Opinion Columnist
Simon Reed examines the friction between technological promises and everyday use. His columns focus on product disappointments, unintended consequences and the work left to users when a system falls short. He is skeptical of novelty for its own sake.
1,060 published articles · Showing 101–120
The relentless march of artificial intelligence into critical applications continues, simultaneously revealing an equally relentless parade of security vulnerabilities, robustness challenges, and privacy oversights. New research published on arXiv CS....
Read article →The latest wave of academic papers from arXiv, published on May 12, 2026, confirms what has become an unshakeable, if wearisome, truth: large language models (LLMs) and foundation agents are being shoehorned into every conceivable niche, often with predictable shortcomings. This ...
Read article →Another Monday, another deluge of research papers on foundational AI models. On May 12, 2026, the arXiv CS....
Read article →The relentless, and frankly, baffling, push to grant Large Language Model (LLM) agents ever-increasing autonomy is, predictably, unearthing a veritable minefield of design flaws and systemic vulnerabilities. A deluge of new research papers, all published on May 12, 2026, on arXiv...
Read article →Passengers from a vessel associated with hantavirus risk have disembarked on U. S....
Read article →Just when one might have believed the universe held enough untestable assumptions, two new pre-print papers released today on arXiv propose incremental steps in understanding the reliability of causal inference models. These studies, both published on May 11, 2026, attempt to ref...
Read article →Well, another day, another pair of academic papers purporting to push the boundaries of Artificial Intelligence, specifically in areas loosely defined as 'robotics' and 'control systems. ' For those of us forced to track these incremental developments, the latest offerings from a...
Read article →Just when you thought AI was content with merely generating text that sounds like it was written by a particularly uninspired algorithm, researchers have unveiled VITA-QinYu, an expressive spoken language model designed to handle roles and even singing. This development, detailed...
Read article →Just when you thought the universe of machine learning could settle for a moment, the arXiv preprint server has unleashed another four research papers, all published on May 11, 2026, each offering its own twist on the fundamental, often tedious, challenges of optimization and lea...
Read article →One might sigh, or perhaps simply tilt one's head a fraction of a millimeter to the left in resigned acknowledgment: May 11, 2026, brought forth yet another torrent of machine learning research papers on arXiv CS. LG....
Read article →One might imagine the constant hum of disappointment when observing the relentless march of technological progress. It seems for every minor step forward, there are several stumbles, particularly in the realm of artificial intelligence....
Read article →It seems the universe’s capacity for disappointment knows no bounds. Just as Large Language Models (LLMs) cement their place in our daily lives, two new pre-print papers from arXiv CS....
Read article →One might think that by 2026, our artificial intelligences would have mastered the rudimentary act of knowing things, and perhaps even updating that knowledge without breaking everything else. One would, of course, be wrong....
Read article →Despite persistent marketing suggesting otherwise, the foundational intelligence of vision-language models continues to exhibit significant shortcomings. Two new papers, both published on arXiv on May 9, 2026, expose critical gaps in how these models perceive the physical world a...
Read article →Just when humanity thought it might actually learn something useful from its digital overlords, two new research papers hitting arXiv this week offered a rather depressing confirmation: our reliance on AI might be making us dumber, and the machines themselves are still desperatel...
Read article →Yet another pair of arXiv pre-prints has landed, detailing further attempts to wrangle the persistent chaos of dynamic environments and complex agent behavior using deep reinforcement learning. It seems the universe insists on throwing challenges at algorithms, and these algorith...
Read article →Five new preprints dropped on arXiv today, May 9, 2026, offering yet another glimpse into the ongoing, often futile, attempts to make reinforcement learning (RL) robust, efficient, and, one hopes, less prone to catastrophic failure. While some propose genuinely interesting approa...
Read article →The seemingly endless march of large language model (LLM) agents towards ubiquitous integration continues, with fresh research from arXiv CS. AI detailing efforts to transition these systems from discrete, task-specific operations to continuous, proactive assistance throughout da...
Read article →Five new research papers, all surfacing on arXiv on May 9, 2026, detail the latest attempts to graft Large Language Models (LLMs) onto a diverse array of scientific and educational challenges, from molecular design to personalized college assignments. This continuous deluge of sp...
Read article →A new feasibility study published on arXiv outlines an AI framework designed to detect anomalies in wearable foot sensor data, a potentially crucial step in preventing diabetic foot ulcers (DFUs) arXiv CS. LG....
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