6 Cool Features That Have Disappeared From Samsung Galaxy Phones Smartphones have changed the world in a huge way, bridging the gap between reality and science fiction with every passing year, thanks to so many different apps and features. Features tend to be a big draw for a lot of consumers, especially when they're exclusive to the brand. Samsung continues to reign supreme on the Android side of the market thanks to the many capabilities its flagship handhelds offer. Unfortunately, over the years, the brand has removed some of the most beloved (and some not-so-beloved) features from its devices. Some of the features Samsung did away with weren't exclusive to the brand, but it nonetheless removed them from its flagships. Others were features that only Samsung Galaxy devices have, and many loyalists miss and continue to lament their absence. Sure, users could jump ship to another brand if it offers that feature, but it's not easy when you're a fan of a specific brand. All you can do is hope that the feature will return one day. Iris scanners Iris scanners seemed to be something out of science fiction, and you might be surprised that you don't see them on more handhelds in 2026. Like fingerprint scanners and facial recognition on your smartphones, the iris scanner was a security feature that scanned your eyes before unlocking your device. Samsung experimented with this technology when it launched the Galaxy Note 7, letting users unlock the device and activate Samsung Pass. It was also used by large businesses so authorized users (employees) could unlock certain workspace apps. Samsung eventually did away with the iris scanner by the time the Galaxy S10 launched, unfortunately. It likely went away because Samsung found fingerprint scanners to be more accurate. You might expect a device that
May 27, 2026 · via bgr.com
Kenvue Partners with Greyparrot to Improve Thier Waste Intelligence Edited by Adam Harrie — May 26, 2026 — Eco This article was written with the assistance of AI. References: greyparrot.ai & packagingeurope Greyparrot expanded its AI-powered waste intelligence platform through a partnership with consumer health company Kenvue, applying machine learning and image-recognition technology to analyze packaging performance in commercial recycling facilities. The collaboration uses Greyparrot’s Deepnest system to monitor packaging streams in real time, classify materials and measure how components such as labels, pumps and material types affect sorting and recovery rates. By creating a digital twin of operational recycling systems, the platform gives Kenvue facility-level data on contamination, packaging flow and recyclability outcomes across facilities in the U.K. and U.S. The insights are intended to help packaging teams evaluate design changes before manufacturing prototypes while also preparing for stricter regulations tied to packaging waste and extended producer responsibility frameworks. For consumers and brands, the technology could improve packaging recyclability and increase transparency around real-world recycling outcomes. The partnership reflects a broader shift toward AI-driven recycling intelligence and digital-twin systems that help companies optimize circular packaging strategies using operational data rather than theoretical models. Image Credit: Greyparrot By creating a digital twin of operational recycling systems, the platform gives Kenvue facility-level data on contamination, packaging flow and recyclability outcomes across facilities in the U.K. and U.S. The insights are intended to help packaging teams evaluate design changes before manufacturing prototypes while also preparing for stricter regulations tied to packaging waste and extended producer responsibility frameworks. For consumers and brands, the technology could improve packaging recyclability and increase transparency around real-world recycling outcomes. The partnership reflects a broader shift toward AI-driven recycling intelligence and digital-twin systems that help companies optimize circular packaging strategies using operational data rather than theoretical models. Image
May 27, 2026 · via trendhunter.com
Abstract Underwater Acoustic Target Recognition (UATR) plays a significant role in intelligent sonar and underwater environmental monitoring systems, but successful recognition in underwater environments of complex scenarios is a significant challenge because of the effects of ambient noise, signal attenuation, and dynamic propagation. The recent developments in deep learning have enhanced automatic generation of features in acoustic signal classification, and the vast majority of existing models represent a trade-off between recognition accuracy and computational efficiency. In this regard we introduce Lightweight Hybrid Attention Network with Multi Scale Feature Integration (DCAT) a new deep learning system that combines depthwise separable convolutions to extract