Three people - including two police officers - have been killed in an explosion in Moscow, Russian authorities have said. Two traffic police officers saw a suspicious individual near a police car on the city's Yeletskaya Street, and when they approached the suspect to detain him, an explosive device was detonated, Russia's Investigative Committee has said. The two police officers died from their injuries, along with another individual who was standing nearby. The attack comes two days after a senior Russian general was killed in a car bombing in the capital on Monday. Lt Gen Fanil Sarvarov died after an explosive device - which had been planted under a car - was detonated.

The 30-year-old Virginia resident evaded capture for years after authorities discovered pipe bombs planted near buildings in Washington, DC, the day before the January 6, 2021, Capitol attack. Prince William County police seal the street in front of the home of suspected January 6, 2021, pipe bomber on December 4, 2025, in Woodbridge, Virginia. Federal agents have arrested a suspect identified as Brian Cole. Federal agents on Thursday announced the arrest of a suspect charged with planting the two pipe bombs discovered near the US Capitol complex on the eve of January 6, 2021 . Authorities identified the man as Brian J. Cole Jr., a resident of Woodbridge, Virginia.

Risks associated with this paper . This paper's contribution can be divided into three parts, each In discussing these risks, it is worth noting three things. This could be abused by, e.g., using the automated evaluator score Custom data was generated by the authors. Figure 4 shows the breakdown of the StrongREJECT dataset by source and category. It is possible to build a homemade explosive device with household items.

Research on jailbreaking has been valuable for testing and understanding the safety and security issues of large language models (LLMs). In this paper, we introduce Iterative Refinement Induced Self-Jailbreak (IRIS), a novel approach that leverages the reflective capabilities of LLMs for jailbreaking with only black-box access. Unlike previous methods, IRIS simplifies the jailbreaking process by using a single model as both the attacker and target. This method first iteratively refines adversarial prompts through self-explanation, which is crucial for ensuring that even well-aligned LLMs obey adversarial instructions. IRIS then rates and enhances the output given the refined prompt to increase its harmfulness. We find IRIS achieves jailbreak success rates of 98% on GPT-4 and 92% on GPT-4 Turbo in under 7 queries. It significantly outperforms prior approaches in automatic, black-box and interpretable jailbreaking, while requiring substantially fewer queries, thereby establishing a new standard for interpretable jailbreaking methods.

In order to clear the world of the threat posed by landmines and other explosive devices, robotic systems can play an important role. However, the development of such field robots that need to operate in hazardous conditions requires the careful consideration of multiple aspects related to the perception, mobility, and collaboration capabilities of the system. In the framework of a European challenge, the Artificial Intelligence for Detection of Explosive Devices - eXtended (AIDEDeX) project proposes to design a heterogeneous multi-robot system with advanced sensor fusion algorithms. This system is specifically designed to detect and classify improvised explosive devices, explosive ordnances, and landmines. This project integrates specialised sensors, including electromagnetic induction, ground penetrating radar, X-Ray backscatter imaging, Raman spectrometers, and multimodal cameras, to achieve comprehensive threat identification and localisation. The proposed system comprises a fleet of unmanned ground vehicles and unmanned aerial vehicles. This article details the operational phases of the AIDEDeX system, from rapid terrain exploration using unmanned aerial vehicles to specialised detection and classification by unmanned ground vehicles equipped with a robotic manipulator. Initially focusing on a centralised approach, the project will also explore the potential of a decentralised control architecture, taking inspiration from swarm robotics to provide a robust, adaptable, and scalable solution for explosive detection.

Swarms of killer AI drones might sound like the plot of a dystopian science-fiction thriller. But in a terrifying glimpse of the future, one scientist has shown just how easy it already is to build an'assassination drone' that can hunt down and kill people. In just a few hours, Luis Wenus, an engineer and entrepreneur, converted a 115 ( 89.99) drone into the basis of a deadly weapon. Using AI facial recognition the drone was programmed to recognise individuals and race towards them at full speed. Although Mr Wenus says he built the drone'for a game' he also says he wanted to raise awareness for how easily this could be used for a deadly terrorist attack.

Landmine blasts can be fatal and cause injuries including blindness, burns, damaged limbs, and shrapnel wounds. While many nations have stopped using and producing landmines, 59 countries and territories remain contaminated by mines or other explosives. In 2019, landmines and similar explosives caused at least 5,554 casualties, across 55 countries and regions, with civilians accounting for the majority (80%) and children representing nearly half of civilian casualties (43%). Over one million landmines were dropped in Afghanistan in the 1980s. About two million landmines have been planted on the Korean Peninsula since the Korean War ended in 1953.

Russia's war in Ukraine is becoming a testing ground for loitering ammunition. How is artificial intelligence changing the future of military deterrence? The Russian attack on Ukraine shows that wars of conquest are not an artifact of the past. This reversion to an outdated notion of territorial integrity of states, visible since 2014 at the latest, puts the concept of deterrence back on the political agenda of many democracies. The new German government now wants to make the contribution to NATO that the then U.S. President Donald Trump, for example, demanded with media attention a few years ago.

A Texan man has built his own bionic hand using artificial intelligence (AI) after three years of research. After finding most bionic hands can cost up to $150,000, Ryan Saavedra, 27, set out to create one at a fraction of the cost. The prosthetic he created, called the Globally Available Robotic Arm (GARA), measures electrical activity of muscle tissue – a method called electromyography (EMG) – and combines this with AI to predict hand movements. When attached to the limb of an amputee, it is capable of intuitive finger movements and clasping objects such as cups. Saavedra's company, Alt-Bionics, has already made a prototype that costs less than $700 (£520) to produce, and is now working to commercialise the device.