It was only by chance that Tom Ronketty said he discovered that his wife’s family members have claimed for generations that they are connected to the infamous outlaw, Billy the Kid. They even have family album that contains a couple of photos of a young man not yet known as Billy the Kid, the family told him. That would be a truly historic discovery, as to date there has only been one verified image of Billy the Kid, a damaged tintype that sold at auction for $2.3 million. The emergence of genuine photo — let alone two — would be huge. If either or both of the photos could be verified. So far, despite a decade of having the images studied and scientifically examined, experts haven’t been able to do that. They also haven’t debunked them, either, the Ronkettys say. ‘Jeopardy!’ Moment Tom Ronketty told Cowboy State Daily that he and his wife, Beth, were watching an episode of “Jeopardy!" when Beth shouted out the answer to an obscure question about the infamous outlaw. “I asked her why in the world would you know about Billy the Kid?” Ronketty said. “Beth told me that when she was a kid, her dad always said that they were related to him, but his family wasn’t proud of the relationship.” Ronketty thought she was pranking him, but Beth persisted and even claimed that they had an old photo album with two pictures of Billy that would prove what she was saying. It took a couple of hours of searching through her father’s things to find the old, red-leather album Beth presented to her doubting husband. “I'm like, ‘Get out of here,'” Ronketty said. “This is bizarre.” Ronketty was expecting to see guns, horses and cowboy hats. Instead, Beth picked out two photos from
Apr 18, 2026 · via cowboystatedaily.com
Live facial recognition vans are set to return to Slough High Street next week. On Tuesday, April 21, police will attempt to "identify known suspects" and "deter crime" using CCTV vans with algorithms built to spot people on a "watchlist". The force stated: "Our Live Facial Recognition (LFR) vans will be coming to Slough High Street on Tues (21/4). "We will be working to identify known suspects, deter crime & help keep our communities safer. "Any questions? "Want to see how the technology works? "Come over & chat with our team." This will not be the first time that the cameras have been used in town. In February, Thames Valley Police (TVP) said it had launched Operation Catalyst in a bid to reduce the interrelated issues of anti-social behaviour and violent crime. The force worked with the Safer Towns Team to deploy LFR vans on the High Street and said that this resulted in the arrest of three wanted individuals while providing a 'visible deterrent'. Previously, a TVP spokesperson stated: "We always ensure the public is informed when LFR is in use through signage and social media updates and welcome questions throughout the deployments. "Once again a big thank you to everyone who stopped to speak with us this week - we're here to serve and protect our community."
Apr 18, 2026 · via sloughobserver.co.uk
Explore the things
you love
.
Log into Facebook
Email or mobile number
Password
Log in
Forgot password?
Create new account
English (US)
Español
Français (France)
中文(简体)
العربية
Português (Brasil)
Italiano
More languages…
Sign Up
Log In
Messenger
Facebook Lite
Video
Meta Pay
Meta Store
Meta Quest
Ray-Ban Meta
Meta AI
Instagram
Threads
Privacy Policy
Consumer Health Privacy
Privacy Center
About
Create ad
Create Page
Developers
Careers
Cookies
Ad choices
Terms
Help
Contact Uploading & Non-Users
Meta © 2026
Apr 18, 2026 · via facebook.com
Abstract Conventional models encounter challenges in detecting vehicle appearance components in intricate settings because of their limited small-target recognition capability and suboptimal fusion of multi-scale features. To address these issues, we propose an enhanced vehicle appearance segmentation model based on the YOLOv11-seg framework. Central to our approach is the MCALayerPlus module, designed to concurrently process targets across a wide range of scales. By executing multi-scale feature extraction, the model effectively suppresses false detections arising from cluttered backgrounds. Furthermore, we incorporate an improved ShapeIoU loss function, which integrates a size-sensitivity factor and a category-aware shape penalty term. This integration sharpens shape-matching precision, captures nuanced feature representations, and accelerates model convergence. Experimental results on a specialized automotive dataset demonstrate state-of-the-art performance, achieving a mean Average Precision (mAP@0.5) of 94.09%, an mAP@0.5:0.95 of 77.12%, precision of 91.31%, and recall of 90.75%. Notably, the model maintains a lightweight profile (5.75 MB), ensuring high-speed inference (45.3 FPS) suitable for real-time deployment in intelligent transportation systems. Similar content being viewed by others Data availability The datasets used and/or analyzed during the current study are available from the corresponding author. References Jocher, G., Chaurasia, A. & Qiu, J. Ultralytics YOLO [Computer software]. (2023). https://github.com/ultralytics/ultralytics Wang, C.