Ukrainians brace for -20C despite energy truce: 'It will be a catastrophe' It's not the electricity cuts that Yulia Hailunas struggles with most after the Russian airstrikes. Like so many Ukrainians, she's had no central heating since Russia launched a wave of targeted attacks on the power grid in January. So Yulia now lives in a long, quilted coat and hat in her flat, and rests her feet on a saucepan-full of hot water to keep them from freezing. If that's not enough, she lifts weights for 10 minutes to get warm. When the weather outside is above zero, it's just about bearable.

Donald Trump is the only world leader capable of stopping Vladimir Putin from threatening Europe, according to Poland's President Karol Nawrocki. In an interview with Radio 4's Today programme he said the Russian leader was not to be trusted, but that Europe needed to do everything it could to support President Trump in his efforts to end the war in Ukraine. President Nawrocki was already well-known as a firm supporter of Donald Trump even before he landed in Britain for meetings with PM Sir Keir Starmer and others. Now, he says that with Vladimir Putin's Russia threatening his country as well as central and eastern Europe, the US president was the only person who could, as he put it, solve this problem - as well as ending the war in Ukraine. Referring to last September's mass incursion by Russian drones, when more than 20 uncrewed aircraft crossed into Poland from Belarus and Ukraine, President Nawrocki called it an extraordinary situation, adding that until that time, no Nato member state had experienced a drone attack on that scale.

Archaeologists say they located a Black Death burial site containing some of a village's 12,000 dead. Breakthroughs, discoveries, and DIY tips sent six days a week. The Black Death () killed as much as half of Europe's total population between 1346 and 1353, so there are a of bodies buried across the continent. For example, contemporary accounts from Thuringia--a state in central Germany--report that about 12,000 plague victims died around Erfurt amid the city's outbreak in 1350. But despite multiple accounts attesting to this devastation, none of the 11 mass graves could be pinpointed for centuries.

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 ...

When you purchase through links in our articles, we may earn a small commission. Here are 15 geeky gifts and gadgets I'd buy for myself! 'Tis the season to get the perfect nerd gift. It could be for yourself or even your geeky friends. I don't know about you, but I love the holidays.

We present a non-linear AI-model designed to reconstruct monthly mean anomalies of the European temperature and precipitation based on the Euro-Atlantic Weather regimes (WR) indices. WR represent recurrent, quasi-stationary, and persistent states of the atmospheric circulation that exert considerable influence over the European weather, therefore offering an opportunity for sub-seasonal to seasonal forecasting. While much research has focused on studying the correlation and impacts of the WR on European weather, the estimation of ground-level climate variables, such as temperature and precipitation, from Euro-Atlantic WR remains largely unexplored and is currently limited to linear methods. The presented AI model can capture and introduce complex non-linearities in the relation between the WR indices, describing the state of the Euro-Atlantic atmospheric circulation and the corresponding surface temperature and precipitation anomalies in Europe. We discuss the AI-model performance in reconstructing the monthly mean two-meter temperature and total precipitation anomalies in the European winter and summer, also varying the number of WR used to describe the monthly atmospheric circulation. We assess the impact of errors on the WR indices in the reconstruction and show that a mean absolute relative error below 80% yields improved seasonal reconstruction compared to the ECMWF operational seasonal forecast system, SEAS5. As a demonstration of practical applicability, we evaluate the model using WR indices predicted by SEAS5, finding slightly better or comparable skill relative to the SEAS5 forecast itself. Our findings demonstrate that WR-based anomaly reconstruction, powered by AI tools, offers a promising pathway for sub-seasonal and seasonal forecasting.

Large Language Models increasingly possess capabilities that carry dual-use risks. While data filtering has emerged as a pretraining-time mitigation, it faces significant challenges: labeling whether data is harmful is expensive at scale, and given improving sample efficiency with larger models, even small amounts of mislabeled content could give rise to dangerous capabilities. To address risks associated with mislabeled harmful content, prior work proposed Gradient Routing (Cloud et al., 2024) -- a technique that localizes target knowledge into a dedicated subset of model parameters so they can later be removed. We explore an improved variant of Gradient Routing, which we call Selective GradienT Masking (SGTM), with particular focus on evaluating its robustness to label noise. SGTM zero-masks selected gradients such that target domain examples only update their dedicated parameters. We test SGTM's effectiveness in two applications: removing knowledge of one language from a model trained on a bilingual synthetic dataset, and removing biology knowledge from a model trained on English Wikipedia. In both cases SGTM provides better retain/forget trade-off in the presence of labeling errors compared to both data filtering and a previously proposed instantiation of Gradient Routing. Unlike shallow unlearning approaches that can be quickly undone through fine-tuning, SGTM exhibits strong robustness to adversarial fine-tuning, requiring seven times more fine-tuning steps to reach baseline performance on the forget set compared to a finetuning-based unlearning method (RMU). Our results suggest SGTM provides a promising pretraining-time complement to existing safety mitigations, particularly in settings where label noise is unavoidable.

The Nobel-winning author, whose newest book is out this week, discusses work by a few of her favorite writers. The Nobel Prize winner Olga Tokarczuk's fiction is known for its interest in the porosity of boundaries--between nations, between ethnicities, between fiction and reality, consciousness and dreams. As her novels and stories stage the constant flux of national borders, particularly in Eastern Europe (Tokarczuk is Polish), they also delight in supernatural and science-fictional elements. In " House of Day, House of Night," out from Riverhead this week, she writes, "All over the world, wherever people are sleeping, small, jumbled worlds are flaring up in their heads, growing over reality like scar tissue." Not long ago, Tokarczuk sent us some remarks about a few of her favorite sci-fi and speculative-fiction writers, whose books mix the fantastical and the prosaic masterfully.

The adoption of artificial intelligence (AI) offers transformative potential for small and medium-sized enterprises (SMEs), particularly in enhancing financial decision-making processes. However, SMEs often face significant barriers to implementing AI technologies, including limited resources, technical expertise, and data management capabilities. This paper presents a conceptual model for the adoption of AI in financial decision-making for SMEs. The proposed model addresses key challenges faced by SMEs, including limited resources, technical expertise, and data management capabilities. The model is structured into layers: data sources, data processing and integration, AI model deployment, decision support and automation, and validation and risk management. By implementing AI incrementally, SMEs can optimize financial forecasting, budgeting, investment strategies, and risk management. This paper highlights the importance of data quality and continuous model validation, providing a practical roadmap for SMEs to integrate AI into their financial operations. The study concludes with implications for SMEs adopting AI-driven financial processes and suggests areas for future research in AI applications for SME finance.

More than just rats and fleas added to the'perfect storm' plague. Photograph of the fresco Trionfo della Morte, taken at its original location in the Camposanto Monumentale in Pisa. The fresco, known as the "Triumph of Death" and attributed to the painter Buonamico Buffalmacco, is not precisely dated; scholarly estimates range from 1335 to 1350. While it does not depict the Black Death explicitly, the selected detail shows victims of an epidemic from diverse social backgrounds, their souls carried off by demons. Breakthroughs, discoveries, and DIY tips sent every weekday.