Rather than type in a password or PIN countless times daily, smartphone users turn to biometrics for device unlock. Your face and fingerprint are unique to you and are generally difficult to replicate, making these kinds of biometric security both convenient and safe. However, biometric sensors aren't all equal — some are easier to trick than others, making them less secure. Facial recognition is notoriously hard for smartphone manufacturers to implement without a dedicated depth sensor. A single camera usually isn't enough, which is why Apple's camera cutout for the Face ID sensors on iPhones is shaped like an oval rather than a circle. Adding a secondary sensor, like an infrared camera, flood illuminator, dot projector, or iris scanner, can elevate a facial recognition suite's accuracy and make it harder to thwart. This is crucial on the Android side of things, because Google splits biometric sensors into three groups: Class 1 (formerly Convenience), Class 2 (formerly Weak), and Class 3 (formerly Strong). Only a Class 3 biometric can allow access to banking and payment apps, as well as other sensitive data. Today, the only phone brand in the U.S. with a Class 3 facial recognition system is Google Pixel. Samsung had, then removed, a Class 3 face unlock feature from Galaxy phones, and this is the reason why. These Android features make your phone a nightmare to steal — I enable them all Your phone is easier to steal than you think—these Android features quietly flip the odds. The three levels of Android biometrics security Most users don't know about this critical biometric standard Android phones commonly offer both a fingerprint and face unlock feature. Fingerprint sensors on Android phones are either capacitive, optical, or ultrasonic, and all three sensor types can meet the Class 3 biometric standard. So, you've
Apr 27, 2026 · via makeuseof.com
Accelerating the next-generation AR glasses experience with a gaze-controlled UI and ultra-lightweight form factor TOKYO, April 27, 2026 /PRNewswire/ -- Cellid Inc., a developer of displays and spatial recognition engines for next-generation AR glasses, today announced that it has supplied its latest waveguide (AR glass lens) for the next-generation AI smart glasses "J9," developed by Jorjin Technologies Inc., a premier AR/XR platform solution provider dedicated to wearable innovation for decades. This product is scheduled for public announcement in Q2 2026, and its reference design for evaluation is available now. In Japan, Cellid will serve as the authorized distributor. Cellid has established a strong track record through its collaboration with the Foxconn Group on the development of next-generation waveguides. For this model, the "J9," Jorjin and Cellid have combined their world-class development and manufacturing capabilities. Leveraging their experience in mass production, they aim to further accelerate the transition of AR glasses into the phase of widespread real-world adoption. An intuitive user experience enabled by the "J9" eye-tracking UI The J9 features a "Gaze-Controlled UI," enabling users to complete all interface operations using only their eyes. With a hands-free, voice-free "Look. Select. Done." Interaction model, users can easily perform a wide range of tasks, including taking photos, recording videos, navigating form screens, and adjusting brightness. Key Features of "J9" - Equipped with Cellid's ultra-thin waveguide: The ultra-thin, high-brightness glass waveguide achieves a thickness comparable to standard eyeglass lenses. - Gaze-controlled UI: Enables hands-free and voice-free operation—users can take photos and control the interface simply by looking. - Built-in high-precision eye tracking: Uses two compact cameras and infrared LEDs to detect gaze with approximately 3-degree accuracy. - Full-color display on the lens: Projects full-color images (500 × 380 pixels) directly into the user's field of view with a 25° FOV. - High-performance processor
Apr 27, 2026 · via prnewswire.com
Disneyland is allowing guests to opt out of its new facial recognition system when entering its theme parks in California. This week, the resort rolled out facial recognition software combined with biometric technology at the front entrances of Disneyland and Disney California Adventure following limited tests over the past few months. According to the Disney Experiences website, the facial recognition software uses images of guests' faces taken by at a camera at the entrance and the image of their faces that was saved when they first used the ticket or pass. The software utilises biometric technology to convert those images into unique numerical values, which are compared to find a match. Except in cases where data needs to be maintained for legal or fraud-prevention purposes, Disneyland deletes all numerical values within 30 days of creation, the website says. Alternative entrances for guests For guests who "do not wish to use this service", entrance lanes that do not employ facial recognition technology are available. Guests who would prefer not to participate can enter through the parks' main entrances located along the Esplanade and choose an entrance lane with overhead signage showing a person with a diagonal strikethrough. "When using these entrance lanes, you may still have your image taken. However, these lanes will not utilize biometric technology on your image. Instead, a cast member will manually validate your ticket," the website says. Regarding the new facial recognition software, it says: "The security, integrity and confidentiality of your information are extremely important to us. "We have implemented technical, administrative and physical security measures that are designed to protect guest information from unauthorized access, disclosure, use and modification." It adds: "From time to time, we review our security procedures to consider new technology and methods, as appropriate. "Please be aware that, despite our