-Y., Yeh, I.-H. & Liao, H.-Y. YOLOv9: Learning what you want to learn using programmable gradient information. arXiv https://doi.org/10.48550/arXiv.2402.13616 (2024). Wang, A. et al. YOLOv10: Real-Time End-to-End Object Detection. ArXiv, abs/2405.14458. (2024). Liu, Z. et al. Swin Transformer: Hierarchical Vision Transformer using Shifted Windows [C]// Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). : 10012–10022. (2021). Lv, W. et al. DETRs Beat YOLOs on Real-time Object Detection [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). : 16965–16974. (2024). Raj, V. et al. Smart traffic control for emergency vehicles prioritization using video and audio processing [C]//
Apr 18, 2026 · via nature.com
DES MOINES – A plea deal has been reached in the murder trial of a woman accused of killing her stepfather. After being charged with Murder in the Second Degree in the shooting death of stepfather Anthony Hartmann, 29-year-old Sera Alexander entered a guilty plea to two amended charges—Involuntary Manslaughter (Class D Felony) and Reckless Use of a Firearm Causing Serious Injury (Class C Felony). Alexander’s trial began Monday at the Drake Legal Clinic in Des Moines, with first responders, as well as Alexander’s brother and mother, testifying. The prosecution argued that Alexander was driven by anger and hatred, not fear, in shooting Hartmann after he was in the house in May 2017. “While he was collecting his tools, she was collecting her loaded gun, she was focused, focused on confronting him and removing tony from her life once and for all,” said Assistant Polk County Attorney Shannon Archer. “The imminent threat was his presence” Defense attorneys, however, said a history of violence and abuse with the family made Alexander feel threatened. “Tony displayed a smorsgesborg of behaviors that instilled fear in the whole family, in Sera Alexander, and ultimately contributed to his death,” said defense attorney F. Montgomery Brown. Alexander’s mother and Hartmann’s estranged wife, Susan Hartmann, testified Wednesday that she didn’t feel safe in the home, often spending increased time at work. “I never knew when I was going to get hurt. When he wasn’t physically hurting me he was threatening. He would threaten to destroy the house,” Hartmann testified. “If I stayed, things would get destroyed in the house. If he wasn’t harming me physically … I never knew when he’d be on a rant and literally be up all night long screaming.” As part of the plea agreement, Alexander waives her right to appeal, and both
Apr 18, 2026 · via weareiowa.com
Abstract Single-Image Super-Resolution (SISR) has witnessed a significant shift from traditional methods to deep learning, leading to flourishing developments recently. However, effectively handling arbitrary scales (e.g., integer, non-integer, or asymmetric) with a single model remains a challenging task. Existing SISR models fail to adequately perceive scale variations during the extraction of resolution features for arbitrary scales, while their limited local receptive fields hinder the modeling of global image structures. Furthermore, due to insufficient consideration of the impact of scale factors and local feature diversity on the upsampling stage, the generation of non-integer scale super-resolved images often suffers from incoherent details or abrupt transitions. To address these limitations, we proposed a cross-scale dynamic arbitrary-scale super-resolution network (CDASSR-Net) from the perspectives of cross-scale dynamic feature extraction and adaptive upsampling. Firstly, we propose a scale-aware feature adaptation (SAFA) module that adaptively adjusts filters according to the scale factor. Meanwhile, the cross-scale feature fusion via skip connections is proposed to better accommodating the demand for multi-scale feature representation and mitigating the loss of detail information common in deep networks performing such fusion. Then, we design a locally-adaptive scale-aware upsampler (LASU) module, which dynamically generates filters based on the input scale information, enabling upsampling to generalize to arbitrary resolutions. Extensive experiments conducted on various benchmark datasets demonstrate that integrating the proposed modules into fixed-scale SR networks allows them to achieve satisfactory performance on non-integer or asymmetric scales, while maintaining superior performance on integer scales. The code is available at https://github.com/Zheng4x/CDASSR. Similar content being viewed by others Data availability The datasets generated or analysed during the current study are available in the repository. DIV2K: https://data.vision.ee.ethz.ch/cvl/DIV2K/. Set5, Set14, BSD100, Urban100, and Manga109: https://pan.baidu.com/s/1qeftNHrWSjLxfhJCjfqNyw?pwd=9ag4. GF1K: https://pan.baidu.com/share/init?surl=NeFj2gnAHuq0tKdZW_bqoA?pwd=isku. References Bashir, S. M. A. et al. A comprehensive review of deep learning-based single image super-resolution. PeerJ Comput. Sci. 7, e621 (2021).
