No-frills tech news

Under-16s to be banned from social media by next spring, Starmer says

Under-16s face social media ban by next spring, but questions remain on how it will workpublished at 18:53 BST 15 June Rachel Flynn Live reporter Under-16s in the UK will be banned from using social media by spring next year, Prime Minister Keir Starmer announced earlier today. It follows a government consultation, in which 89% of 9,499 parents and carers said they strongly supported a legal minimum age for social media access, 88% of which strongly agreed that age should be under-16s. Apps such as Snapchat, TikTok, Youtube, Instagram, Facebook and X will be included in the ban, the government says, but it will not include messaging services WhatsApp and Signal. A lot of the detail about this ban "isn't particularly clear", BBC technology correspondent Chris Vallance says, with no definitive list of what's banned, and what's not. Aliyyah, a 14-year-old from Barnsley, calls the ban "a waste of time" and says "sometimes apps are safe spaces for people". While Sean, a 13-year-old from Wythenshawe, says "it's time they did something about" social media use, calling it a "bad place". Technology minister Liz Kendall described the ban as a "defining moment for our children", and said more details will be set out in the regulations. We're ending our live coverage here, but you can read more about the government's policy in our news story.

Your strong passwords mean nothing if your phone PIN is four digits

Smartphones contain sensitive data, and that's why they are safeguarded with thoughtful security measures. Many flagship devices feature biometric security methods, like a fingerprint scanner or facial recognition support. Some even support extra anti-theft safety measures, like Theft Detection Lock on Android. However, these security measures — and all the precious information your smartphone holds — can be bypassed if your phone's passcode is compromised. It's surprisingly easy to catch a glimpse at someone's phone password, and it's even easier to brute-force short PINs with the right gear. That's why the best way to protect your smartphone data and online accounts is to use a strong device passcode in addition to individual strong site passwords. All your passwords are only as strong as their weakest link, and for most of us, that's our phone. 4 reasons I'm still not giving up my password for passkeys I’ll switch to passkeys eventually, just not before the rough edges disappear. Your phone is probably your master password If you use Apple Passwords or Google Password Manager, it's true Convenience and security are always at odds, and our desire to quickly access our smartphones usually prompts us to create short, memorable passwords. Sometimes, they are easy to guess as a result. It could be a simple pattern, an important date, or the year you were born. Of course, these are poor choices for a secure passcode, as they wouldn't be too hard for someone to figure out using public information. That doesn't stop people from using weak PINs for the sake of convenience. In theory, the smart way to secure your device is to make a strong device passcode, and use biometrics for everyday device unlocking. Reality is much different, as there are plenty of reasons why you might not be able to use

Face2social Launches Social Media Face Search Tool for a New Era of <b>Facial Recognition</b> Discovery

NEW YORK, USA, June 15th, 2026, FinanceWire New platform helps users discover matching public profiles across Instagram, Facebook, TikTok, and X using a single photo NEW YORK, March 12, 2026 — Face2social has announced the launch of its public image search platform, a social media facial recognition tool designed to help users discover matching public profiles across major social networks using only a photo. The platform enables users to upload an image and search for matching faces across public profiles on Instagram, Facebook, TikTok, and X. By focusing specifically on social media platforms, Face2social aims to simplify profile discovery, image reuse detection, and identity verification in an increasingly fragmented online environment. Face2social enables social media profile discovery through image search Face2social enables users to upload a photo and search for matching faces across public profiles on Instagram, Facebook, TikTok, and X. The platform is designed to help users discover profile connections, identify image reuse, and explore publicly available social media accounts associated with a photo. Unlike broader reverse image search tools that scan the wider internet, Face2social focuses specifically on social media platforms, providing users with a more targeted search experience centered on public social profiles. Addressing the growing demand for social media identity verification Face2social’s key strength is its social-first focus. Rather than scanning the entire web, it targets platforms like Instagram, Facebook, TikTok, and X—where users are most likely trying to verify identities. This matters because intent is usually simple: not to find every instance of a face online, but to see if it connects to real social media accounts. By focusing on these platforms, Face2social feels more practical and relevant, positioning social media face search as a direct solution to a common, modern problem. Social media face search offers a more direct starting point by using the