Apr 27, 2026 · via blooloop.com
Meta's New Smart Glasses Feature Could Be A Privacy Nightmare, According To Advocates Meta has been trying to work facial recognition systems into its social media environment for what seems like forever. Not only is the company planning to add this feature to its line of smart glasses, but The New York Times got its hands on an internal memo about how the project carries "safety and privacy risks." On April 13, the ACLU sent a letter to Mark Zuckerberg, claiming the upcoming facial recognition system, dubbed "Name Tag," poses a threat to "vulnerable communities." These include religious minorities, people of color, LGBTQ+ people, and survivors of stalking and sexual harassment. In fact, anyone with an online presence (which is basically everyone) is vulnerable, from children to the CEOs of major companies. The ACLU is concerned that since the smart glasses look like your run-of-the-mill prescription glasses, users could "surveil and profile" everyone they see covertly to "identify and stalk" potential victims. The organization is also concerned that members of police forces could wear the smart glasses and use Name Tag to violate the Fourth Amendment. The letter cites a 2024 incident where Harvard students used smart glasses equipped with facial recognition software to "identify strangers on the Boston subway in real time," as well as studies that demonstrate attacks (physical and otherwise) against members of the LGBTQ+ community have increased in recent years. Name Tag is a definite concern. Luckily, there are glasses with specialized lenses that fool facial recognition software and apps that act as anti-smart glasses radar to help combat such features. Meta couldn't have picked a worse time, and it did so intentionally When a company discusses such matters as "safety and privacy risks," it's usually under the purview of how to minimize them. That's certainly
Apr 26, 2026 · via bgr.com
On first glance, scammy dating profiles have nothing but green flags. They're verified accounts, often posing as handsome men in their 40s. Their photos tell the story of a laid-back, yet exciting life — gym selfies, beach trips, a snowy hike in the Alps — except for the very last picture. It's not a photo at all, but an illustration, clearly AI-generated, depicting a totally different person's face pasted onto a billboard, a bobble head, an anime character, or an oil painting. One weird picture might not be enough to raise alarm bells (seasoned swipers have seen much worse on the apps), but, as journalist Christophe Haubursin uncovered, it is a surefire sign of a romance scammer. And if you're not careful, they can drain your wallet before you go on one coffee date (1). How the scam works Haubursin, a former Vox journalist and now independent YouTube creator, first heard about the issue when a friend showed him screenshots of strange Tinder matches. All the accounts were verified, and they all seemed totally normal — except for the AI images at the end. She wondered if this was some kind of subtle signal. Could these people be in a secret society? It was nothing so romantic as that. Haubursin figured out that, once you chat with one of these users, they quickly try to move the conversations to WhatsApp and steer the topic to cryptocurrency. They eventually pressure their would-be sweethearts to urgently send money. It's obvious scammer behavior. So what's with the odd images? They're a way to get around security features like Tinder's Face Check. To get a "verified" badge on a dating app, you need to take a video of your face from several angles, much like you would do to set up FaceID on an
Apr 26, 2026 · via moneywise.com
We’ve all been there — you’re patiently waiting for the people in front of you to hop on the ride, but then the seatbelt check takes forever! The good news is, Disney just filed a patent to fix that. In theory, they wouldn’t even need ride operators to check the seatbelts and lap bars in the first place! If it’s implemented, ride loading times and overall throughput could decrease dramatically. The patent is for a new AI system that uses cameras and machine learning to verify that ride restraints are properly secured before a vehicle dispatches. It works by capturing continuous video of each passenger seat during the loading process. A restraint verification platform analyzes footage using multiple machine learning models trained to detect the passenger’s body position and size, the restraint type, and whether the restraint is correctly securing the passenger. While the use of AI for something so safety-critical might sound scary, it could detect scenarios that human operators might miss. The patent mentions scenarios where a rider may be sitting on top of a seat belt instead of beneath it, or when the belt is intentionally extended beyond its proper length to create a false sense of it being tightly secured. The system combines video analytics with data from current sensors, notably seat sensors that detect whether a guest is seated, clasping sensors that confirm whether a restraint is locked, and rotary encoder devices that measure the physical length of the seat belt extended. Right now, ride operators rely on a combination of manual visual checks and basic sensor data, which can’t detect all improper restraint situations that the new system would. The patent notes that restraint inspection is “time-consuming due to the number of passengers and seat belts to inspect and/or due to the level of