local features efficiently in parallel in conjunction with transformer-based global temporal dependency modeling attention modules. The key innovation of DCAT is its adaptive fusion mechanism, which conditionally combines contextual information of the two transformer branches with different receptive fields with varying scales with the purpose of allowing the model to ideally capture small-scale local features and long-range acoustic structures. The framework employs robust preprocessing and feature engineering, including Zero Crossing Rate (ZCR), Root Mean Square Energy (RMSE), Mel-Frequency Cepstral Coefficients (MFCC), and Chroma features, computed from 22.05 kHz sampled audio, combined with data augmentation techniques—pitch shifting, time stretching, and Gaussian noise addition—to enhance generalization to real-world acoustic variability. Evaluated on two benchmark datasets, DeepShip and ShipsEar, DCAT achieves superior classification accuracies of 98.84% and 99.16%, respectively, while maintaining extremely low computational complexity of only 0.52 million parameters and 6.1 million FLOPs, supporting real-time inference with latency below 0.7 ms per sample. Comparative studies show that DCAT is more accurate and more efficient compared to state-of-the-art networks, including Transformer, ResNet1D, and AResNet, which substantiate its ability to trade-off discriminative power with resource economy. The suggested model sets a new standard of performance efficiency of underwater acoustic target recognition, which
May 27, 2026 · via nature.com
Social Media Facial Recognition: New Reality Check Before You Trust an Online Match Meeting people online is now the norm. A little over a decade ago, if you said you met someone online, eyebrows would be raised.How I Met Your Mother made a whole joke about it. But since the pandemic, it’s becoming the go-to option (for better or worse). Yet that’s created a new problem - how do you even know the person you’re talking to is real? Fake profiles, stolen photos, and now AI images are increasingly common. Whether it’s catfishing or a romance scam, you’ve got to tread carefully in the world of online dating. That’s where social media facial recognition comes in. You can submit a photo and find out if the person you’re talking to has a verifiable social media presence. Or whether something doesn’t quite add up. Why Trusting Online Profiles Is Getting Harder Been burned by an online profile? You’re not alone. As many as 18% of online daters have been catfished, according to a 2023 study, with millennials accounting for 45% of reported victims. Little wonder people are turning to social media face search as a potential solution. So, what are the problems? Well, they boil down to three issues: - AI-generated faces - Stolen images - Carefully built fake personas Profiles can look fine at a glance. But dig a little deeper, and there’s nobody behind the profile. It’s all smoke and mirrors. Worse still, you might find the same set of photos used by multiple accounts, each as part of some scam. What Is Social Media Facial Recognition? Social media facial recognition is a tool that lets you find a social media profile based on an uploaded photo. Platforms like Face2social scan across multiple social media networks to identify matching
May 26, 2026 · via jsonline.com
Is it really the “happiest place on Earth”? A new proposed class action lawsuit accuses the Walt Disney Company of violating privacy, unfair competition, and consumer protection laws by using facial recognition technology at Disneyland park entrances to verify tickets. The proposed class action seeks at least $5 million in damages and a court order requiring Disney to obtain written consent before using the technology. How Does Disney Use Biometric Data? In April, Disney implemented facial recognition at the entrances to Disneyland and its sister park, Disney California Adventure (aka where you go for Radiator Springs Racers). Disney takes photographs of guests’ faces and compares them with images that were taken when they first used their annual passes or tickets. Disney has said that this makes entering and reentering the park easier and helps prevent fraud. There are signs posted at four entrances indicating that visitors can avoid the technology by using separate non-biometric entry lanes. But critics say these signs are easy to miss, and most guests opt to have their faces scanned. Disney has said publicly that the biometric information it collects at Disneyland entrances is deleted within 30 days, unless it’s retained for legal or fraud-prevention purposes. The Complaint The complaint was filed in the U.S. District Court for the Southern District of New York on May 15, on behalf of a woman named Summer Christine Duffield. Duffield lives in Riverside County and visited Disneyland with her kids. The complaint alleges that Disney “does not adequately disclose the use of their biometric collection, so consumers — which almost always include children — have no idea that Disney is collecting this highly sensitive data.” The lawsuit argues that posting signs telling people they can skip the scan is not the same as giving meaningful notice. Instead, the complaint
