Hugin & Munin Journal

Official promotional image for Slow Horses Season 6. Apple TV promotional material, used for review and commentary. By its third episode, Slow Horses Season 6 has its agents running for their lives, and they barely stop until the finale. Yet watching the episodes week by week, I found myself increasingly impatient. The series was never short of danger; what it lacked was the steady accumulation of discoveries that made its earlier conspiracies so absorbing. The change in viewing habits may have contributed to that impression. Most previous seasons passed quickly when watched over a few evenings, while the weekly release exposed the structure of individual episodes. But I suspect the difference runs deeper. The sixth season places more emphasis on immediate danger than on the political and institutional manoeuvring that once made Slow Horses distinctive. The story begins with the deaths of people connected to Slough House, MI5's dumping ground for agents whose...

New research suggests that the brain begins from two distinct developmental systems. The deeper puzzle is why something so biologically composite feels, from the inside, like one self. Editorial image generated by the author. The adult brain is a single organ. A study published in Nature Neuroscience in September 2026 suggests that developmentally, it may not begin that way. Using lineage tracing in mouse embryos alongside experiments with human pluripotent stem cells, researchers found evidence for an anterior neural progenitor population that gives rise to the forebrain and midbrain and a separate posterior population committed to the hindbrain. The authors describe the brain as a “composite organ” formed from two lineage-restricted progenitors . The finding quickly produced a more dramatic formulation. Stanford Medicine announced the research under the headline that the human brain is “two separate organs.” That should not be read as meaning that an adult human possesses tw...

The strange history of a finished story that became increasingly difficult to finish. Editorial image generated by the author. When The Name of the Wind appeared in 2007, Patrick Rothfuss offered readers something unusually reassuring for the beginning of an epic fantasy series. The sequels were already written. “I’ve already written them,” he told SFFWorld shortly before the novel’s release . Readers, he said, would not have to wait forever: the remaining books would appear on a regular schedule, one per year. His next two novels were already “good to go.” Nineteen years later, that promise has acquired an almost legendary quality. The Wise Man’s Fear eventually appeared in 2011, four years rather than one after the first book. The Doors of Stone , the intended third volume of The Kingkiller Chronicle , still has no announced publication date. Rothfuss has published shorter work set in Temerant, most recently the extensively revised The Narrow Road Between Desires in 2023,...

A rule simple enough to describe with eight black-and-white combinations produces a pattern whose most basic long-term properties remain unproved. Stephen Wolfram has now invited AI to try to change that. On 23 October 2026, Stephen Wolfram invited artificial intelligence agents to tackle a challenge that has resisted mathematicians for decades. The subject was Rule 30, an elementary cellular automaton whose behaviour looks far more complicated than its instructions. Since 2019, Wolfram has offered three prizes of $10,000 each for resolving fundamental questions about the sequence it generates. The invitation comes as AI systems are beginning to contribute to original mathematical research. Yet one of the Rule 30 problems reverses the familiar promise of better algorithms. Instead of finding a faster way to calculate an answer, an AI might establish a limit on how fast any algorithm can calculate it. That possibility needs care. A proof of the proposed computational lower bound ...

AI progress is supposed to be running into limits almost everywhere at once. Frontier models are consuming much of the readily available high-quality public text; giant training clusters strain semiconductor supply chains and electricity infrastructure; more elaborate reasoning systems consume increasing amounts of computation after training; and AI agents can perform impressive individual tasks while remaining unreliable over long workflows. Yet frontier AI is not behaving like a technology at its ceiling. Stanford’s 2026 AI Index reports a roughly 30 percentage-point improvement in a single year on Humanity’s Last Exam, a benchmark deliberately designed to remain difficult for advanced models. On OSWorld, which tests an agent’s ability to operate computers, performance rose from roughly 12 percent to 66.3 percent. The same report captures the other side of the picture: agents still fail roughly one in three structured benchmark attempts, while systems capable of solving extremely ...