Apr 26, 2026 · via allears.net
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Apr 26, 2026 · via swoknews.com
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Apr 26, 2026 · via youtube.com
ADVP and NO2ID back DVS framework from opposing perspectives The UK’s Digital Verification Service (DVS) trust framework is drawing support from both industry and long-time critics of centralized identity — a convergence explored in the latest episode of the Biometric Update Podcast. David Crack, chair of the Association of Document Verification Professionals (ADVP) has been busy advocating for providers verified under the Digital Verification Service (DVS) trust framework, but credits for the whole scheme to someone who’s now on his second generation of digital identity debate (at least). Phil Booth is the national coordinator of the NO2ID campaign. “I’m going to embarrass Phil now,” Crack says, “because the reason for the DVS sector existing, and the reason why this whole industry has come about, is because of Phil, and the campaign that he did back under the Tony Blair government.” Indeed, NO2ID argues that the kind of centralized national digital identity scheme that the former UK prime minister and his namesake institute have championed cannot be successful in the UK without creating massive risks to democracy and human rights. Its slogan is “stop the database state.” Booth says “the whole premise of these centralized systems that we see, not just in the UK, but all around the world, is this sort of ‘one ring to rule them all’ type thinking, which has and does play out badly – maybe not for everyone, but for many people and many groups and for many reasons.” On the other hand, “we understand that we live in a world in which we need to prove all sorts of things about ourselves to various levels of assurance when and where appropriate, and to do it in hopefully a minimally disclosive way – but the crucial thing being that we, the citizens of the individual, are
Apr 26, 2026 · via biometricupdate.com
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Apr 26, 2026 · via the-sun.com
If You Can See The Baby In This Image, You Have A Subtle Perception Skill Most People Lack Do you ever notice that you can see shapes in clouds and tree branches? Do you wonder if other people are seeing the same thing you are? Be honest: what do you see when you look at the photo below? The visual puzzle challenges people to spot a hidden baby in an image, something not everyone can immediately see. Those who do tend to have strong pattern-recognition and subtle-perception skills, allowing them to pick up on visual cues that others might overlook. The illusion highlights how differently people process the same information, suggesting that noticing hidden details can be a sign of sharper observational awareness and cognitive flexibility. If you can see a baby in this image, you have a subtle perception skill most people lack: Cambridge University Is it just a few random blotches on a page, or can you see something more substantial, such as a building, an animal, or a child? Now, look at this picture. If you look at the blotchy picture next to the picture of the baby, can you start to see the baby in the blotchy picture? If you can see the baby, it could also mean that you're prone to hallucinations and possibly psychosis But before you start to question your mental health, seeing the baby in the blotchy picture isn't necessarily a bad thing. Most people construct a picture of the world using experience, expectation, and context. Most of the time, that's a feature, not a flaw. It's this ability that researchers believe can help explain why some people are susceptible to hallucinations that are often associated with psychotic disorders, and that it's a natural process of the brain making sense of the
Apr 25, 2026 · via yourtango.com
Woman and child die after getting into difficulty in water
A woman and child believed to be mother and son have died after getting into difficulty in water at a west London park.
The Metropolitan Police said despite the efforts of emergency services called to Elthorne Park in Ealing on Saturday, both were pronounced dead at the scene.
An investigation is under way and the police said "all initial indications are that the circumstances are not suspicious". Officers are working to identify the next of kin.
Det Supt Pete Thackray, from the West Area Command Unit, said: "This is a tragic incident in which a woman and her young child have lost their lives. Our thoughts are with their loved ones."
"I would also like to acknowledge the efforts of the first responders and members of the public who did their very best in an incredibly challenging situation.
"While an investigation into what took place is under way, all initial indications are that the circumstances are not suspicious."
The park leads on to the Grand Union Canal Walk and is bordered by the River Brent, a tributary of the River Thames.
