Counterfactuals, Concepts, and Causality: XAI Finally Gets Its Act Together
A causal concept-based XAI framework shows why useful model explanations need more than heatmaps, concept labels, and wishful thinking.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Digging Deeper with Bayes: Why AI May Finally Fix Mineral Exploration
A decision-science reading of why AI’s real value in mineral exploration may be reducing false-positive drilling, not replacing geologists.
Flame Tamed: Can LLMs Put Out the Internet’s Worst Fires?
A comparison-based reading of new research on LLMs as online mediators, separating moderation, model performance, human style, and practical deployment boundaries.
Prompting on Life Support: How Invasive Context Engineering Fights Long-Context Drift
A mechanism-first reading of Invasive Context Engineering, a training-free proposal for keeping LLM control instructions alive inside long conversations and agentic reasoning loops.
Scan, Plan, Report: When Agentic AI Starts Thinking Like a Radiologist
A mechanism-first look at why Radiologist Copilot matters less as a report generator and more as a workflow engine for high-stakes medical AI.
Stuck on Repeat: Why LLMs Reinforce Their Own Bad Ideas
A mechanism-first reading of Martingale Score, a new unsupervised way to detect when LLM reasoning becomes prior-protecting rather than truth-seeking.
Blunders, Patterns, and Predictability: What n‑Gram Models Teach Us About Human Chess
A mechanism-first look at how skill-specific n-gram models turn chess move prediction from optimal play into human behavior modeling.
Checkmating the Hype: What LLM CHESS Reveals About 'Reasoning Models'
A mechanism-first reading of LLM Chess, showing why interactive benchmarks expose failures that static reasoning tests often miss.
From Building Blocks to Breakthroughs: Why RL Finally Teaches Models to Think
A mechanism-first reading of why reinforcement learning helps models compose memory and context only after supervised training has built the right atomic skills.
Ground and Pound: How Iterative Reasoning Quietly Redefines GUI Grounding
Chain-of-Ground shows that GUI grounding can improve not only by training larger models, but by forcing multimodal models to revisit their own visual hypotheses.