May 26, 2026 · via findlaw.com
Biometric face morph attack detection breakthroughs offer border security hope Morphing attack detection (MAD) was a major theme of the European Association for Biometrics’ (EAB’s) workshop on live enrollment last year, and as AI makes sophisticated biometric spoof attacks more inexpensive and widely available, the subject has graduated to a full multi-day examination. Dr. Annalisa Franco of Italy’s University of Bologna hosted the first half of a two-day workshop on the state of the art and outlook for biometric face morphing on Tuesday. Morphs and facial recognition improve with training, but not border guards Face morphing attack image creation has evolved from landmark warping to diffusion synthesis, Kiran Raja of the Norwegian University of Science and Technology (NTNU) explained to open the workshop. Landmark-based approaches using Delaunay Triangulation and Affine transformations can leave behind artifacts that are visible on close inspection. Post-processing can clean these up, but only to a certain extent. GANs have similar drawbacks, but Raja and his research associates have found that attackers can use diffusion models to generate attack images that do not have the same flaws. Diffusion morphs are not perfect, but they are the most difficult to detect, reaching up to 99.8 percent in Raja’s tests, and therefore should be included in training data. Raja went on to describe different morph attack image creation techniques and their relative effectiveness. David Robertson of the University of Strathclyde in Scotland introduced the concept of familiar or unfamiliar face recognition. These terms describe how people can identify the same person in widely varying photos, if they know them, and yet fail at the much simpler task of matching a person standing in front of them to, or differentiating them from, a photo. He also shared the results of a study which showed that training people on what
May 26, 2026 · via biometricupdate.com
Nevada facial recognition project draws scrutiny over privacy, police oversight The Sparks, Nevada Police Department is moving forward with a federal grant-funded facial recognition project officials say will help investigators identify suspects in retail theft cases, but which is drawing scrutiny because of its regional structure, use of police image databases, and a recent Reno wrongful arrest lawsuit involving similar technology. The Sparks City Council approved acceptance of a $16,172.36 grant from the U.S. Department of Justice (DoJ) Office of Justice Programs Bureau of Justice Assistance and administered by the Nevada Department of Public Safety’s Office of Criminal Justice Assistance, which received a $2.1 million block grant from DoJ. The project is intended to support facial recognition investigative tools, contractual services, and coordination among the Sparks Police Department, Reno Police Department, and the Washoe County Sheriff’s Office through a regional Real-Time Information Center. The project period runs from April 1 through Aug. 31, 2026, and city staff materials say the software would allow analysts to compare images and video evidence against databases, generate investigative leads, and improve coordination across jurisdictions. Sparks is not simply buying a stand-alone tool for one police department. The project is structured around shared investigative use by multiple Northern Nevada agencies, which means questions about access, auditing, retention, training, and permissible use will not be confined to Sparks alone. The software at issue is from Greenville, South Carolina-based DataWorks Plus and will be used by a small number of crime analysts to compare images or video from crime scenes against local police databases. DataWorks provides mugshot management, booking, biometric identity, rapid ID, and facial comparison tools for police, corrections, and public safety agencies. Detroit police used DataWorks facial recognition in cases that produced several widely reported wrongful arrests. In one case, police used a blurry surveillance
May 26, 2026 · via biometricupdate.com
Facial recognition van catches wanted man at Luton carnival
Vans were set up at the entrances to Wardown Park, and caught a man who was wanted for sexual assault.
Officers made arrests for possession of a knife and possession with intent to supply drugs.
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Hide AdTwo teenagers were spotted riding e-scooters while wearing balaclavas, hoodies, and surgical gloves, during the blazing heat. Both were arrested for attempted robbery and their e-scooters were seized.