Apr 18, 2026 · via nature.com
In the global rush to develop and deploy artificial intelligence, one metric remains conspicuously absent: how many people have died, directly or indirectly, because of AI? No government agency, international watchdog, or industry group maintains a public database of AI-attributable deaths. Yet researchers, journalists, and legal advocates have documented dozens of cases where artificial intelligence systems, whether embedded in military drones, medical diagnostics, criminal justice tools, or consumer applications, have either played a role in human deaths or have created conditions where fatal outcomes were more likely. Without clear accounting, the answer to a basic question of “how dangerous is AI, really?” remains hidden beneath layers of proprietary algorithms, regulatory opacity, and institutional denial. AUTONOMY AND WARFARE: AI’S DEADLIEST EDGE Nowhere are the risks more literal than in the defense sector. Since 2020, multiple open-source investigations have reported that AI-assisted autonomous drones have engaged targets in live combat zones without human confirmation. A 2021 United Nations Security Council report on Libya referenced a Turkish-made Kargu-2 drone that allegedly attacked retreating soldiers autonomously. Though the Libyan government did not confirm casualties, human rights observers warned the incident marked a pivotal shift in combat ethics. A machine had decided, unilaterally, to kill. The same year, reports surfaced that the Israeli military had used AI-assisted target selection in operations against Hamas. While Israeli Defense Forces denied that AI made final strike decisions, the role of algorithmic analysis in lethal operations was confirmed. Despite international treaties such as the Geneva Conventions requiring accountability in war, no formal legal framework exists to assign liability when AI miscalculates. As a result, civilian casualties from drone warfare, whether caused by faulty image recognition, misclassification of movement, or heat signature confusion, go unlinked to AI entirely, even when machine intelligence was involved in the targeting chain. MEDICAL ERRORS
Apr 18, 2026 · via milwaukeeindependent.com
Puerto Rico National Guard Youth ChalleNGe Academy graduates, reveal the winning design for Denim Day during a Sexual Assault Awareness and Prevention Month recognition day at Fort Buchanan, Guaynabo, Puerto Rico, April 8, 2026. PRNG Youth ChalleNGe Academy former Cadets showcased multiple designs that competed to be the official logo for SAPR Denim Day in the PRNG. (U.S. Air National Guard photo by Senior Airman Victoria A. Jewett)
| Date Taken: | 04.08.2026 |
| Date Posted: | 04.17.2026 09:07 |
| Photo ID: | 9621806 |
| VIRIN: | 260408-Z-QU148-1011 |
| Resolution: | 7363x4909 |
| Size: | 8.46 MB |
| Location: | GUAYNABO, PR |
| Web Views: | 2 |
| Downloads: | 0 |
This work, SAAPM Recognition Day [Image 12 of 12], by SrA Victoria Jewett, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
Apr 18, 2026 · via dvidshub.net
Walking into MSG for a Knicks game or Harry Styles concert means your face gets scanned, cataloged, and cross-referenced against watchlists before you reach your seat. As reported by Wired, since 2018, Madison Square Garden has deployed facial recognition technology at entrances, partnering with Xtract One’s SmartGateway system to process 40 people per minute through AI-powered cameras integrated with metal detectors. What began as security theater has morphed into something far more invasive, raising serious digital rights concerns. The Technology Behind the Tracking High-tech gates scan faces faster than you can buy overpriced nachos. The SmartGateway system, powered by eConnect’s facial recognition software, creates instant digital dossiers on attendees. MSG’s “council” assigns priority scores to flagged faces—Priority 2 means “OBSERVE: DO NOT APPROACH”—turning venue security into algorithmic profiling. This technology affects innocent attendees too, with false positives creating unnecessary confrontations and ejections. Critics face ejection based on owner James Dolan’s personal grudges. According to whistleblower lawsuits, security chief John Eversole allegedly tracked Nina Richards, a trans Knicks fan, second-by-second during a 2022 Pride Night game, logging her bathroom visits and interactions without any evidence of threat. From Security to Personal Vendettas Owner James Dolan weaponized surveillance against critics, lawyers, and fans who dare complain. MSG has banned 900-1,500 lawyers from venues—anyone whose firm has sued the company gets flagged and ejected. The system monitors social media for “sell the team” chants, compiles investigative dossiers on critics, and extends surveillance beyond venue walls to neighborhood patrols. “Dolan quadrupling down on his use of facial recognition across MSG venues is pathetic,” says Will Owen of S.T.O.P., a surveillance accountability group. Your Privacy Disappears at the Door What happens at MSG doesn’t stay at MSG—your biometric data travels everywhere. This isn’t isolated to one paranoid billionaire’s empire. MSG Entertainment operates Radio City Music
Apr 18, 2026 · via tech.yahoo.com
