Time flows ever onwards with reassuring uniformity - at least, that's how it feels to mere mortals unplugged from the weirder parts of physics. But everyone knows that the exception to this rule is the period between Christmas and New Year, in which time behaves strangely, moving like molasses until it lurches forwards as you near your return to work. If you usually misspend the twilight days of the year sitting idly in a fog of libations, you might be wondering how to occupy yourself. Fear not: staff and contributors have crafted a bucket list of all-time cultural greats to fill the long hours of the holiday season. It is an eclectic mix of books, films, television, music, video games, board games and more, designed to highlight some overlooked classics that you simply must try. The only thing they all have in common is their celebration of science, technology, the environment or any other topic you might find in . We hope you enjoy our favourites - if you choose to give one a go, your time will pass in the blink of an eye. Released in 2019, it broke from a stale formula of largely linear plotlines and choreographed cutscenes in the middle of gameplay, instead opting for narrative experimentation. You begin as a spacefaring alien in a solar system moments from destruction, stuck in a 22-minute time loop that ends with a supernova. It is also a physics lover's paradise: the game wrestles with quantum entanglement, entropy and non-Euclidean spaces. Its simulation of light bending around black holes is among the most accurate ever rendered in media.

The Morning After: Flying Antigravity's A1 drone is unlike anything else Spinning off from the action-camera company Insta360, Antigravity now has its debut drone on sale. With 360-degree cameras that capture 8K and offer you a truly unconstrained view of the skies, the A1 is a different drone from everything else out there. Instead of typical drone joysticks, you get a motion controller that lets you point and shoot like video game gesture controls, while crisp FPV goggles put you right inside the cockpit. It's easy to fly after takeoff, but the A1's myriad parts are often tricky to sync together -- and pulling video down to the companion app is even trickier. Still, it's not meant to be a cinematic drone.

Reddit is considered one of the most human spaces left on the internet, but mods and users are overwhelmed with slop posts in the most popular subreddits. A Reddit post about a bride who demands a wedding guest wear a specific, unflattering shade is sure to provoke rage, let alone one about a bridesmaid or mother of the groom who wants to wear white. A scenario where a parent asks someone on an airplane to switch seats so they can sit next to their young child is likely to invoke the same rush of anger. But those posts may trigger a Reddit moderator's annoyance for a different reason--they are common themes within a growing genre of AI -generated, fake posts. These are examples that spring to mind for Cassie, one of dozens of moderators for r/AmItheAsshole .

What are freeze-dried sweets and why are they popular? When Savannah Louise West first tasted freeze-dried gummies, she was intrigued. I think the crunch is so satisfying, and I find it interesting to experience a candy I'm familiar with that has an entirely new texture, says the Toronto resident. Ms West is describing one of the main features of this spin-off candy that independent and major confectionary manufacturers have been releasing onto shelves, both online and offline, for the past three years. It's been largely a US phenomena, hence we'll use the US term candy, but for our UK readers, we're talking about sweets here.

Meta is shifting some of its investments in the metaverse to AI glasses and wearables, hoping to capitalise on the momentum in that segment, a company spokesperson has said. Over the last decade, Meta has poured billions of dollars to build the metaverse, which lets people to interact in a virtual reality. However, the tech giant has struggled to convince investors of the viability of the nascent technology. Bloomberg first reported on Thursday that Meta would cut its metaverse investment by as much as 30%. Its shares climbed more than 3.4% following the news.

'It was about degrading someone completely': the story of Mr DeepFakes - the world's most notorious AI porn site The hobbyists who helped build this site created technology that has been used to humiliate countless women. Why didn't governments step in and stop them? For Patrizia Schlosser, it started with an apologetic call from a colleague. "I'm sorry but I found this. Are you aware of it?"