Three more teenagers were arrested for affray and one person was arrested after failing to appear in court. A total of nine were arrested at the event.
Superintendent Hob Hoque said: “The past week and bank holiday weekend have been an extremely busy one for the force. Our officers have attended a range of different incidents, alongside helping keep the public safe during one of the major events of the year, Luton carnival.”
May 26, 2026 · via lutontoday.co.uk
Apple Introduced Its Apple Intelligence Accessibility Upgrades Edited by Adam Harrie — May 26, 2026 — Tech This article was written with the assistance of AI. Apple introduced a new wave of Apple Intelligence-powered accessibility features that bring on-device AI enhancements to tools including VoiceOver, Magnifier, Voice Control and Reader. The updates add richer contextual assistance through features like Image Explorer for detailed screen descriptions, Live Recognition accessible through the iPhone Action button and natural-language navigation that lets users control devices by describing what they see on-screen. The rollout also includes automatic on-device caption generation for uncaptioned videos and streams, upgraded Reader support for navigating complex documents and expanded communication tools such as ASL interpreter support in FaceTime and smoother Made for iPhone hearing-aid handoffs. Apple Vision Pro also gained eye-tracking controls that enable some power wheelchair users to steer mobility devices in controlled environments with reduced calibration requirements. For users with vision, hearing and mobility challenges, the features create more conversational and context-aware interactions while preserving privacy through local AI processing. The updates reflect Apple’s broader push toward adaptive, real-time accessibility experiences powered by on-device intelligence. Image Credit: Apple The rollout also includes automatic on-device caption generation for uncaptioned videos and streams, upgraded Reader support for navigating complex documents and expanded communication tools such as ASL interpreter support in FaceTime and smoother Made for iPhone hearing-aid handoffs. Apple Vision Pro also gained eye-tracking controls that enable some power wheelchair users to steer mobility devices in controlled environments with reduced calibration requirements. For users with vision, hearing and mobility challenges, the features create more conversational and context-aware interactions while preserving privacy through local AI processing. The updates reflect Apple’s broader push toward adaptive, real-time accessibility experiences powered by on-device intelligence. Image Credit: Apple Which AI accessibility features would you actually
May 26, 2026 · via trendhunter.com
A new bill that prohibits the collection, use and sale of biometric identifier information in commercial settings in Erie County has been signed into law. The county is the first in New York to enact such a law. Erie County Executive Mark Poloncarz signed the "Biometric Transparency and Privacy Act," saying it is intended to "promote transparency and protect the public." "This law creates a safer community for all by protecting a person's most basic and unique features - their face and biometric data," Poloncarz said in a statement. "Along with our legislature, our administration was able to come up with a local law that we believe is one of the strongest in the country. It is something we are very proud of because we believe it is going to be the standard going forward." This comes after Wegmans recently said some stores are using the technology to help with misconduct and retail theft, and that it doesn't collect other biometric data and disposes of the images and video after security purposes are fulfilled. Democratic Legislator Lawrence Dupre said that he first proposed the legislation to make any retailer using the technology more transparent. "You can reset a password. You cannot reset your face," said Dupre. "Your face is yours. It is not a data point for a corporation to collect and sell. As of today, that practice is banned in Erie County. This law does not ban security cameras. It does not ban loss prevention. The line it draws is between a security camera and a biometric database. A store can record video for security. What it cannot do is run facial recognition software to build a profile of every customer who walks through the door." According to the law, companies and businesses found in violation could face fines
May 26, 2026 · via spectrumlocalnews.com