UK ministers lobby Trump to avert backlash against social media ban

Ministers have embarked on a concerted lobbying operation to prevent a backlash from the Trump administration to the under-16s social media ban announced by Keir Starmer. Officials said they have spent weeks trying to reassure senior Trump officials and the US president himself that the restrictions were not specifically aimed at US technology companies. The ban on platforms including X, Facebook, YouTube, Snapchat and TikTok, makes the UK the second country in the world to put sweeping limits on social media for children, after Australia did the same earlier this year. But British officials are aware of the risk of retaliation from Trump, whom Starmer will meet at the G7 summit in Evian this week and who has previously threatened the UK with “a big tariff” if the government does not drop its digital services tax. One person involved in the effort said ministers had taken a three-pronged approach to “engage the companies, pre-brief the administration and myth bust in the media”. They added: “This is about protecting children in Britain, not taking on US tech.” Asked about the possibility of sparking a fresh row with Washington, Starmer said: “I honestly think that across world leaders, there has always been a recognition that leaders have to take steps to protect children.” He added: “In relation to President Trump, I spoke to him on Saturday, I’ll see him again this afternoon and, yes, of course, we’ll discuss this and many other issues, and lots of other leaders are very interested in it.” By Monday evening the US president had not commented on the plans. However his ally Elon Musk, who owns X, posted: “This censorship law is a wolf in sheep’s clothing. The real goal is to enable the UK government to track everyone.” The plans involve a wider set of

From Pitch to Lab: Georgia State Scientists are Tackling One of Soccer's Toughest Injuries

SORRY, WE'VE CHANGED THE WEBSITE AND CAN'T FIND THE PAGE YOU WERE LOOKING FOR. Although there could be several reasons why you got this page, here are some possible reasons for the error: Mistyped URL Copy-and-paste error Broken link Truncated link Moved content Deleted content If those don't help, use the search bar below to help locate what you might be looking for, or return to the News Hub homepage. Search the News Hub FEEDBACK Tell us how our website could be better for you.

Conroe police chief addresses concerns with Flock safety cameras

In a nutshell Buckholtz said the cameras are designed to identify vehicles involved in criminal activity and are not used for traffic enforcement, to issue speeding tickets or for facial recognition. Information that the camera does collect includes: - License plate number - Vehicle make, model and color - Date, time and location of detection - The identification of vehicle occupants - Audio or video recording - Continuous video surveillance - Monitoring of private property - Collection of personal information More details When it comes to investigative uses, Buckholtz said the Flock cameras can be used for investigations such as: - Stolen vehicles - Wanted suspects - Missing persons - Amber Alerts - Silver Alerts - Thefts - Violent crimes - Burglaries - Hit-and-runs When it comes to data storage and retention, Buckholtz said the cameras retain data for 30 days, after which it’s deleted, and the data is encrypted and stored in a secure cloud infrastructure. In terms of sharing Flock camera data with other law enforcement agencies, Buckholtz said Flock allows the police department to collaborate with the Montgomery County Sheriff’s Office and neighboring cities within a 50-mile radius. Access is not allowed for immigration uses or reproductive care, and Conroe police does not share with any federal agency, Buckholtz said. Also of note In response to community concerns, Buckholtz said Flock does not track people throughout the day, identify who’s driving or use facial recognition. The cameras also cannot track someone in real time continuously, only capturing detection where they’re installed. Buckholtz also said Flock will not sell data for commercial purposes, and while Flock uses artificial intelligence and machine learning, it is not AI surveillance. By the numbers Buckholtz said that in the past 30 days in Conroe, there were: - 14.4 million camera reads -