Waterstones would stock books created using artificial intelligence, the company's boss has said, as long as they were clearly labelled, and if customers wanted them. However, James Daunt, a veteran of the bookselling industry, said he personally did not expect that to happen. There's a huge proliferation of AI generated content and most of it are not books that we should be selling, he said. But it would be up to the reader. An explosion in the use of artificial intelligence, or AI, has prompted heated debate in the publishing industry, with writers concerned about the impact on their livelihoods.

We introduce a diffusion-transformer (DiT) framework for single-image reflection removal that leverages the generalization strengths of foundation diffusion models in the restoration setting. Rather than relying on task-specific architectures, we repurpose a pre-trained DiT-based foundation model by conditioning it on reflection-contaminated inputs and guiding it toward clean transmission layers. We systematically analyze existing reflection removal data sources for diversity, scalability, and photorealism. To address the shortage of suitable data, we construct a physically based rendering (PBR) pipeline in Blender, built around the Principled BSDF, to synthesize realistic glass materials and reflection effects. Efficient LoRA-based adaptation of the foundation model, combined with the proposed synthetic data, achieves state-of-the-art performance on in-domain and zero-shot benchmarks. These results demonstrate that pretrained diffusion transformers, when paired with physically grounded data synthesis and efficient adaptation, offer a scalable and high-fidelity solution for reflection removal. Project page: https://hf.co/spaces/huawei-bayerlab/windowseat-reflection-removal-web

Singing Voice Synthesis (SVS) remains constrained in practical deployment due to its strong dependence on accurate phoneme-level alignment and manually annotated melody contours, requirements that are resource-intensive and hinder scalability. To overcome these limitations, we propose a melody-driven SVS framework capable of synthesizing arbitrary lyrics following any reference melody, without relying on phoneme-level alignment. Our method builds on a Diffusion Transformer (DiT) architecture, enhanced with a dedicated melody extraction module that derives melody representations directly from reference audio. To ensure robust melody encoding, we employ a teacher model to guide the optimization of the melody extractor, alongside an implicit alignment mechanism that enforces similarity distribution constraints for improved melodic stability and coherence. Additionally, we refine duration modeling using weakly annotated song data and introduce a Flow-GRPO reinforcement learning strategy with a multi-objective reward function to jointly enhance pronunciation clarity and melodic fidelity. Experiments show that our model achieves superior performance over existing approaches in both objective measures and subjective listening tests, especially in zero-shot and lyric adaptation settings, while maintaining high audio quality without manual annotation. This work offers a practical and scalable solution for advancing data-efficient singing voice synthesis. To support reproducibility, we release our inference code and model checkpoints.

The rapid progress of Large Language Models (LLMs) has transformed natural language processing and broadened its impact across research and society. Yet, systematic evaluation of these models, especially for languages beyond English, remains limited. "Challenging the Abilities of LAnguage Models in ITAlian" (CALAMITA) is a large-scale collaborative benchmarking initiative for Italian, coordinated under the Italian Association for Computational Linguistics. Unlike existing efforts that focus on leaderboards, CALAMITA foregrounds methodology: it federates more than 80 contributors from academia, industry, and the public sector to design, document, and evaluate a diverse collection of tasks, covering linguistic competence, commonsense reasoning, factual consistency, fairness, summarization, translation, and code generation. Through this process, we not only assembled a benchmark of over 20 tasks and almost 100 subtasks, but also established a centralized evaluation pipeline that supports heterogeneous datasets and metrics. We report results for four open-weight LLMs, highlighting systematic strengths and weaknesses across abilities, as well as challenges in task-specific evaluation. Beyond quantitative results, CALAMITA exposes methodological lessons: the necessity of fine-grained, task-representative metrics, the importance of harmonized pipelines, and the benefits and limitations of broad community engagement. CALAMITA is conceived as a rolling benchmark, enabling continuous integration of new tasks and models. This makes it both a resource -- the most comprehensive and diverse benchmark for Italian to date -- and a framework for sustainable, community-driven evaluation. We argue that this combination offers a blueprint for other languages and communities seeking inclusive and rigorous LLM evaluation practices.