The integration connects AI-powered image recognition from the store floor directly into Pitcher's commercial workflows, giving field teams the visibility and direction needed to win at retail. DENVER, May 26, 2026 /PRNewswire/ -- Pitcher, the AI-native sales enablement platform for enterprise commercial teams, today announced a strategic partnership with EasyPicky, a specialist in retail execution optimization and field data collection for consumer goods companies. The partnership brings together two platforms already trusted by leading CPG manufacturers, including Mondelēz International, one of the world's largest snack companies and the makers of globally recognized brands like Oreo and Cadbury. "The strategic alignment of Pitcher and EasyPicky represents a powerful convergence of two critical capabilities: meaningful sales representative engagement with store managers and the precise execution and validation of in-store display standards for merchandising teams," said Rensilin Pathrose, Senior Director of Digital Experience, Digital Business Transformation & Digital Commerce at Mondelēz International. "Together, this integration bridges the gap between sales and shelf-level compliance, delivering end-to-end visibility across the retail execution lifecycle." EasyPicky gives field teams instant visibility into shelf conditions, from product availability to out-of-stocks, merchandising compliance, and display placement — all captured via a short smartphone video, even offline. That intelligence now flows directly into Pitcher, where it becomes the foundation for Next Best Action (NBA) recommendations, prioritized visit planning, and real-time commercial guidance. This empowers commercial leadership to replace field rep guesswork with data-driven decision-making at scale, impacting store visits, display negotiation, and on-shelf outcomes. Connecting Strategy to Field Performance The new partnership solves a common challenge across CPG companies: turning Perfect Store data into real-time action that reps can take to capitalize on in-store opportunities and capture lost revenue. Both platforms are designed for field realities: offline-capable, mobile-first, and built to work in environments where connectivity is unpredictable and every
May 26, 2026 · via prnewswire.com
The longest whale journey ever recorded links Australia to Brazil An international team has documented humpback whales making record-breaking crossings between eastern Australia and Brazil, with one individual confirmed travelling 15,100 kilometres - the longest movement ever recorded for the species. An international research team has documented humpback whales travelling more than 14,000 kilometres across open ocean, crossing between breeding populations in eastern Australia and Brazil. The findings, published in Royal Society Open Science, represent the longest confirmed movements ever recorded for the species. The breakthrough was made possible by comparing tens of thousands of photographs of whale flukes – the distinctive tail markings that act as a natural fingerprint for individual animals. Drawing on a dataset of 19,283 high-quality fluke images collected between 1984 and 2025 from eastern Australia and Latin America, the team used automated image-recognition software to identify potential matches before independently verifying each one by eye. The photographs were contributed by both professional scientists and citizen scientists via the global platform Happywhale. From nearly 20,000 individual whales spanning more than four decades of data, two animals emerged as having crossed between the two regions – a figure representing just 0.01% of identified individuals. The first whale was photographed in Hervey Bay, Queensland in 2007, resighted in the same area in 2013, and then recorded off the coast of São Paulo, Brazil in 2019. The straight-line ocean distance between those two breeding grounds is approximately 14,200 kilometres – roughly equivalent to the distance from Sydney to London. The second case involved a whale first photographed in 2003 at the Abrolhos Bank, Brazil’s primary humpback nursery off the coast of Bahia, within a boisterous group of nine adults. Some 22 years later – in September 2025 – the same animal was spotted alone in Hervey Bay, Australia, marking
May 26, 2026 · via oceanographicmagazine.com
