own Risk: WildRelight and the Synthetic Vision Reality Check
WildRelight shows why real-world relighting needs measurement infrastructure, not just prettier synthetic demos.
Same Causal Effect, Different Bill: Derivation Graphs and the Estimand Trap
A mechanism-first reading of derivation graphs, showing why equivalent do-calculus expressions can lead to very different estimators, costs, and operational decisions.
Stale Gradients, Fresh Economics: CoCD’s Lightweight Route to Zeroth-Order AI
Coherent Coordinate Descent turns stale finite-difference gradients into a practical mechanism for lighter zeroth-order optimisation, with clear promise and equally clear scale boundaries.
Control, Alt, Generate: Why AI Needs Control Surfaces, Not Bigger Prompts
Two distant-looking papers show the same production lesson: generative AI becomes useful when teams can measure, constrain, and localise the behaviour that actually matters.
Furniture Has a Chain of Command: Why Dense Scene AI Needs Object Roles, Not One Bigger Generator
HetScene shows why dense 3D indoor generation improves when AI separates room structure from local object placement instead of treating every object as the same kind of token.
Judge, Jury, and Benchmark: Why LLM Evaluation Needs Fresh Cases, Not Bigger Leaderboards
CoEval shows how task-specific LLM evaluation can become renewable, contamination-resistant, and less dependent on a single judge model.