Apr 25, 2026 · via bbc.com
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Apr 25, 2026 · via hackernoon.com
Abstract This study proposes an automated defect detection system for large-scale fudge production, addressing the limitations of manual inspection, which is both labor-intensive and error-prone. Deep learning-based image recognition was employed to classify normal samples and four defect types using multiple object detection models, including SSD and YOLOv4/YOLOv5/YOLOv7/YOLOv8/YOLOv11. Instead of relying on a single model, the system integrates a multi-model strategy combining confidence-weighted voting, rule-based selection for specific defects, and Non-Maximum Suppression (NMS), enabling complementary strengths across models and improving robustness. The selected models were deployed in a real-time inspection system equipped with a flipping mechanism that allows each piece of fudge to be inspected on both sides, thereby expanding the coverage of defects. In evaluations using 1,000 real production samples, first-round accuracies were 47.5% (hole), 56.7% (leak), and 60.9% (white). After applying the flipping mechanism for a second inspection, accuracies increased to 75.8%, 83.6%, and 89.3%, respectively, with hole defects showing the largest improvement (28.3%). Our validation-learned fusion achieves 0.995 mAP@0.5 (on par with the best single model) and 0.944 mAP@0.5:0.95, outperforming YOLOv11 and YOLOv5 by + 0.2 and + 2.4 percentage points, respectively; gains are most evident for White defect and Hole defect. These results indicate that combining multi-model detection with dual-side inspection significantly enhances accuracy and enables the reliable screening of defects in real-time production environments. Similar content being viewed by others Acknowledgements The authors would like to express their sincere appreciation to Hsiehlung Electromechanical Technology Co., Ltd. for their valuable contribution and support to this research under Contract No. 111255. Funding This research was supported by the National Science and Technology Council (NSTC) of Taiwan, R.O.C., under Contract No. NSTC 111–2622-E-029–004. Author information Authors and Affiliations Corresponding author Ethics declarations Competing interests The authors declare no competing interests. Additional information Publisher’s note Springer Nature remains neutral
Apr 25, 2026 · via nature.com
The Metropolitan police have launched investigations into hundreds of officers after using an AI tool built by the controversial tech company Palantir to root out rogue cops. The software was deployed by the Met over the course of a week, surveilling staff members using data the force has ready access to, unearthing rule-breaking ranging from work-from-home violations to suspected corruption and even criminal allegations such as rape. The Met said as a result of the software, evidence had been found tying a small number of officers to serious cases of misconduct and criminality, resulting in the arrest of three officers for offences including abuse of authority for sexual purposes, fraud, sexual assault, misconduct in public office and misuse of police systems. According to numbers cited by the Met, corruption was the most consistent offence detected by the AI software, with 98 officers being assessed for misconduct related to “abuse of the IT system that rosters shifts by police officers for personal or financial gain”, while another 500 had received prevention notices in relation to the same offence. The Met said that 42 senior officers, with ranks ranging from chief inspector to chief superintendent, were “being assessed for misconduct for serious noncompliance” for sometimes falsely claiming to have been in the office when they had been working from home or otherwise away from the office for excessive periods of time, when the Met’s guidelines state that in-office attendance cannot dip below 80%. The software also found officers who had failed to state that they were Freemasons – now a declarable interest within the force – with 12 officers under investigation for gross misconduct for keeping their membership of the group private, and a further 30 officers receiving prevention notices for suspected but uncorroborated undeclared membership. The implementation of the software is
Apr 25, 2026 · via theguardian.com
SplitScan: AI Bill Splitter is a mobile-focused utility that uses artificial intelligence to process photographed receipts and automatically divide shared expenses among multiple participants. Users capture an image of a restaurant or group bill, and the system extracts line items to calculate proportional or equal splits based on the context. It is commonly used in social dining, shared housing expenses, and group payments where manual calculation can be time-consuming or error-prone. The tool aims to simplify post-transaction reconciliation by reducing the need for manual itemisation and calculation. From a business perspective, SplitScan reflects a growing category of AI-assisted financial convenience tools that automate small but frequent interpersonal transactions. It leverages image recognition and data extraction to streamline everyday expense management, contributing to broader trends in consumer fintech focused on frictionless payment coordination. Bill Splitting Apps SplitScan AI Bill Splitter Instantly Splits Receipts From A Photo Input Trend Themes - AI Receipt Parsing — Advanced computer vision and NLP that extract line-item details from photographed receipts create opportunities to replace manual bookkeeping for microtransactions. - Contextual Expense Allocation — By understanding who ordered what and the social context, systems that allocate costs proportionally can reshape how shared expenses are recorded and reconciled. - Social Payments Integration — Tightly coupling bill-splitting tools with peer-to-peer payment rails and social contacts opens pathways to seamless multi-party settlement experiences. Industry Implications - Consumer Fintech — Personal finance apps and payment platforms stand to incorporate AI-driven splitters to reduce friction in small-group transactions and increase transactional volume. - Hospitality and Dining — Restaurants and food service providers could leverage receipt-splitting tech to streamline table payments and improve customer throughput during peak periods. - Property Management and Co-living — Shared-housing managers and coliving operators can benefit from automated allocation of recurring shared bills, enabling clearer accounting for
