Testing has revealed that smartphones from major brands including Samsung and Motorola can be unlocked using printed images of the owners face. Consumer experts have warned that this security loophole could be exploited by criminals to unlock devices and access personal information. Which?, the UK’s largest independent consumer organisation, has been carrying out lab tests on hundreds of phone models since 2022, assessing features from battery life to security features. While most smartphones now offer facial recognition to unlock mobile devices, Which?’s testing found that as many as 64% of phones – 133 devices since 2022 – could be tricked by a printed image. Phones that failed the organisation’s tests include top-of-the-range models such as the Oppo Find X9 Pro, which retails for upwards of £1,000. According to Which?, Samsung’s former flagship range of Galaxy S25 phones could all be fooled by a 2D photograph, while the some lower-priced Android phones also struggled, often relying on a standard 2D facial recognition system. Which? Found that the newest Google Pixel models and Samsung Galaxy S26 series passed their tests and Apple Face ID was considerably harder to trick. The non-profit says that some device cameras take flat pictures, which means they cannot always distinguish between a real person and a high-resolution photo. Most phones that failed Which?’s test did have an onscreen message warning that face recognition cannot be relied upon for security. Lisa Barber, Which? Tech Editor said: “These security flaws are far from isolated incidents. “The majority of Android phones we’ve tested in the last four years can be easily unlocked using a 2D image, and some manufacturers are still failing to adequately warn their users that this is the case. “We’d urge affected users to set up alternative methods of security, like a fingerprint or a PIN, which
Apr 19, 2026 · via news.stv.tv
Specialists from the Unified Center for Biometric Testing (ECBI) conducted the first testing of Russian facial recognition systems. Seven IT solutions were tested for accuracy, the press service of the Department of Information Technology (DIT) of Moscow reported. The tests involved four companies from Moscow and one from Chelyabinsk. Their biometric algorithms had to find similar faces in a database of 750 thousand images. How the algorithms were evaluated When evaluating IT solutions, the following parameters were taken into account: data collection reliability (processing images of a person in glasses, in a half-turn) and recognition accuracy (error rate). The final result was calculated based on the arithmetic mean of all metrics. Dmitry Golovin, Deputy Head of the DIT of Moscow, said that the algorithms analyzed images from city video surveillance cameras. The test participants demonstrated their developments in real, not laboratory conditions, he added. As a result, the market receives a transparent tool for selecting technologies for a specific business task. The DIT of Moscow also noted that the ECBI will regularly conduct such tests. This will allow tracking progress in the development of domestic biometrics. Read more materials on the topic: - In Russia, they began to let into trains using biometrics — how it works - Face instead of a passport: biometrics is gaining popularity in Russia - Payment by "face" in buses: a new biometric travel system will be launched in Moscow
Apr 19, 2026 · via www1.ru
Abstract At present, multi-scale learning is a popular and effective method to improve the accuracy of real-time semantic segmentation. However, these multi-scale methods do not consider the influence of CNN receptive field on the feature discriminability. They still suffer from the small receptive field and insufficient feature extraction, which limits the accuracy of real-time segmentation. To solve the problem, we propose a novel Triple-Branch Multi-Scale Network (TBMSNet) for real-time semantic segmentation. Specifically, in initial feature extraction stage, we propose the Simple Inverted Residual (SIR) module with reducing the number of input channels, using two successive SIR modules to initially extract features, which can enhance the feature extraction capability of lightweight backbone network. Subsequently, we design a new multi-scale triple-branch structure to parse detail, semantic, and boundary information respectively. In triple-branch structure stage, we propose the Dilation-wise Residual (DWR) module in Semantic branch, which combines the multi-scale detail and boundary branches down-sample semantic feature maps to 1/64. The design can extend the valid receptive field and improving the capture efficiency of multi-scale information. Besides, we also design a Multi-scale Semantic Aggregation Pyramid Pooling (MSAPP) module in semantic branch, which connects multi-scale pooling maps before the convolutional layer to form local and global context representations for further enriching the semantic information, and extract multi-scale features more efficiently. Experiments show that our TBMSNet achieves an accuracy of 80.5% mIoU on Cityscapes and an inference speed of 50.4 FPS, achieving the best trade-off between inference speed and accuracy. Similar content being viewed by others Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Corresponding authorshould be contacted if someone wants to request the data from this study. Code availability The code are available from the corresponding author upon reasonable request. References Long et
Apr 19, 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 19, 2026 · via weareiowa.com
Abstract With advancements in big data and internet technologies, images are becoming central to professional and recreational activities. While watermarks are crucial for copyright protection, their robustness against common manipulations such as compression or filtering also makes their removal for legitimate restoration purposes highly challenging. Traditional approaches to watermark removal almost always require manual tuning of parameters and complex optimization, resulting in limited applicability in practical use. To address these issues, this paper presents an improved self-supervised convolutional neural network (CNN) for image watermark removal, enhanced with Particle Swarm Optimization for hyperparameter tuning. The proposed approach performs self-supervised learning to generate training data, while avoiding the preparation of clean reference images, and benefits from PSO-based optimization in pursuing faster convergence and higher restoration quality. Experimental results on the PASCAL VOC 2012 dataset show that the proposed PSO-SWCNN has achieved the best performance among several state-of-the-art methods with the highest SSIM and PSNR. This integrated approach offers an effective and efficient solution in removing watermarks from images and restoring them for research and archival purposes. Similar content being viewed by others Data availability Data are publicly available. The PASCAL VOC 2012 dataset, which was used for training and evaluating the models, can be accessed at: https://huggingface.co/datasets/nateraw/pascal-voc-2012Additional data, scripts, and code generated and/or analyzed during the current study are available at: https://github.com/maedeh-dashti/PSO-SWCNN. References Petitcolas, F. A., Anderson, R. J. & Kuhn, M. G. Information hiding-a survey. Proc. IEEE 87(7), 1062–1078 (1999). Islam, M. S. & Chong, U. P. A digital image watermarking algorithm based on DWT DCT and SVD. Int. J. Comput. Communication Eng. 3(5), 356 (2014). Cox, I., Miller, M., Bloom, J., Fridrich, J. & Kalker, T. Digital watermarking and steganography (Morgan kaufmann, 2007). Petitcolas, F. A. & Katzenbeisser, S. Information hiding techniques for steganography and digital watermarking (Artech House Computer