‘The face thing is probably going to break’ — Sam Altman-backed firm warns AI will soon outgrow facial recognition, but says its ‘proof of human’ system World ID could be part of the solution A new ‘proof of human’ system aims to tackle deepfakes Sign up for breaking news, reviews, opinion, top tech deals, and more. You are now subscribed Your newsletter sign-up was successful Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Facial recognition has become one of the default ways we prove who we are online, from unlocking our phones to logging into banking apps. But according to a senior figure at a Sam Altman-backed startup, that entire system may not hold for much longer, thanks to AI. “Over time the AI is going to get so powerful that really, the face thing is probably going to break,” says Tiago Sanda, Chief Product Officer for Tools for Humanity, as I catch up with him to discuss the latest upgrade to its World ID system. The company behind the controversial Orb device, is rolling out new ways to use its "proof of human" system in a world where AI-generated faces, voices, and identities are getting harder to spot by the day. Article continues belowHow the Orb works If you cast your mind back to about a year ago you’ll remember the Orb — essentially it was a fancy camera inside a round case — that could verify that you were human and give you a World ID to prove it. The Orb has a bunch of sensors inside. Some of them are similar to what’s inside your iPhone, like near- and far-spectrum infrared, but it also has cameras and a very powerful Nvidia chip inside it. So, it's able
Apr 17, 2026 · via techradar.com
- Equinix’s Arun Dev argues it’s time to upgrade an old mantra: Now, “the network is the agent” - New Equinix Fabric Intelligence turns the network into a multi-agent system that can understand intent and take action - As cool as it is, it could take another year or two for agentic AI to really catch on, Dev said It’s one thing to say that networks will be critical foundational pillar underpinning AI and the agentic revolution. It’s quite another to assert that the network itself needs to become an intelligent agent. But that’s exactly what Arun Dev, Equinix VP of Interconnection, said needs to happen and exactly what the colocation provider is trying to achieve. Back in the 1980s, Sun Microsystems coined the phrase “the network is the computer.” Dev said that slogan needs an update. “In the AI era, we believe the network is the agent,” he told Fierce. And that change means updating the network so it can become “an agent in its own right,” one capable of understanding intent, enforcing policies and adapting to growing connectivity needs. Hence the launch of Equinix Fabric Intelligence. The company’s fabric offering itself has been around for more than a decade. But Dev said Equinix has been working since the launch of model context protocol (MCP) late last year to build in new agentic capabilities. According to Dev, Fabric Intelligence is a multi-agent system that uses specialized agents to perform specific tasks. So, for instance, there are lightweight models being used for pattern recognition and large language models that provide the conversational interface. The end result is a system that removes a lot of manual processes around provisioning and helps fill in enterprise skills gaps in deep networking expertise. To be fair, Lumen Technologies has been banging the drum about
Apr 17, 2026 · via fiercewireless.com
NEW YORK, N.Y. — According to an ACLU report published April 14, 2026, Kimberlee Williams, an Oklahoma resident, was wrongly jailed after Maryland police relied on faulty facial recognition software that falsely identified her as the perpetrator of a bank robbery in a state she had never visited. According to the report, in June 2021, police in three Maryland counties “accused Ms. Williams of being a match to an unknown individual who had entered several bank branches in Maryland, impersonated account holders, and withdrawn thousands of dollars from their accounts.” The banks investigating the incident sent a picture of the unknown suspect to “a national listserv of police and private investigators called Crimedex. Someone on the listserv ran the image through facial recognition technology and sent back Ms. Williams’ name and photo as a purported match to the suspect.” According to the report, without any further research or oversight, county police obtained a warrant for Ms. Williams’ arrest. Further illustrating the lack of diligence, the detective applying for the arrest warrant falsely claimed that Ms. Williams had been identified as the suspect “and that the detective had confirmed the identification by visually comparing a photo of the suspect with an older photo of Ms. Williams. Because the facial recognition search had found an innocent person (Ms. Williams) who looked similar to the suspect—an inherent problem with the technology—the officers claimed verification was worthless.” According to the report, after Ms. Williams’ arrest, she was jailed in Montgomery County for six months and was only released in December 2021 when charges from two other counties were also dropped. According to the report, Kimberlee Williams is not the only person who has been falsely accused and jailed because of faulty facial recognition software. “We now know of 14 people across the country who
