How the US left Ukraine exposed to Russia's winter war Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? Russian forces launched multiple attacks on Ukraine's Zaporizhia region, killing one person and injuring seven others over the past day, the region's military administration said on the Telegram messaging platform. The attacks involved 448 drones as well as 163 artillery strikes, causing damage to 136 homes, cars and other structures, the military administration said. Russian forces also continued shelling Ukraine's Donetsk region, forcing 173 people, including 135 children, to evacuate front-line areas over the past day, regional governor Vadym Filashkin said on Telegram.

How the US left Ukraine exposed to Russia's winter war Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? Russia-Ukraine talks resume in Geneva as US claims'meaningful' progress Day two of the third round of trilateral talks between Russia, Ukraine and the United States is under way in Geneva, Switzerland, as the four-year anniversary of Russia's full-scale invasion of its neighbour looms next week, with vague references to "progress" but nothing tangible yet shared. Little has been made public about the talks' contents since negotiations kicked off on Tuesday behind closed doors and continued on Wednesday morning. The thorniest of issues, territory and the yielding of it, remains the key sticking point.

How the US left Ukraine exposed to Russia's winter war Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? Three people were killed in a Russian drone attack on a civilian car in the city of Mykolaivka in the Kramatorsk district of Ukraine's Donetsk region, the state's emergency service said in a statement. The three people, as well as another person injured in the attack, were workers at the Sloviansk Thermal Power Station, the Kyiv Independent news outlet reported. A woman died after being injured in a Russian drone attack in Ukraine's Zaporizhia region, Governor Ivan Fedorov wrote on the Telegram messaging app.

Could Ukraine hold a presidential election right now? Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? 'Ukraine is running out of men, money and time' A deadly exchange of drone strikes has killed one person in Ukraine and one in Russia and cast doubts on the prospects of a ceasefire before another round of negotiations to end the war next week. News of the deaths comes as Ukrainian President Volodymyr Zelenskyy and US Secretary of State Marco Rubio signalled hurdles to reaching an agreement in Geneva as the conflict is about to enter its fifth year.

Is the fall of Pokrovsk inevitable? Is Trump losing patience with Putin? Here's where things stand on Monday, November 24. United States Secretary of State Marco Rubio told reporters in Geneva that "a tremendous amount of progress" was made during talks in the Swiss city on Sunday and that he was "very optimistic" that an agreement could be reached in "a very reasonable period of time, very soon". Rubio also said that specific areas still being worked on from a 28-point peace plan for Ukraine, championed by US President Donald Trump, included the role of NATO and security guarantees for Ukraine.

Volker Turk, United Nations high commissioner for human rights, attends the Human Rights Council in Geneva on Sept. 8. | REUTERS Geneva - A few tech giants accumulating massive power coupled with artificial intelligence is posing huge global rights challenges and needs regulation, the U.N. human rights chief said in an interview. Amid increasing worries over threats to democracy and with a growing number of countries at risk of sliding towards autocracy, Volker Turk said a key concern was the seeming unbridled power of a small number of technology companies. In an interview this week at the UN rights office overlooking Lake Geneva, he pointed to how seven or eight big tech companies now boast more wealth than the entire economies of even industrialized nations. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

As deep learning (DL) technologies advance, their application in automated visual inspection for Class III medical devices offers significant potential to enhance quality assurance and reduce human error. However, the adoption of such AI-based systems introduces new regulatory complexities-particularly under the EU Artificial Intelligence (AI) Act, which imposes high-risk system obligations that differ in scope and depth from established regulatory frameworks such as the Medical Device Regulation (MDR) and the U.S. FDA Quality System Regulation (QSR). This paper presents a high-level technical assessment of the foreseeable challenges that manufacturers are likely to encounter when qualifying DL-based automated inspections -- specifically static models -- within the existing medical device compliance landscape. It examines divergences in risk management principles, dataset governance, model validation, explainability requirements, and post-deployment monitoring obligations. The discussion also explores potential implementation strategies and highlights areas of uncertainty, including data retention burdens, global compliance implications, and the practical difficulties of achieving statistical significance in validation with limited defect data. Disclaimer: This paper presents a technical perspective and does not constitute legal or regulatory advice.

This allows plugins to solve not only simple toy problems, but also more complex ones, where e.g. an accelerator device is known to behave in an unusual fashion but it is not feasible to fix the issue at the source[29]. Because plugins are independent packages with their own dependency declarations, they can scale from minimal proof-of-concept implementations to complex state machines that call out to subprocesses or request data from the accelerator's monitoring devices. Because plugins have their own versioning scheme, faulty upgrades are trivial to roll back without excessive downtime in the accelerator. The dynamic nature of the plugin architecture also allows plugin developers to test their code using a deployed version of the host application, and include it in a future one. The modular architecture of Geoff also means that plugin developers do not have to use the deployed application at all, and instead e.g.

Given the growing use of generative artificial intelligence as a tool for creating multilingual content and bypassing both machine and traditional translation methods, this study explores the ability of linguistically trained individuals to discern machine-generated output from human-written text (HT). After brief training sessions on the textual anomalies typically found in synthetic text (ST), twenty-three postgraduate translation students analysed excerpts of Italian prose and assigned likelihood scores to indicate whether they believed they were human-written or AI-generated (ChatGPT-4o). The results show that, on average, the students struggled to distinguish between HT and ST, with only two participants achieving notable accuracy. Closer analysis revealed that the students often identified the same textual anomalies in both HT and ST, although features such as low burstiness and self-contradiction were more frequently associated with ST. These findings suggest the need for improvements in the preparatory training. Moreover, the study raises questions about the necessity of editing synthetic text to make it sound more human-like and recommends further research to determine whether AI-generated text is already sufficiently natural-sounding not to require further refinement.

Multilingual wordlists play a crucial role in comparative linguistics. While many studies have been carried out to test the power of computational methods for language subgrouping or divergence time estimation, few studies have put the data upon which these studies are based to a rigorous test. Here, we conduct a first experiment that tests the robustness of concept translation as an integral part of the compilation of multilingual wordlists. Investigating the variation in concept translations in independently compiled wordlists from 10 dataset pairs covering 9 different language families, we find that on average, only 83% of all translations yield the same word form, while identical forms in terms of phonetic transcriptions can only be found in 23% of all cases. Our findings can prove important when trying to assess the uncertainty of phylogenetic studies and the conclusions derived from them.