Apr 25, 2026 · via trendhunter.com
Derrick White received a special honor when peers voted him the NBA's Sportsmanship Award winner. NBA players backed White over five finalists, including former Boston Celtics teammate Al Horford, to earn the Joe Dumars Trophy. White discussed the award before Friday's first-round playoff game against the Philadelphia 76ers, via CLNS Media Boston Sports Network. "It’s pretty cool," White said. "I think I’m doing things the right way out there, and I think it’s a pretty cool honor." After the Celtics chose White as their team nominee, a panel of league executives voted him to the final stage. The guard then garnered 77 first-place votes and 113 second-place votes from players. "I don’t know if guys take those votes too seriously or not," White said. "But it was just cool to be nominated and go out there and do the right thing." One of the game's fiercest two-way performers, White balances a competitive mentality with a friendly on-court demeanor. "We have respect for each other," White said. "But at the end of the day, you’re competing. You want to win. So that’s kind of when I’m at my best, is when I’m kind of doing different stuff, like that. And for other people, that doesn’t work, but I feel like it works for me." White followed Jrue Holiday as Boston's second straight Sportsmanship Award winner. The 31-year-old paid respect to his former teammate for setting an example. "I just learned a lot from Jrue," White said. "So, shoutout Jrue." Whire will look to celebrate the achievement by snapping out of his shooting funk. Friday's Game 3 kicks off in Philadelphia at 7 p.m. ET on Prime Video. More NBA: Celtics Announce Interesting Injury Report Heading Into Game 3 Vs. 76ers
Apr 25, 2026 · via nesn.com
If teenagers have a will, they will find a way. In the days following Australia’s social media ban for children under 16, the country’s teenagers immediately worked to circumvent the restrictions on the platforms, which included age verification steps, account renewal, and prevention of registration from underage users. Evelyn, a 14-year-old in New South Wales, told The Washington Post in December 2025, just before the implementation of the ban, she planned to use her mother’s face ID to log in to Snapchat and Instagram. In a Reddit thread on ways to bypass the ban, one user suggested using a printed mesh face mask from Temu to outsmart apps’ facial recognition tools. Others still have tried VPNs that obscure their locations. A new report suggests these efforts are working. In a survey of 1,050 Australians ages 12 to 15 conducted last month, the UK-based suicide prevention organization the Molly Rose Foundation found more than 60% of teens who had social media accounts before the ban still had access to at least one of those platforms. Social media sites including TikTok, YouTube, and Instagram, have retained more than half of their users under 16. About two-thirds of young users say these platforms have taken “no action” to remove or reactive accounts that existed before the restrictions. The survey comes at the heels of the Australian internet regulator calling for an investigation into the five largest social media platforms over potential breaches of the ban. Australia, the first country to implement a widespread social media ban for underage teens, has effectively become the guinea pig for other governments similarly considering hefty restrictions on the platforms. Greece, France, Indonesia, Austria, Spain, and the UK have or are considering similar action, and eight U.S. states are weighing legislation that would put guardrails or ban social
Apr 25, 2026 · via fortune.com
Lubbock records show machete attack preceded rival lover's deadly shooting Court records show a 44-year-old man now charged with murder in a deadly shooting earlier this month had previously admitted to attacking the same man with a machete more than a year ago for dating his ex-girlfriend. Tommy Rios was booked into the Lubbock County Detention Center on a count of murder, which carries a punishment of five years to life in prison. Investigating a deadly shooting near a Lubbock convenience store His arrest stems from a Lubbock Metropolitan Special Crimes Unit investigation that began after Lubbock patrol officers responded to a shots-fired call at a convenience store in the 5800 block of Avenue P and found 37-year-old Jonathan Trevino suffering from a gunshot wound. He was taken to University Medical Center where he died. Investigators obtained video from the store's security cameras, which showed a man armed with a handgun arguing with Trevino, who exited the store. However, the armed man followed Trevino outside the store, continuing to argue with him as he pointed the weapon. The video shows Trevino continued to walk away from the man, who got in front of him. A gunshot erupted and Trevino could be seen falling to the ground, the affidavit states. The gunman ran away and was heard saying, "I'm gonna kill you." Rios was identified as the suspected shooter after investigators sent a still image of the gunman to other officers and to the Texas Department of Public Safety. Two facial recognition programs identified Rios as the person believed to be in the still image and a police officer who recently worked as a jailer also recognized Rios as the suspected shooter. A motive for the shooting was not disclosed in the warrant. However, court records show this is the second
Apr 25, 2026 · via lubbockonline.com
Analýza EUR/USD, GBP/USD, AUD/JPY, USD/JPY podle Elliottovy teorie 3.12.2012
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Apr 25, 2026 · via fxstreet.cz