Is Neuro-Symbolic AI (NSAI) more suitable for Indian education? Read here to understand its advantages for Indian Education. Neuro-Symbolic Artificial Intelligence (NSAI) is a hybrid AI framework that combines the strengths of neural networks (learning from data) and symbolic reasoning systems (rule-based logic). It aims to create AI systems that are not only intelligent but also explainable, reliable, and context-aware. Traditional AI models such as Large Language Models (LLMs) largely depend on statistical prediction, whereas NSAI integrates reasoning and knowledge structures with learning capabilities. Is Neuro-symbolic AI more suitable for the Indian education system? What is Neuro-Symbolic AI? NSAI merges two complementary AI approaches: - Neural Component (Learning/Perception) The neural network component handles: - Pattern recognition - Speech processing - Image recognition - Language understanding - Handling unstructured data Examples: - Understanding handwritten answers - Identifying speech in Hindi, Tamil, Bengali, or Odia - Recognising diagrams or visual inputs This acts as the “eyes and ears” of the system. - Symbolic Component (Reasoning) The symbolic system works using: - Explicit logical rules - Knowledge graphs - Ontologies - Human-readable reasoning pathways Examples: - Mathematical formulas - Grammar rules - Scientific principles - NCERT curriculum concepts This acts as the “brain” of the system. Working Mechanism Input: Neural network processes information – Converts into symbols – Symbolic engine applies rules – Generates fact-based output. Example: A student asks: “Why does an object fall to the ground?” Traditional LLM response: May generate an answer from statistical patterns and occasionally produce incorrect details. NSAI response: - Recognises the question - Maps it to the Newtonian mechanics knowledge graph - Applies symbolic laws of gravity - Produces a verified explanation Limitations of Traditional LLMs in Indian Education Infrastructure mismatch: Large AI models require: - Massive GPUs - Data centers - High electricity consumption -
May 26, 2026 · via clearias.com
The findings set new records for the greatest distances ever confirmed between sightings of individual humpback whales anywhere in the world. “Discoveries like this are only possible because of investment into long-term multi-decadal research programs and international collaboration,” Griffith University Ph.D. Candidate and co-author Stephanie Stack said. “These whales were photographed decades apart, by different people, in opposite parts of the world, separated by two different oceans, and yet we can connect their journey.” By comparing tens of thousands of photographs of whale tails, also known as “flukes”, the team identified two individual whales that had been photographed in both eastern Australia and Brazil. One whale was first photographed in Hervey Bay, Queensland, in 2007, and was seen again in the same area in 2013 before turning up off the coast of São Paulo, Brazil, in 2019. These two breeding grounds are separated by a minimum straight-line ocean distance of about 14,200 km—roughly the distance from Sydney to London. Because only the start and end points of the whale’s journey were documented, the actual route taken, and therefore the true distance swum, remains unknown. The other whale was first photographed in 2003 at the Abrolhos Bank—Brazil’s main humpback whale nursery off the coast of Bahia—in a large, boisterous group of nine adults. Twenty-two years later, in September 2025, it was spotted alone in Hervey Bay, Australia, representing a travel distance of 15,100 km, making this the longest distance ever documented between sightings of the same individual humpback whale on record. The study drew on 19,283 high-quality fluke photographs collected between 1984 and 2025 from eastern Australia and Latin America, contributed by both scientists and citizen scientists through the global platform Happywhale. By running these photographs through an automated image-recognition algorithm and then independently verifying every potential match by eye, the
May 26, 2026 · via ecomagazine.com
Police deploy face tech in response to beach party - Published Adverts for an unofficial beach party on social media have prompted the police to deploy live facial recognition technology. "Significant numbers of young people" are expected to travel to Southend-on-Sea on Tuesday and gather by the seafront, Essex Police said. Flyers promoting the event online encouraged attendees to bring their own drinks and indicated that drugs could be available. A police spokesman said: "Anyone coming here intending to commit crime will be dealt with swiftly and robustly." It followed a busy Bank Holiday weekend when thousands of people visited the seaside city in Essex. The beach party has been advertised online as both the "Southend Takedown" and the "32C Southend Beach Step". Nitrous oxide and marijuana were also promoted as potentially available, although one flyer told people to create "no problems". Police are expected to have a highly visible presence at the city's railway stations, seafront and High Street throughout the day. They have imposed a dispersal order across the whole of the