Fifty years after her death in New York, Hannah Arendt has become the most popular philosopher of our time. For good reason: Her views are just as timely as ever. It must be so nice to play Hannah Arendt. No fewer than five actresses are on stage this evening at the Deutsches Theater Berlin to portray the philosopher. The piece is an adaptation of the graphic novel by American illustrator Ken Krimstein about the philosopher's life, called The Three Escapes of Hannah Arendt," combined with scenes from the famous interview that journalist Günter Gaus conducted with Arendt in 1964 for German public broadcaster ZDF. The article you are reading originally appeared in German in issue 49/2025 (November 28th, 2025) of DER SPIEGEL. They play Arendt and a few of her contemporaries, the philosopher Martin Heidegger, the writer Walter Benjamin, her husband Heinrich Blücher. There is a great deal of speech in the play, especially from Arendt herself. The places of her life are ticked off, her ...

Kant's life was famously dull, but he was less of a hermit than is often supposed.

Wargames are simulations of conflicts in which participants' decisions influence future events. While casual wargaming can be used for entertainment or socialization, serious wargaming is used by experts to explore strategic implications of decision-making and experiential learning. In this paper, we take the position that Artificial Intelligence (AI) systems, such as Language Models (LMs), are rapidly approaching human-expert capability for strategic planning -- and will one day surpass it. Military organizations have begun using LMs to provide insights into the consequences of real-world decisions during _open-ended wargames_ which use natural language to convey actions and outcomes. We argue the ability for AI systems to influence large-scale decisions motivates additional research into the safety, interpretability, and explainability of AI in open-ended wargames. To demonstrate, we conduct a scoping literature review with a curated selection of 100 unclassified studies on AI in wargames, and construct a novel ontology of open-endedness using the creativity afforded to players, adjudicators, and the novelty provided to observers. Drawing from this body of work, we distill a set of practical recommendations and critical safety considerations for deploying AI in open-ended wargames across common domains. We conclude by presenting the community with a set of high-impact open research challenges for future work.

Can Ukraine restore its pre-war borders? Why are Tomahawk missiles for Ukraine a'red line' for Russia? Is Russia testing NATO with aerial incursions in Europe? Lithuania, a small Baltic state bordering Belarus and Russia's Kaliningrad, is adapting to new tensions between NATO and Moscow. A member of the Lithuanian Riflemen's Union takes part in a military exercise in central Lithuania [Nils Adler/Al Jazeera] Two members of the Lithuanian Riflemen's Union take part in a military exercise in central Lithuania [Nils Adler/Al Jazeera] On a nearby building is an illuminated decorative Z, a symbol used to show support for the Russian military's full-scale invasion of Ukraine, which began in February 2022.

'Kissing Trump's a**': President mocks Canada's obsequious PM as he begs for tariff relief World's most invasive predator terrorizing East Coast is delicious and should be eaten to stop its spread, experts say Clash of the White House titans: Two of Trump's most powerful lieutenants go to WAR with each other - after vicious leak sent shockwaves AMANDA PLATELL: I never thought I'd feel sorry for Harry. There's one thing he'd do anything to defend... and now Meghan's trampled all over it White House insider who says WAR with Venezuela is inevitable... as Trump's lethal options are laid out Jimmy Kimmel's audience boom comes crashing down as he loses 71% of viewers in one week Lynn put her strange symptoms down to being a busy mum. AOC hit by shockingly crude sex insult by White House after she mocked'TINY' Stephen Miller Friends fear for new CBS News boss Bari Weiss, claiming her wife thinks she sold out... and her new job will'consume her life' Biden ordered CIA cover-up of his'corrupt' business ties to Ukraine, astonishing secret files show We've lost FOURTEEN stone on weight-loss jabs... and it's changed our lives in ways you'd NEVER expect. Jerry Jones slapped with fine by NFL for making rude gesture to fans... but Cowboys owner gives baffling excuse And a humiliating lifeline: Backroom secrets of Taylor Swift and Blake Lively... after hit new song Inside the rise of'kidfluencers' and the hidden toll of turning childhood into million-dollar content A US Air Force jet designed to collect intelligence on enemy radar systems was spotted making circles over Russia, following rising tensions with Moscow . Flight tracking data showed the RC-135U'Combat Sent' taking off from England early Tuesday, flying over the Baltic states and looping around Kaliningrad, the Russian exclave between Poland and Lithuania, before returning to the UK.