EUROSATORY NEWS: European Air Defense Needs to be Fully Autonomous

MISSILE DEFENSE EUROSATORY NEWS: European Air Defense Needs Full Autonomy, Experts Insist By Allyson Park Marine Corps photo PARIS — As wars in Ukraine and in Iran continue, one of the most significant lessons the European defense world is learning from both those conflicts is the importance of fully autonomous, layered air defense. Johannes Pinl, CEO of global defense and security company MARSS, said that the most recent drone that flew in the Iran conflict a few days ago was shot down by an almost fully autonomous defense system, and that’s the fundamental shift that needs to occur in air defense. “In the Middle East .... we have now such a mass of incoming targets,” he said during a roundtable at the Eurosatory defense exhibition June 15. “What we had to do was automate the kill chain, from detection, classification and countering, automate that as much as possible, so we can actually deal not with one, two, 10, 50, but hundreds of threats simultaneously.” Drones are becoming more autonomous and more embedded with artificial intelligence, and the key to defending against that threat is a multi-layered, fully autonomous approach, he said. “The only way to defend against that is actually being autonomous yourself, otherwise you're too late.” Layered air defense means possessing and executing multiple kinds of capabilities and effectors depending on the threat such as laser weapons that can eliminate high numbers of threats quickly and cheaply, interceptor drones that can be launched to defend against a drone swarm and more traditional defense systems that are cannon, missile or rocket based, but are more expensive, he said. “All that needs to be orchestrated by a very intelligent command and control system,” Andreas Schwer, CEO of EOS Defence Systems, said at the roundtable. “So, matching defense versus attackers is another

HKUST Develops World's First AI Slide-Free Pathology Imaging System

HKUST Develops World's First AI Slide-Free Pathology Imaging System Generates Histological Images in Just Three Minutes to Support Rapid Intraoperative Diagnosis A research team from The Hong Kong University of Science and Technology (HKUST), together with an HKUST-incubated medtech startup, PhoMedics Limited, has developed Glanzir®, the world's first artificial intelligence (AI)-enabled, slide-free pathology imaging system. The system enables direct imaging of fresh tissue without the need for conventional procedures such as freezing, sectioning, and staining, producing histological images in approximately three minutes in an operating room setting for intraoperative assessment. Compared with using formalin-fixed and paraffin-embedded (FFPE) tissue, which is widely regarded as the gold standard in pathology, Glanzir® has demonstrated approximately 85% or higher diagnostic concordance. Upon completion of large-scale clinical trials, the team expects this concordance to improve further to around 95%. The technology has the potential to shorten intraoperative diagnostic time while preserving intact tissue for downstream analyses. The team plans to collaborate with public and private hospitals to advance clinical adoption, with the goal of improving overall diagnostic workflow efficiency. With an aging population and rising cancer rates, demand for pathology services continues to grow. Histopathology remains fundamental to cancer diagnosis. In current clinical practice, two primary techniques are used for tissue assessment: FFPE and frozen section analysis. While FFPE is considered the gold standard due to its high accuracy, it typically requires several days to a week to complete. Frozen section analysis, by contrast, can provide preliminary results within 30 to 45 minutes during surgery, but its diagnostic accuracy is suboptimal compared to FFPE, occasionally necessitating repeat surgery for patients. To address these constraints, a research team led by Prof. Terence WONG Tsz-Wai, Associate Head and Associate Professor in the Department of Chemical and Biological Engineering at HKUST, together with his medtech startup PhoMedics Limited,

Report: Americans support targeted AI surveillance, oppose 'indiscriminate' monitoring