district until Thursday morning and been given extra stop and search powers. "We expect the vast majority of people to enjoy the seafront responsibly," the spokesman said. "However, those who do not should expect to be identified, stopped and, where appropriate, arrested." Ten people were sentenced in 2025 after a similar "beach rave" led to violence erupting between "two rival gangs" on the seafront the year before. The defendants, aged between 15 and 19, were given prison terms of up to eight years at Basildon Crown Court. Do you have a story suggestion for Essex? Contact us below. Get in touch Your Voice Follow Essex news on BBC Sounds, Facebook, external, Instagram, external and X, external. Related topics - Published16 July 2025 - Published2 August 2024
May 26, 2026 · via bbc.co.uk
Digital dragnet: When images online destroy lives Public wanted notices are increasingly used for trivial cases. Experts warn of disproportionate infringements of fundamental rights and call for reform. It sounds like an absurd joke from the digital world, but in November 2025 it was bitter reality on the website of the tabloid newspaper „Berliner Zeitung“. Under an official police wanted poster showing a young man in a drugstore, the headline proclaimed that a Pokémon card thief was being sought. Because the fan did not pay the nearly 10 euros for one of the coveted mini tin boxes in Brandenburg, the police resorted to a sharp sword of law enforcement: public wanted notices via the press. In a post for the Grundrechte-Report 2026 (Basic Rights Report 2026), which Netzpolitik.org published upon the release of the "alternative report on the protection of the constitution", aspiring legal scholar Athena Möller puts her finger on the wound. With such minor offenses, she explains, the suspicion arises "that we are dealing with a disproportionate interference with the right to informational self-determination." Publicly branded Similar reports have often been found in the media over the past few months. The co-editor of the volume warns that this should not only alarm data protection advocates. The spectrum of people who could suddenly find themselves in the digital spotlight without their consent is broad. It ranges from witnesses and missing persons to suspects, among whom there are always wrongly accused individuals. For example, in February, the Magdeburg police searched for a man who had pocketed a lost wallet in a supermarket using press appeals. As it turned out, he was an honest finder: the wallet had long been back in the hands of its rightful owner by the time the search began. Nevertheless, the high-resolution photos of the wrongly
May 25, 2026 · via heise.de
Vadzo Imaging Explains V4L2 Driver Development for Embedded Linux MIPI CSI-2 Camera Integration V4L2 driver development for MIPI CSI-2 sensors demands accurate device tree configuration, sensor subdevice registration, and media controller pipeline setup before a single frame reaches the application. Vadzo Imaging's Bolt MIPI CSI-2 camera series - the BOLT 234CGS AR0234 Color Global Shutter MIPI Camera, BOLT 544CRS AR0544 HyperLux Color MIPI Camera, BOLT 900MGS IMX900 Monochrome Global Shutter MIPI Camera, and BOLT 1335CRS AR1335 Fixed Focus 4K MIPI Camera gives embedded engineers pre-validated hardware with Linux kernel driver support confirmed on Raspberry Pi, NVIDIA Jetson, and NXP i.MX platforms. FORT WORTH, Texas, May 25, 2026 (Newswire.com) - Vadzo Imaging, a provider of embedded vision cameras for OEMs and system integrators, today publishes a technical guide addressing V4L2 driver development for embedded Linux MIPI CSI-2 camera integration. The guide covers the full MIPI CSI-2 camera driver stack from kernel driver structure and device tree configuration through sensor subdevice registration in the Linux camera subsystem and the V4L2 MIPI camera integration sequence required across Raspberry Pi V4L2 driver, NVIDIA Jetson camera integration, and NXP i.MX camera integration platforms. Vadzo's Bolt MIPI CSI-2 camera series supports this workflow directly: every camera in the Bolt series ships with module-level Linux kernel driver packages verified on the platforms covered, giving embedded engineers a confirmed starting point for V4L2 driver development. V4L2 Driver Development for MIPI CSI-2 Cameras Requires More Than a Generic Kernel Driver MIPI CSI-2 camera integration in embedded Linux operates across three layers that must all be correct before the V4L2 camera driver delivers frames to the application: the sensor subdevice driver handling register initialization and mode switching through the V4L2 subdev API, the device tree configuration describing MIPI lane count, polarity, and link frequency for both the sensor node and
