Even the Empire State Building would eventually crumble. Breakthroughs, discoveries, and DIY tips sent every weekday. New York City is one of the noisiest cities in the world. With a population of eight and a half million people, the city is a nonstop symphony of car honks, yelling, and ambulance sirens. Now, imagine if all that noise and all those people suddenly disappeared overnight. Just how quickly would nature move into abandoned apartments? Well in a new episode of's podcast, we explore just that. So, yes, there's a reason cats love boxes and no, hot workout classes usually aren't better . If you have a question for us, send us a note .

Large Language Models (LLMs) are commonly evaluated for robustness against paraphrased or semantically equivalent jailbreak prompts, yet little attention has been paid to linguistic variation as an attack surface. In this work, we systematically study how linguistic styles such as fear or curiosity can reframe harmful intent and elicit unsafe responses from aligned models. We construct style-augmented jailbreak benchmark by transforming prompts from 3 standard datasets into 11 distinct linguistic styles using handcrafted templates and LLM-based rewrites, while preserving semantic intent. Evaluating 16 open- and close-source instruction-tuned models, we find that stylistic reframing increases jailbreak success rates by up to +57 percentage points. Styles such as fearful, curious and compassionate are most effective and contextualized rewrites outperform templated variants. To mitigate this, we introduce a style neutralization preprocessing step using a secondary LLM to strip manipulative stylistic cues from user inputs, significantly reducing jailbreak success rates. Our findings reveal a systemic and scaling-resistant vulnerability overlooked in current safety pipelines.

Technology Engineering A'post-apocalyptic' shipwreck tower will be Prague's tallest building Top Tower is finally moving forward after years of debate. Breakthroughs, discoveries, and DIY tips sent every weekday. The Czech Republic is moving forward with plans to construct what will become the country's tallest skyscraper . But even at 442 feet tall, Prague's Top Tower won't turn heads for its height alone. Architecture firm Black n' Arch, architect Tomáš Císař, and internationally renowned sculpturist David Černý first announced the surreal project in 2019 .

Breakthroughs, discoveries, and DIY tips sent every weekday. Researchers at Texas A&M University are perfecting a deceptively simple solution to our increasingly overburdened energy grid: ice-cooled buildings. This approach, known as thermal energy storage or sometimes referred to colloquially as "ice batteries," uses energy to freeze liquid overnight, when most people are asleep and electricity demand is lower. That stored ice is then melted to help cool building temperatures during peak hours. If successful, the end result is reduced electricity use for air conditioning during the day, which could decrease overall energy demand and help lower costs.

I read "Middlemarch" for the first time during my sophomore year of college. Why would Dorothea, a young and intelligent woman, marry that annoying old man? How could she be so stupid? No one else in the class seemed to get it, either, and this pushed our professor over the edge. "Of course you don't understand," he roared, swilling a Diet Coke.

This paper introduces ProLab, a novel approach using property-level label space for creating strong interpretable segmentation models. Instead of relying solely on category-specific annotations, ProLab uses descriptive properties grounded in common sense knowledge for supervising segmentation models. It is based on two core designs. First, we employ Large Language Models (LLMs) and carefully crafted prompts to generate descriptions of all involved categories that carry meaningful common sense knowledge and follow a structured format. Second, we introduce a description embedding model preserving semantic correlation across descriptions and then cluster them into a set of descriptive properties (e.g., 256) using K-Means. These properties are based on interpretable common sense knowledge consistent with theories of human recognition. We empirically show that our approach makes segmentation models perform stronger on five classic benchmarks (e.g., ADE20K, COCO-Stuff, Pascal Context, Cityscapes, and BDD). Our method also shows better scalability with extended training steps than category-level supervision. Our interpretable segmentation framework also emerges with the generalization ability to segment out-of-domain or unknown categories using only in-domain descriptive properties. Code is available at https://github.com/lambert-x/ProLab.

Ukraine has warned Vladimir Putin that more drone attacks coming -- just hours after a flying bot smashed into one of Moscow's skyscrapers for the second time in as many days. Although Kyiv refuses to officially take responsibility for such attacks inside Russia, this latest skirmish is considered to be part of a wider offensive aimed at shifting the focus of the conflict to the Kremlin's doorstep. Experts say the way Kyiv is looking to do this is with the help of drones in the air and by sea -- a'cheap', expendable technology which has been revolutionising modern warfare over the past two decades. It is certainly turning attention from the First World War-style trench warfare that has been raging throughout Ukraine since the conflict broke out - and there's a reason the rest of the world is watching. Here, MailOnline looks at how drones are changing the face of future conflict, and why Ukraine is ratcheting up the use of them in an attempt to win the propaganda war and turn the tide of Putin's invasion.

Geographically weighted regression (GWR) is a popular tool for modeling spatial heterogeneity in a regression model. However, the current weighting function used in GWR only considers the geographical distance, while the attribute similarity is totally ignored. In this study, we proposed a covariate weighting function that combines the geographical distance and attribute distance. The covariate-distance weighted regression (CWR) is the extension of GWR including geographical distance and attribute distance. House prices are affected by numerous factors, such as house age, floor area, and land use. Prediction model is used to help understand the characteristics of regional house prices. The CWR was used to understand the relationship between the house price and controlling factors. The CWR can consider the geological and attribute distances, and produce accurate estimates of house price that preserve the weight matrix for geological and attribute distance functions. Results show that the house attributes/conditions and the characteristics of the house, such as floor area and house age, might affect the house price. After factor selection, in which only house age and floor area of a building are considered, the RMSE of the CWR model can be improved by 2.9%-26.3% for skyscrapers when compared to the GWR. CWR can effectively reduce estimation errors from traditional spatial regression models and provide novel and feasible models for spatial estimation.

This week on Dezeen, we compiled an explainer of all the key facts you need to know about the Neom development in Saudi Arabia and its megacity The Line, which is proving to be the most controversial architecture project in recent history. Set to occupy around as much space as the entire country of Albania, Neom will be split into 10 different regions including a floating port, a ski resort in the Sarwat Mountains and a mirrored city for nine million people formed from two linear skyscrapers. Our explainer breaks down everything from how the project is financed to what architecture studios are working on its various different components. Saudi Arabia also revealed another strange-shaped skyscraper this week in the form of a giant cube, which is set to be constructed in the capital of Riyadh. Measuring 400 metres high and 400 metres long on each side, the Mukaab building is set to become the city's tallest building and will house two million square metres of shops alongside cultural and tourist attractions.

Schmidt said there are three significant dangers that could result from generative AI, the first being the creation of killer biological viruses. "Viruses turn out to be relatively simple to construct," he said. "An AI system using generative design techniques, plus a database of how biology actually works, and a machine that makes the viruses, which do exist, can start building terrible viruses." Second, bad actors can use generative AI tools to create and target misinformation, which Schmidt said could lead to violence. Lastly, Schmidt said generative AI can be dangerous when its decision-making is faster than humans, particularly in critical situations.