Apr 17, 2026 · via davisvanguard.org
Two factors dominate our search for life and habitability elsewhere in the galaxy. The first is liquid water, which, as far as we know, is necessary for life. When we find exoplanets, scientists try to determine if they're in their stars' habitable zones. Under the right atmospheric conditions, liquid water could persist there. The second is biosignatures. One of the reasons the JWST was built was to study exoplanet atmospheres and determine their contents, and it's found some very interesting potential biosignatures. But scientists struggle with the fact that an atmospheric biosignature here on Earth could have a non-biological origin on exoplanets that are much different from Earth. One of the ways forward is to develop an agnostic viewpoint. That's the focus of new research in The Astrophysical Journal titled "An Agnostic Biosignature Based on Modeling Panspermia and Terraforming." The authors are Harrison Smith from the Earth-Life Science Institute (ELSI) at Institute of Science Tokyo and Lana Sinapayen from the National Institute for Basic Biology in Okazaki City, Japan. "Realistically, there are just a few locations to search for alien life within the solar system," the authors write. "Outside the solar system, opportunities are nearly unlimited, but thereâs a catch: it is difficult to attribute, with certainty, features of exoplanets to extraterrestrial life." The authors point out that individual biosignatures are susceptible to false positives, and that searching for technosignatures isn't much better. They're based on a whole host of underlying assumptions about the nature of a civilization's technology and culture. This work is focused not on individual exoplanets, biosignatures, and technosignatures, but on situations where life is spreading from world to world. "We have developed an agnostic approach to exoplanet life detection that overcomes these limitations by using properties that emerge on the scale of groups of planets, without
Apr 17, 2026 · via universetoday.com
By Lauren Yu, William J. Brennan Fellow, ACLU Speech, Privacy, and Technology Project; and Nathan Freed Wessler, Deputy Director, ACLU Speech, Privacy, and Technology Project When police arrested Kimberlee Williams, a grandmother living in Oklahoma, because of a warrant from Maryland, she was shocked. She had never been to Maryland in her life. Ms. Williams later learned that Maryland police had relied on an incorrect result from facial recognition technology that falsely flagged her as a suspect. She is the fourteenth person in the U.S. to join a growing list of people wrongfully arrested because police let flawed facial recognition technology taint their investigations. Police use of facial recognition technology is dangerous, and stories of people wrongfully arrested because of police reliance on incorrect facial recognition results continue to surface. Today, the ACLU and ACLU of Maryland sent letters to three Maryland police departments on behalf of Ms. Williams, who was wrongfully arrested and jailed for six months because Maryland police relied on a false facial recognition result and concealed their reliance on that unreliable technology from the court when applying for an arrest warrant. One Woman Arrested for a Crime She Didn't Commit On June 23, 2021, Ms. Williams was accompanying one of her daughters on a DoorDash delivery to a local military base in Lawton, Oklahoma. When base security at the entry checkpoint conducted a standard identification check, they discovered outstanding Maryland arrest warrants for Ms. Williams and detained her. These warrants sought Ms. Williams’ arrest for a series of fraudulent over-the-counter cash withdrawals in Maryland in December 2019 and January 2020. An unknown individual had entered SunTrust and Truist bank branches in three different counties, impersonated account holders, and fraudulently withdrew thousands of dollars from those individuals’ accounts. Ms. Williams, however, was nowhere near Maryland during this
Apr 17, 2026 · via acluga.org
Tinder and Zoom offer 'proof of humanity' eye-scans to combat AI - Published Tinder will let users prove they are human and not robots by bringing advanced eye-scanning technology to the app amid rising fears over AI. Users of the dating app, as well as other major platforms such as video calling service Zoom, will be able to scan their irises to earn a "proof of humanity" badge attached to their profile or name. Through either an online app or an orb-shaped scanning device run by the World network people can submit to a scan of their iris, the coloured portion of the eye, in order to confirm they are human. World, formerly known as Worldcoin, is part of Tools for Humanity, a start-up co-founded and chaired by Sam Altman who is also the head of ChatGPT-maker OpenAI. Once a person is confirmed as human by the technology they receive a unique identification code which is stored on their smartphone and considered their World ID. A new World ID app, as well as the partnerships with Tinder and Zoom, were revealed during a live event in San Francisco on Friday. It began with a video projected on several large screens in a small auditorium depicting several famous journalists, including Walter Cronkite, Dan Rather, and Larry King, as well as former President Ronald Regan. All of the men were shown using historic video footage that had been altered using AI to have them appear to be realistically discussing the need for a way to identify who is human on the internet. Altman took the stage briefly after the deepfake montage to applause from an audience of a few hundred people. He said there will soon be "more stuff made by AI than is made by humans" online. "I'm not afraid for