Apr 19, 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 19, 2026 · via weareiowa.com
Can everyone use local AI? We tested it on a budget phone, and the results were disappointing. In April this year, Google released the new-generation open-source large model, Gemma 4. This time, it launched four versions at once, covering everything from mobile phones to workstations. The two smallest versions are specifically designed for mobile devices and are mainly for fully offline operation. This isn't really that rare, but more importantly, Google now wants mobile phones to run local models. You may have come across a lot of content about the actual installation and testing of Gemma 4. However, most of the existing online tests are conducted on the latest iPhones or flagship phones. These flagships are the latest models, with top-notch performance and computing power, so it's reasonable that they perform well. At this point, Xiaolei can't help but ask, If you use an ordinary Android phone that costs a few hundred to over a thousand yuan, with a mid-range processor and not top-notch computing power, can the local model still be used normally? How big is the gap compared to those flagship phones? (Image source: Photographed by Lei Technology) Digging deeper, is local AI destined to be an exclusive feature of flagship phones? We want to figure this out, so we directly took a thousand-yuan Android phone with a mid-range chip to test Gemma 4 and see how it performs. A thousand-yuan phone running a local model is a complete "disaster" The phone we used for this test is the vivo Y500 Pro, a typical thousand-yuan Android phone. Although it's not an old model, the overall performance of its SoC is still average. After all, its price is set like this, and there's really not much to say. It uses the MediaTek Dimensity 7400, manufactured by TSMC using a
Apr 19, 2026 · via eu.36kr.com
TOPEKA, Kan. — Following a federal investigation, the U.S. Department of Education’s Office for Civil Rights and the Student Privacy Policy Office concluded that four school districts in the Kansas City metropolitan area, including Topeka Public Schools, violated federal law through their transgender student policies and now face the potential loss of federal funding if no resolution is reached. According to The Topeka Capital-Journal, the possible federal funding cuts could affect Topeka USD 501, Kansas City USD 500, Olathe USD 233 and Shawnee Mission USD 512. As The Topeka Capital-Journal reported, the Trump administration announced that policies in the Kansas districts violated Title IX and the Family Educational Rights and Privacy Act, or FERPA. Further, the Trump administration stated in a press release that “Topeka Public Schools violated Title IX with policies that allow male students to use female restrooms, locker rooms, and changing rooms, as well as participate in single-sex athletics, based on ‘gender identity.’” The Topeka district has confirmed to the Office for Civil Rights that “male students have been allowed to use female restrooms and locker rooms based on ‘gender identity.’” Further, the Trump administration stated that USD 501 violated parents’ rights under FERPA by “concealing from parents” school records and information regarding a child’s “gender transition,” different pronouns, names and related matters. Kimberly Richey, a Trump administration official and assistant secretary for civil rights, stated, “These Kansas school districts have allowed ‘gender ideology’ to run amok in their schools.” She continued, stating that “These policies not only violate federal law, but are contrary to the sound judgment we expect from our educational leaders, and thoroughly disrespectful to parents who entrust school personnel to keep their children safe.” With this, the Trump administration warned it could pull federal funding from the four school districts. According to USD
Apr 19, 2026 · via davisvanguard.org
New intelligent infrastructure framework brings predictive operations, stronger security, and consistent performance across on-premise and cloud environments Ahmedabad (Gujarat) [India], April 17: Cygnet.One today announced an expanded direction for its Managed IT Services portfolio with the introduction of Cygnet STRATA, a layered infrastructure framework built to support modern businesses that depend on stable, secure, and high-performing IT environments. As IT systems take on greater operational responsibility, the cost of outages, security gaps, and performance slowdowns continues to rise. Many organizations still rely on reactive support models that respond after issues occur. Cygnet.One is positioning its managed services approach to move beyond that model, focusing on predictability, visibility, and continuous improvement across the infrastructure lifecycle. At the center of this shift is STRATA, a six-layer infrastructure stack designed to connect physical systems with cloud ecosystems while enabling real-time monitoring, analysis, and response. Built on AIOps principles, STRATA integrates telemetry ingestion, event correlation, anomaly detection, and automated remediation into a unified operating model. This allows infrastructure to shift from fragmented monitoring to coordinated, intelligence-driven operations. STRATA operates across six core layers. The SENSE layer focuses on physical infrastructure. It uses telemetry pipelines, sensor-based monitoring, and AI-driven diagnostics to continuously track servers, storage systems, and environmental conditions such as temperature, power, and network health. This layer builds a live operational baseline and detects early signs of hardware degradation or capacity stress. The TRANSMIT layer manages signal flow across the infrastructure. It aggregates and normalizes data streams from multiple sources, filters noise, and prioritizes actionable alerts. This ensures that only relevant signals are passed to operations teams and centralized NOC environments, reducing alert fatigue and improving response accuracy. The REASON layer applies AIOps intelligence. It uses pattern recognition, event correlation, and predictive modeling to identify anomalies across systems. By linking events across compute, storage,
Apr 19, 2026 · via ahmedabadmirror.com
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
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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 |
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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