Thinking LLMs solve complex tasks at the expense of increased compute and overthinking on simpler problems, while non-thinking LLMs are faster and cheaper but underthink on harder reasoning problems. This has led to the development of separate thinking and non-thinking LLM variants, leaving the onus of selecting the optimal model for each query on the end user. We introduce OptimalThinkingBench, a unified benchmark that jointly evaluates overthinking and underthinking in LLMs and also encourages the development of optimally-thinking models that balance performance and efficiency. Our benchmark comprises two sub-benchmarks: OverthinkingBench, featuring simple math and general queries in 72 domains, and UnderthinkingBench, containing 11 challenging reasoning tasks along with harder math problems. Using novel thinking-adjusted accuracy metrics, we extensively evaluate 33 different thinking and non-thinking models and show that no model is able to optimally think on our benchmark. Thinking models often overthink for hundreds of tokens on the simplest user queries without improving performance. In contrast, large non-thinking models underthink, often falling short of much smaller thinking models. We further explore several methods to encourage optimal thinking, but find that these approaches often improve on one sub-benchmark at the expense of the other, highlighting the need for better unified and optimal models in the future.

How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? The Kremlin has announced it has "no alternative" but to continue waging war, as it pushed back on United States President Donald Trump's sudden sea change towards Ukraine that saw him brand Russia a "paper tiger". Kremlin spokesperson Dmitry Peskov hit back at Trump's claim that Ukraine could in effect win the war, declaring on Wednesday that Russia would be continuing its offensive on Ukraine "to ensure our interests and achieve the goals".

How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? Russia and Belarus have begun large-scale military exercises, raising alarm across NATO's eastern flank just days after Warsaw accused Moscow of sending attack drones across Polish airspace, a major escalation that sent shivers through Europe. The Zapad 2025 manoeuvres, which run from Friday until Tuesday, are taking place as Russian forces continue their slow advance in Ukraine and intensify air attacks on Ukrainian cities.

Understanding and classifying human cognitive brain states based on neuroimaging data remains one of the foremost and most challenging problems in neuroscience, owing to the high dimensionality and intrinsic noise of the signals. In this work, we propose an ensemble-based graph representation method of functional magnetic resonance imaging (fMRI) data for the task of binary brain-state classification. Our method builds the graph by leveraging multiple base machine-learning models: each edge weight reflects the difference in posterior probabilities between two cognitive states, yielding values in the range [-1, 1] that encode confidence in a given state. We applied this approach to seven cognitive tasks from the Human Connectome Project (HCP 1200 Subject Release), including working memory, gambling, motor activity, language, social cognition, relational processing, and emotion processing. Using only the mean incident edge weights of the graphs as features, a simple logistic-regression classifier achieved average accuracies from 97.07% to 99.74%. We also compared our ensemble graphs with classical correlation-based graphs in a classification task with a graph neural network (GNN). In all experiments, the highest classification accuracy was obtained with ensemble graphs. These results demonstrate that ensemble graphs convey richer topological information and enhance brain-state discrimination. Our approach preserves edge-level interpretability of the fMRI graph representation, is adaptable to multiclass and regression tasks, and can be extended to other neuroimaging modalities and pathological-state classification.

We propose a test for abstract causal reasoning in AI, based on scholarship in the philosophy of causation, in particular on the neuron diagrams popularized by D. Lewis. We illustrate the test on advanced Large Language Models (ChatGPT, DeepSeek and Gemini). Remarkably, these chatbots are already capable of correctly identifying causes in cases that are hotly debated in the literature. In order to assess the results of these LLMs and future dedicated AI, we propose a definition of cause in neuron diagrams with a wider validity than published hitherto, which challenges the widespread view that such a definition is elusive. We submit that these results are an illustration of how future philosophical research might evolve: as an interplay between human and artificial expertise.