Apr 17, 2026 · via bbc.co.uk
While this may not come as a surprise to everyone—especially those who follow developments in tech forums—it remains an important issue that continues to raise concerns. Over the past few years, discussions have highlighted a critical vulnerability in some smartphones: the ability to unlock certain Android devices using nothing more than a simple 2D photograph printed on paper. A survey conducted by Which?, and widely circulated on social media, found that several well-known smartphone brands—including Samsung Galaxy Series, Motorola, Xiaomi, Vivo, Honor, Nokia, and Oppo—were susceptible to this method. In these cases, the facial recognition systems could be tricked by a low-resolution image, suggesting that not all implementations of this technology are equally secure. This raises serious concerns about the reliability of basic facial recognition systems, particularly when they rely solely on 2D image matching rather than more advanced sensing techniques. In contrast, Apple iPhone devices performed significantly better in the same tests. Apple’s Face ID uses a more sophisticated approach, employing infrared sensors and structured light to create a detailed 3D depth map of a user’s face. This depth-based analysis makes it far more difficult for attackers to bypass the system using flat images or simple replicas. As a result, these devices were rated as more secure in terms of biometric authentication. For Android users who rely heavily on facial recognition to protect their data, this finding is worth serious consideration. Many people assume that biometric locks automatically guarantee a high level of security. However, if a device can be unlocked with a printed photo, sensitive information stored on the phone becomes vulnerable. This risk becomes even more significant when financial applications are involved. Consider a scenario where a user stores payment details in a digital wallet like Google Pay. If an attacker gains access to the phone through
Apr 17, 2026 · via cybersecurity-insiders.com
More than 25 years after its founding, the site has evolved into the internet’s leading platform for artists to grow and monetize their audience. If you spend much time online — especially around Gen Z — you may have noticed that Y2K internet culture is having a moment. Scrolling fatigue, coupled with a reliable nostalgia factor, has sparked a return to the user-generated, creator-centric format and aesthetics of the Blogosphere and early social media. Launched in 2000, DeviantArt is to many an avatar for this era and synonymous with Web 2.0’s niche subcultures. But in 2026, DeviantArt is more accessible, widely used, and creator-friendly than ever before. After a period of network decline through the 2010s, the platform underwent a multi-year overhaul to modernize its user experience and strengthen its core offerings. As a result, usership has been on a steady rise since 2019; DeviantArt now boasts more than 108 million users worldwide. The site calls itself a home for artists of all kinds, with more than 100 million new artworks across 150 distinct artistic genres and categories uploaded in 2025 alone. The bottom line: Whether you’re a creator, a collector, or a seller, your peers are on DeviantArt. This resurgence is undoubtedly driven in part by DeviantArt’s robust creator-first functionality. DeviantArt’s Protect feature uses state-of-the-art image recognition to help safeguard creators’ work against unauthorized use, and the platform employs a dedicated team to investigate and mitigate the impact from spam, scams, fraud, and other bad actors. As of 2019, DeviantArt is also completely free of third-party ads, unlike other mainstream social media platforms whose business model relies on virality and advertising revenue. Dropping ads wasn’t merely an aesthetic choice, though. One of the most significant shifts driving the modern DeviantArt user experience is a revamped monetization model that shifts
Apr 17, 2026 · via artnews.com
