Major cities across Sudan, including the capital, Khartoum, and coastal city Port Sudan, have been plunged into darkness after drone strikes hit a key power plant in the country's east. Flames and smoke rose from the facility in Atbara, River Nile state on Thursday, which is controlled by the government-aligned Sudanese Armed Forces (SAF) and under attack by the paramilitary Rapid Support Forces (RSF) in the ongoing civil war that has ripped the nation apart. Sudan's RSF trying to hide atrocities: Report Two civil defence members were killed, power plant officials said, while trying to extinguish the fire that erupted after the first strike, adding that rescue workers were injured when a second drone hit as they battled the flames. Al Jazeera correspondent Mohamed Vall in Port Sudan reported that residents initially thought a routine power cut had occurred, only to learn it was linked to incidents in Atbara, roughly 320km (about 230 miles) north of Khartoum. He added that such strikes have become a frequent occurrence in Sudan's war.

Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narratives. How to effectively revise and improve long narrative scripts like scriptwriters remains a significant challenge, as it demands a comprehensive understanding of the entire context to identify global structural issues and local detailed flaws, as well as coordinating revisions at multiple granularities and locations. Direct modifications by LLMs typically introduce inconsistencies between local edits and the overall narrative requirements. To address these issues, we propose Dramaturge, a task and feature oriented divide-and-conquer approach powered by hierarchical multiple LLM agents. It consists of a Global Review stage to grasp the overall storyline and structural issues, a Scene-level Review stage to pinpoint detailed scene and sentence flaws, and a Hierarchical Coordinated Revision stage that coordinates and integrates structural and detailed improvements throughout the script. The top-down task flow ensures that high-level strategies guide local modifications, maintaining contextual consistency. The review and revision workflow follows a coarse-to-fine iterative process, continuing through multiple rounds until no further substantive improvements can be made. Comprehensive experiments show that Dra-maturge significantly outperforms all baselines in terms of script-level overall quality and scene-level details. Our approach is plug-and-play and can be easily integrated into existing methods to improve the generated scripts.

Contrary to popular belief, most property crimes--including burglaries and package theft--happen during the day, not under cover of darkness. But night still brings unique challenges: fewer people around, limited visibility, and more opportunity for intruders to move unseen. If your security camera can't see clearly after dark, you're missing protection when you might need it most. Night vision lets security cameras capture what the human eye can't see in the dark. Some cameras shine invisible infrared light to illuminate a scene, while others rely on light-sensitive sensors to amplify what little light is already there.

Adam Roberts' Lake of Darkness opens as two space ships investigate a black hole The starting point for this novel was that I wanted to write utopian fiction. I hadn't done this before: all my previous novels have been straight science fiction. But utopia, the genre that imagines a better, or a perfect, world, is older than science fiction: the first utopian novel, the work that coined the term, was written by Thomas More all the way back in 1516. I was interested in what happened to the mode: More's Utopia generated lots of imitators. Through the 17th and 18th centuries, a great many utopian books, novels, tracts and treatises were written.

Volumetric rendering-based methods, like NeRF, excel in HDR view synthesis from RAW images, especially for nighttime scenes. They suffer from long training times and cannot perform real-time rendering due to dense sampling requirements. The advent of 3D Gaussian Splatting (3DGS) enables real-time rendering and faster training. However, implementing RAW image-based view synthesis directly using 3DGS is challenging due to its inherent drawbacks: 1) in nighttime scenes, extremely low SNR leads to poor structure-from-motion (SfM) estimation in dis- tant views; 2) the limited representation capacity of the spherical harmonics (SH) function is unsuitable for RAW linear color space; and 3) inaccurate scene structure hampers downstream tasks such as refocusing. To address these issues, we propose LE3D (Lighting Every darkness with 3DGS).

Digging up treasures from the past is an exciting business. So exciting, in fact, it's kept players coming back to the Tomb Raider series for nearly three decades. The original trilogy was successfully remastered and rereleased last year. Now a new collection has been recovered from the attic and put on show, like a family heirloom on the Antiques Roadshow. But will this turn out to be the gaming equivalent of a priceless Ming vase?

A painting is more than just a picture on a wall; a painting is a process comprised of many intentional brush strokes, the shapes of which are an important component of a painting's overall style and message. Prior work in modeling brush stroke trajectories either does not work with real-world robotics or is not flexible enough to capture the complexity of human-made brush strokes. In this work, we introduce Spline-FRIDA which can model complex human brush stroke trajectories. This is achieved by recording artists drawing using motion capture, modeling the extracted trajectories with an autoencoder, and introducing a novel brush stroke dynamics model to the existing robotic painting platform FRIDA. We conducted a survey and found that our open-source Spline-FRIDA approach successfully captures the stroke styles in human drawings and that Spline-FRIDA's brush strokes are more human-like, improve semantic planning, and are more artistic compared to existing robot painting systems with restrictive B\'ezier curve strokes.

Large language models (LLMs) have demonstrated remarkable performance, particularly in multilingual contexts. While recent studies suggest that LLMs can transfer skills learned in one language to others, the internal mechanisms behind this ability remain unclear. We observed that the neuron activation patterns of LLMs exhibit similarities when processing the same language, revealing the existence and location of key linguistic regions. Additionally, we found that neuron activation patterns are similar when processing sentences with the same semantic meaning in different languages. This indicates that LLMs map semantically identical inputs from different languages into a "Lingua Franca", a common semantic latent space that allows for consistent processing across languages. This semantic alignment becomes more pronounced with training and increased model size, resulting in a more language-agnostic activation pattern. Moreover, we found that key linguistic neurons are concentrated in the first and last layers of LLMs, becoming denser in the first layers as training progresses. Experiments on BLOOM and LLaMA2 support these findings, highlighting the structural evolution of multilingual LLMs during training and scaling up. This paper provides insights into the internal workings of LLMs, offering a foundation for future improvements in their cross-lingual capabilities.

Three robots are growing vegetables on the roof of the University of Melbourne's student pavilion. As I watch, a mechanical arm, hovering above the crop like a fairground claw machine, sprays a carefully measured dose of water over the plants. The greens themselves look fairly terrestrial – cos lettuce, basil, coriander and moth-eaten kale – but they are actually prototypes for a groundbreaking research mission to grow fresh food in outer space. The project leader, Prof Sigfredo Fuentes, leans over and picks a tiny caterpillar from a kale leaf. "We had a real plague of cabbage moths last week, but it's OK; the kale's just here to distract them from the other vegetables." Prof Fuentes is part of the wonderfully named Australian Research Council Centre of Excellence in Plants for Space – a seven-year collaboration between five Australian universities – which has partnered with 38 organisations, including Nasa, to crack the code of fresh, nutritious "space food".

In hindsight, ChatGPT may come to be seen as the greatest publicity stunt in AI history, an intoxicating glimpse at a future that may actually take years to realize--kind of like a 2012-vintage driverless car demo, but this time with a foretaste of an ethical guardrail that will take years to perfect. What ChatGPT delivered, in spades, that its predecessors like Microsoft Tay (released March 23, 2016, withdrawn March 24 for toxic behavior) and Meta's Galactica (released November 16, 2022, withdrawn November 18) could not, was an illusion--a sense that the problem of toxic spew was finally coming under control. ChatGPT rarely says anything overtly racist. Simple requests for anti-semitism and outright lies are often rebuffed. Indeed, at times it can seem so politically correct that the right wing has become enraged.