The Ring star Daveigh Chase's autopsy reveals actress died from AIDS after painful health battle Clint Eastwood's son reveals shocking on-set spat with entitled Hollywood star: 'They think the world owes them' I thought my drinking was harmless until I realized I couldn't go a day without it. Then I discovered a $3 miracle pill that killed all my alcohol cravings... I'm completely cured I thought I knew the secret to great sex... then one man proved me so wrong: JANA HOCKING is mind-blown by trick that women over 40 are loving Hollywood nepo baby, 17, shows she has her father's unique style with edgy turn on red carpet... who is she? How well do you REALLY know America? Take our ultimate history quiz to find out... Stay-alert warnings issued as sharks return to one of America's busiest beaches Harry DOES want to bring Archie and Lili to the UK - but not without'proportionate protective security', team Sussex say: Duke and Duchess lay out demands after'state-funded guards turned down at 11th hour' Boy, 12, reveals how brother's quick thinking saved him from shark bite while on gorgeous Bahamas vacation Former FBI agent believes there's sinister motive behind new Nancy Guthrie ransom note... as desperation seeps in At 45 I was plagued by muscle pain, brain fog and memory loss... but it wasn't the menopause. I caught a disease while sitting on my sofa.

For 40 years, we thought Earth was home to six million insect species. Turns out, it could be three times that. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Insect species make up the largest percentage of Earth's known species. Breakthroughs, discoveries, and DIY tips sent six days a week.

AI agents are not your "coworkers" Marketing AI agents as digital employees may make human workers worse at spotting errors and more likely to offload accountability. Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool--one that your company nonetheless calls Alex, an "employee" with a title and defined responsibilities. How well do you think you would work with Alex? If you're anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a "coworker" and not a software tool would lead you to do a worse job. Wiles found that people caught 18% fewer errors when the work was said to have come from an agentic "AI employee" rather than a chatbot. It turns out that what's in a name matters.

More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy . The nankeen kestrel () pulls off aerial maneuvers that put many advanced aircraft to shame. These diminutive falcons rank as some of the most stable fliers in the world, and are evolved to handle Australia's extremely gusty, often violent winds.

Recent advances in multimodal models have raised questions about whether vision-and-language models (VLMs) integrate cross-modal information in ways that reflect human cognition. One well-studied test case in this domain is the bouba-kiki effect, where humans reliably associate pseudowords like'bouba' with round shapes and'kiki' with jagged ones. Given the mixed evidence found in prior studies for this effect in VLMs, we present a comprehensive re-evaluation focused on two variants of CLIP, ResNet and Vision Transformer (ViT), given their centrality in many state-of-the-art VLMs. We apply two complementary methods closely modelled after human experiments: a prompt-based evaluation that uses probabilities as a measure of model preference, and we use Grad-CAM as a novel approach to interpret visual attention in shape-word matching tasks. Our findings show that these model variants do not consistently exhibit the bouba-kiki effect. While ResNet shows a preference for round shapes, overall performance across both model variants lacks the expected associations. Moreover, direct comparison with prior human data on the same task shows that the models' responses fall markedly short of the robust, modality-integrated behaviour characteristic of human cognition. These results contribute to the ongoing debate about the extent to which VLMs truly understand cross-modal concepts, highlighting limitations in their internal representations and alignment with human intuitions.

More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Discovered in 2013, the Pink Planet orbits a sun-like star located 57 light-years from Earth. At roughly 25 times the mass of Jupiter, it sits near the fuzzy boundary between giant planets and brown dwarfs. So, astronomers refer to it as a "planetary-mass companion," meaning that it's a planet-sized object orbiting a star. Breakthroughs, discoveries, and DIY tips sent six days a week.

What Happened to Your Face? How the human countenance became something to study, edit, optimize, and scan. The physiognomists promised that your character could be read from your features. Certain forms of facial-recognition technology have revived that old fantasy in digital form. Several months ago, my partner and I bought an apartment in South London. Our previous home was a rental in which, for reasons best known to the landlord, there were mirrors everywhere. The bathroom had two; there was one outside on the terrace; in the bedroom, mirrored panels stretched across a twenty-foot-long wall. On moving day, we realized that we had a problem: the new apartment was mirror-free, and because we'd been so spoiled we weren't bringing one of our own. We spent a few days filling our drafty rooms, decanting books, building furniture, and dressing every morning without seeing ourselves in profile. It was a couple of weeks before we bought a simple mirror, wooden and round, to hang above the bathroom sink. By then, I joked, we didn't recognize ourselves.

California couple's desperate bid to save man, 28, from crocodile attack ends in tragedy after they heard screams coming from beach while on vacation in Mexico'Most beautiful girl in the world' Thylane Blondeau is married: Model stuns as she ties the knot with French DJ Ben Attal in Paris three months after getting engaged Sordid marriage secrets of country star Sam Hunt: Insiders reveal wife's brutal ultimatum... as singer's strange disappearance fuels Nashville whispers The signs I missed that I was sleeping next to a killer: My husband dismembered his secret girlfriend with a machete. Blue collar Democrat's VERY kinky history is exposed as she desperately grasps on to rural Washington seat World's first'pregnant man' Thomas Beatie reveals astonishing full story for the first time as his daughter turns 18... and confronts a hard truth about trans teens'Super, well done you!' Moment Kate stops to chat to 11-year-old boy in wheelchair during her Three Peaks Challenge as he's ...

Flexion Robotics, a startup founded by ex-Nvidia engineers, has a clever way of training robots to do useful work. Humanoid robots might be able to run, dance, and occasionally kick people, but to become human, they're going to need to learn how to do all sorts of menial chores at work. Flexion Robotics, a Swiss startup founded by ex-Nvidia robotics researchers, thinks it has the solution. The company has developed a way to train robots to perform complex tasks that involve simple skills like opening doors, climbing stairs, and carrying boxes. The key is to teach the robots individual skills in simulation, then have a master AI algorithm determine how to use them.

In recent years, fueled by the rapid advancement of diffusion models, text-to-video (T2V) generation models have achieved remarkable progress, with notable examples including Pika, Luma, Kling, and Open-Sora. Although these models exhibit impressive generative capabilities, they also expose significant security risks due to their vulnerability to jailbreak attacks, where the models are manipulated to produce unsafe content such as pornography, violence, or discrimination. Existing works such as T2VSafetyBench provide preliminary benchmarks for safety evaluation, but lack systematic methods for thoroughly exploring model vulnerabilities. To address this gap, we are the first to formalize the T2V jailbreak attack as a discrete optimization problem and propose a joint objective-based optimization framework, called \emph{T2V-OptJail}. This framework consists of two key optimization goals: bypassing the built-in safety filtering mechanisms to increase the attack success rate, preserving semantic consistency between the adversarial prompt and the unsafe input prompt, as well as between the generated video and the unsafe input prompt, to enhance content controllability. In addition, we introduce an iterative optimization strategy guided by prompt variants, where multiple semantically equivalent candidates are generated in each round, and their scores are aggregated to robustly guide the search toward optimal adversarial prompts. We conduct large-scale experiments on several T2V models, covering both open-source models (\textit{e.g.}, Open-Sora) and real commercial closed-source models (\textit{e.g.}, Pika, Luma, Kling). The experimental results show that the proposed method improves 11.4\% and 10.0\% over the existing state-of-the-art method (SoTA) in terms of attack success rate assessed by GPT-4, attack success rate assessed by human accessors, respectively, verifying the significant advantages of the method in terms of attack effectiveness and content control. This study reveals the potential abuse risk of the semantic alignment mechanism in the current T2V model and provides a basis for the design of subsequent jailbreak defense methods.