Is the war entering a new phase? Russian drones and missiles killed four people in Ukraine overnight, while Ukrainian attacks on Russia and Russian-occupied areas of Ukraine killed five. Three people were killed in Russian attacks on Ukraine's central Dnipropetrovsk region overnight, including two at an "industrial enterprise" in the city of Kryvyi Rih, regional officials said on Sunday. Russia has escalated attacks in recent weeks, taking advantage of Ukraine's critical shortage of munitions for its Patriot air defence system, which has rendered it largely unable to intercept ballistic missiles flying at several times the speed of sound. NATO countries pledged at their summit in Ankara last week to provide more Patriot munitions to Ukraine, and President Donald Trump said he was willing to give Kyiv a license to manufacture the US missiles domestically.

Donald Trump's NATO summit remarks in Ankara reveal an emerging grand strategy spanning Iran, Ukraine, China, Greenland and defense spending priorities.

NATO Secretary-General Mark Rutte delivers the keynote speech at the NATO Summit Defense Industry Forum, on the sidelines of the NATO leaders' Summit, in Ankara on Tuesday. NATO allies have agreed to at least $50 billion in defense industry deals, according to an alliance official, to show to U.S. President Donald Trump that Europe is heeding his spending demands. Secretary-General Mark Rutte revealed some of the contracts on Tuesday during a defense industry forum in Ankara, where the military alliance's leaders are meeting for their annual summit this week. Those included $12 billion in deals to buy next-generation drones, surveillance planes and military aircraft. Notably, some of the contracts show Europe moving to locally source some equipment it previously bought from the United States.

Ukraine's president plans to use the Nato meeting in Turkey to urge Kyiv's allies to deliver the air defence systems it urgently needs to protect it from escalating Russian attacks. Volodymyr Zelensky's call for help rings with extra intensity after Russian missiles rained down on the Ukrainian capital twice in less than a week, crashing into blocks of flats and killing more than 50 civilians. The summit in Ankara will also be a chance for Zelensky to hold a crucial meeting with Donald Trump and press home his case that Russia's brutal attacks are a show of weakness, not strength, and that Vladimir Putin should be pressured into talks towards a dignified peace. The latest strikes on Ukraine come as it has been stepping up its own long-range drone attacks against Russia, hitting oil refineries and military targets there and causing significant fuel shortages and power cuts. To play this video you need to enable JavaScript in your browser. Russian social media accounts are full of videos of people queuing for hours to buy petrol and fighting over what little they're allowed.

Missouri State University trained over 1,500 Chinese executives tied to China's military-industrial complex through an MBA program, a new watchdog report claims.

Large language models (LLMs) are increasingly used in sensitive domains, where their ability to infer personal data from seemingly benign text introduces emerging privacy risks. While recent LLM-based anonymization methods help mitigate such risks, they often rely on proprietary models (e.g., GPT-4), raising concerns about cost and the potential exposure of sensitive data to untrusted external systems. To address this, we introduce SElf-refining Anonymization with Language model (SEAL), a novel distillation framework for training small language models (SLMs) to perform effective anonymization without relying on external models at inference time. SEAL leverages adversarial interactions between an LLM anonymizer and an inference model to collect trajectories of anonymized texts and inferred attributes, which are then used to distill anonymization and critique capabilities into SLMs through supervised fine-tuning and preference learning. The resulting models learn both to anonymize text and to evaluate their outputs, enabling iterative improvement of anonymization quality via self-refinement. Experiments on SynthPAI, a dataset of synthetic personal profiles and text comments, demonstrate that SLMs trained with SEAL achieve substantial improvements in anonymization capabilities. Notably, 8B models attain a privacy-utility trade-off comparable to that of the GPT-4 anonymizer and, with self-refinement, even surpass it in terms of privacy protection.

When you purchase through links in our articles, we may earn a small commission. I can't stop using this website that lets me drive through cities around the world Drive and Listen combines street-level video with live local radio for a surprisingly immersive experience--even if it's only from your desktop. Drive and Listen might not sound like it, but it's strangely relaxing once you try it. The site provides exactly the experience the name suggests: Pick a city anywhere in the world, press play, and sit back as you ride along through the streets listening to local radio stations. The site was created during the pandemic by a student in Turkey who missed traveling and wanted a way to reconnect with places beyond his own neighborhood.

The backpropagation algorithm has experienced remarkable success in training large-scale artificial neural networks; however, its biological plausibility has been strongly criticized, and it remains an open question whether the brain employs supervised learning mechanisms akin to it. Here, we propose correlative information maximization between layer activations as an alternative normative approach to describe the signal propagation in biological neural networks in both forward and backward directions. This new framework addresses many concerns about the biological-plausibility of conventional artificial neural networks and the backpropagation algorithm. The coordinate descent-based optimization of the corresponding objective, combined with the mean square error loss function for fitting labeled supervision data, gives rise to a neural network structure that emulates a more biologically realistic network of multi-compartment pyramidal neurons with dendritic processing and lateral inhibitory neurons. Furthermore, our approach provides a natural resolution to the weight symmetry problem between forward and backward signal propagation paths, a significant critique against the plausibility of the conventional backpropagation algorithm. This is achieved by leveraging two alternative, yet equivalent forms of the correlative mutual information objective. These alternatives intrinsically lead to forward and backward prediction networks without weight symmetry issues, providing a compelling solution to this long-standing challenge.

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From specialized motors to the use of machine-learning algorithms, Turkey's billion-dollar hair-transplant industry is the result of a constant process of innovation. The astounding growth of the hair-transplant industry in Turkey is not just a medical tourism success story; it's also a tale of "hacked" medical equipment and algorithmic craftsmanship. From a biological and evolutionary perspective, human hair is often viewed as an unremarkable mass of keratin that still plays some important functions--protecting our scalps from the sun's harmful ultraviolet rays and regulating our body temperatures--but, for the most part, is no longer essential to our survival. Yet, since ancient times, our subconscious perceptions of whether another person is healthy, young, or fertile have been based on visual cues such as skin radiance, the integrity of teeth, and hair density. Deep within our perceptions, hair has become one of the most powerful representations of our identity and self-confidence. Today, the global hair-transplant and restoration industry, which has evolved around this deep psychological and evolutionary need, has grown into a massive, multibillion-dollar industry. Various research firms have estimated the total size of the global hair-transplant market as sitting somewhere between $7.33 billion and $11.61 billion in 2024. And those figures don't include the underground economy.