May 25, 2026 · via newswire.com
BuzzFeed GamesIf You Can Solve This Color Puzzle In Less Than 3 Minutes, You Have Perfect Color VisionHuedoku #29! New week, new puzzle, same zero mercy. 🎨💀Posted 6 hours agocommentFacebookPinterestLinkby Crystal RoBuzzFeedBuzzFeed StaffHi, I’m Crystal, a Senior Editor based in Los Angeles and creator of BuzzFeed’s “That Got Dark” newsletter. Huedoku is a daily color puzzle with simple rules and a satisfying solve. It's like sudoku, but with colors instead of numbers. Sign up here to get notified every time we publish a new Huedoku! Come back tomorrow for Huedoku #30 — and share your score to challenge a friend! 🌈 🌈 New Huedoku drops every weekday at 4:00 a.m. PT / 7:00 a.m. ET. 🧩🗂️ Huedoku Archive — Every past puzzle, all in one place! Comments
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May 25, 2026 · via buzzfeed.com
AI slop is a real and present danger. As a writer and editor, I don't see myself using AI detection tools at every turn of the syllable. Instead, I am trying to train my eye to spot AI-generated content. It's still easy to spot deepfakes, but the written word is getting tougher to nail down. Wikipedia offers some help. Its volunteer editors, the army who obsessively fight for knowledge, have quietly built the most evidence-based AI guide on the internet. Wikipedia's Signs of AI Writing page isn't an app or a checklist. It's just a simple page, meant primarily for Wikipedia's own articles written in wikitext. But even outside the encyclopedia, it might help you eyeball the next piece of AI writing you come across. This AI App Will Help You Prove You Didn’t Use AI to Write Your Paper This app will help prove that you didn't cheat. Wikipedia built a handy AI detection field guide No app needed — just pattern recognition Wikipedia's Signs of AI Writing page started as an internal resource for volunteer editors. Since 2023, a group called WikiProject AI Cleanup has been reviewing new submissions for undisclosed AI-generated content. After combing through thousands of flagged articles, they cataloged the patterns they kept seeing in Wikipedia drafts and edits. The result is what Wikipedia says, that it's what the editors have observed, and it's more "signs" than "rules." The page is worth a bookmark and a deep read. Instead of depending on AI writing detectors, it will help you spot-check writing behaviors. Those are the telltale giveaways of AI writing. As we all know, LLMs are just machines, and they are built on statistical probability, not on real storytelling skills. When I first came across the page, I expected a basic checklist. What I found
May 25, 2026 · via makeuseof.com
IRS proposal could turn taxpayer facial verification into long-term fraud database The Internal Revenue Service (IRS) is considering a proposal that would authorize ID.me to retain taxpayers’ biometric data for years, a change that would deepen the role of facial recognition in federal tax administration and revive privacy concerns that forced the IRS to retreat from a similar controversy four years ago. Under the proposal, biometric scans collected during identity verification for IRS.gov accounts could be kept by ID.me for as long as an account remains active and then for up to 36 months after the account is deleted. The retained data could be accessed by government officials only as part of law enforcement or IRS inspector general investigations and through legal process. The proposal reflects a growing concern inside the federal government that identity fraud is becoming harder to detect as criminals use stolen personal information, synthetic, and AI-generated images to impersonate taxpayers. The proposed action has raised questions about how much biometric information Americans should be expected to give a private contractor to access government services online. ID.me says biometric retention depends on the customer agency and that some customers require biometric information to be purged within 24 hours after a successful verification, while others require longer retention. The company says it will not retain biometric information for more than 36 months unless there is a subpoena, warrant, or other legally compelling justification. The new IRS proposal would move the agency toward the longer end of that retention model. ID.me’s public privacy policy, updated May 7, says personal information provided in connection with a public sector agency verification may be retained for up to three years after account closure unless regulations require a shorter period. The policy also says ID.me may retain data tied to high-risk transactions, particularly
May 25, 2026 · via biometricupdate.com