Abstract “Data hugging” blocks independent verification of medical AI. Apple claims age estimation with a mean absolute error of 2.9 years using photoplethysmographic (PPG) signals. Given PPG’s noise, such accuracy is questionable, raising concerns about other tech companies’ claims. Using UK Biobank data, we find this accuracy unreplicable, achieving results only marginally better than predicting mean age. We advocate for curated public benchmark datasets and evaluation platforms to protect the public from unverifiable claims. Similar content being viewed by others Introduction “Water, water everywhere, nor any drop to drink” from The Rime of the Ancient Mariner, by Samuel Taylor Coleridge, nicely describes almost every academic AI health researcher’s challenges with access to data. Medical AI has always promised to revolutionize healthcare, from early disease detection to personalized treatment, but its success hinges on robust evidence and public trust. Yet today, many cutting-edge health AI models are developed behind closed doors on proprietary datasets, precluding independent verification. Data and code sharing is remarkably scarce in medical AI literature: a recent systematic review of 1342 studies of AI in critical care found that 85% of studies did not make their datasets available, and 87% of studies did not provide relevant code1. Such widespread absence of transparency and reproducibility impedes external validation, hampers cumulative scientific progress, and, as we show here, leads us to believe we are safer than we are. Several high-profile failures of prominent AI algorithms have already surfaced: Epic’s widely used sepsis prediction algorithm was shown to have poor performance on external retrospective validation, after it had already been deployed in hospitals across the United States2. Likewise, Philips recently issued a Class I software correction for its outpatient telemetry monitoring service when the algorithm failed to transmit ECG alerts for atrial fibrillation and ventricular tachycardia, contributing to two patient deaths
Apr 17, 2026 · via nature.com
Her movements were tracked, over and over. When she sat down. When she ordered a drink. When she went to the bathroom. When she took the elevator. Nina Richards went to New York Knicks games quite a bit, and the security forces at Madison Square Garden used the arena's network of cameras to follow her. New Yorkers have known for a long time that going to a game or concert at the Garden meant surrendering some privacy. That, as you watched the show, the Garden in a real sense watched you. Since 2018, there have been reports of the venue deploying face-recognition technology in what critics believe are increasingly intrusive ways. Owner James Dolan has watch lists of basketball fans who have dared criticize his management. He keeps a close eye on his other venues too, including Radio City Music Hall and the Sphere in Las Vegas. Last March, Dolan’s security team blocked a graphic designer from seeing a concert; the designer, years earlier, had printed and sold a half-dozen T-shirts reading “Ban Dolan.” He has locked out whole firms’ worth of lawyers, even keeping out a mom who was trying to take her 9-year-old Girl Scout to a Christmas show at Radio City Music Hall; the mom’s coworker had pissed him off. But the true extent of Dolan’s panopticon has only been caught in glimpses. A 2025 lawsuit by a former member of the MSG security team lifted the veil, just a bit. We started our own digging into the Garden's operations. We discovered that Dolan’s security teams obsessively tracked Nina Richards, a trans woman, over a two-year period, monitoring her movements through the venue down to the second. (WIRED is using a pseudonym in this article out of respect for her privacy.) Dolan's biometric surveillance is so extensive
Apr 17, 2026 · via wired.com
Facebook is trying out a new approach to get people to share more content, with users in the U.K. now able to opt into a process that will recommend photos to share from users’ camera roll and provide suggestions for edits, collages, etc. The new feature, which people will have to opt in to use, will enable Meta’s system to scan the camera roll on a users’ device to access their images. It will then recommend collections, like travel collages and recaps, that the user can post to the main feed or Stories. Letting Meta scan all the images on a device may not be exactly what people want. But it sure is something. As explained by Meta: “Many people capture life’s moments but rarely share them — whether it’s because they don’t think their photos or videos are ‘shareworthy,’ or because they simply don’t have time to create something special. With your permission, this opt-in feature analyses media in your camera roll to find standout moments — the memories that can get lost among screenshots, receipts and random snapshots.” The tool will also recommend creative edits and generate videos from camera roll content in order to help users create stand-out content. “You may see these recommendations appear in Stories, Feed and Memories (a Facebook bookmark) for you to review privately before deciding what to share,” Facebook said. “You can manage or disable the feature at any time in your Facebook camera roll settings.” Yeah, it sounds a little bit creepy, and a little bit intrusive, and it’s unlikely many Facebook users will be overly keen to set Meta’s crawlers free in their camera roll, even with the assurance that they’ll always be asked to provide consent for any image sharing. Facebook experimented with something similar in the U.S. last
Apr 17, 2026 · via socialmediatoday.com