- Americans support targeted AI surveillance but oppose indiscriminate monitoring, a report reveals. - The report said 94% of respondents expect security cameras to aid or solve crimes committed in public spaces. - Concerns persist over AI facial recognition tracking citizens at civic events, highlighting privacy issues. SALT LAKE CITY — Everyday surveillance has, slowly but surely, become integrated into more and more aspects of our lives. You or a neighbor likely uses a Ring doorbell or has some variety of home security system. Traffic cameras catching erratic and speeding drivers is far from a new phenomenon. And with AI becoming ever more integrated into all aspects of life, surveillance technology certainly isn't being left behind. But how do Americans feel about it? A report released last week by Utah-based software company LiveView Technologies, based on a Harris Poll survey of 2,089 U.S. adults, aimed to answer that question by painting a picture of how people actually feel about emerging technologies like AI-powered security cameras, license plate readers, and facial recognition in public spaces. Perhaps surprisingly, the main takeaway wasn't that Americans distrust surveillance or oppose AI integration into surveillance but oppose "unchecked, indiscriminate surveillance," said the report. "The public draws a precise line: They endorse targeted technology that monitors behavior, detects active criminal actions, and identifies known violent offenders, while explicitly rejecting systems designed to track ordinary citizens going about their daily routines," the report continued. Surveillance has been a hot topic in national and local headlines, specifically license plate recognition. Ivan Miller, an Iowa man charged with killing three women in southern Utah, was captured in Colorado in March through a network of license plate recognition cameras, a technology that has become increasingly common across the country and is debated among citizens concerned about privacy implications. While the

Cornwall tech firm planning global expansion after USA | Falmouth Packet

A tech firm in Cornwall is making waves on the world stage with its facial recognition technology. Penryn-based Salto VisionWorks, headquartered at Tremough Innovation Centre, has launched its frictionless access solutions in the USA and is planning further global expansion. The business began more than a decade ago under the name TouchByte and was acquired by global door access company Salto in 2023. Jeremy Sneller, managing director at Salto VisionWorks, said: "We started in Cornwall 11 years ago with a small team and a big idea – to use face recognition to make everyday access simpler and more secure. "Launching in the US with a huge stand in Las Vegas is a milestone for us, and it's one we're proud to reach while still based here at Tremough Innovation Centre." Salto VisionWorks’ technology delivers secure, seamless access to offices, gyms, and facilities across higher education, health and care, residential, and critical industries. To date, it has processed access for approximately 750,000 people. The company emphasises privacy and security in its approach to facial recognition. Mr Sneller said: "The technology itself is focused on convenience, not surveillance. "Our system doesn’t store faces; it stores an algorithm, so people can enjoy the benefits of frictionless access without feeling like they're being watched." Salto VisionWorks recently showcased its technology in Germany and has further plans to expand into Norway and the Asia-Pacific region, including Australia, New Zealand, and Singapore. The company currently employs 15 staff and expects to grow to 20 by the end of the year. Salto VisionWorks is also committed to supporting its local community. Mr Sneller said: "Cornwall is a brilliant hub of ambitious, bright individuals, and we’re committed to creating high-value tech careers for young people here, with most of our team aged 35 and under, including apprentices. "Our

Law enforcement relied too heavily on AI, falsely arrested a suspect, ACLU argues

A Fort Myers man and the ACLU of Florida are suing Jacksonville Beach for relying too heavily on an artificial intelligence program that fingered him as a suspect in a now-dropped 2023 child luring investigation. The ACLU said in a 66-page federal lawsuit that Robert Dillon had been arrested “for a crime he never committed in a city he’d never been to.” Dillon filed suit against the Jacksonville Beach Police Department and the Jacksonville and Pinellas Sheriff’s offices on Wednesday in a case centering around what the ACLU calls a “faulty facial recognition match” in 2023 and an arrest eight months later. The now-dropped charges claimed that Dillon, a commercial crabber from Fort Myers, tried to lure a child at a McDonald’s in Jacksonville Beach, five hours from his home. “The night I spent in jail after they arrested me for a crime I did not commit still haunts me to this day. I will never get over how terrified and worried I was, wondering if I’d ever go home to my wife and daughter again,” Dillon said in a news release. Dillon’s attorneys explain that law enforcement put security camera footage into facial recognition technology operated by the Pinellas County Sheriff’s Office, comparing the image to millions of photos in a database to find matches. It returned a 93% match to an image of Dillon. “Over a year later, I’m still picking up the pieces of my life, all because the police relied on this dangerous technology instead of doing their jobs and actually investigating,” Dillon said. “Florida police must implement safeguards and ensure this never happens to anyone else, because until they do, nobody is safe.” The 2023 investigation centered on the idea that the suspect was a regular at the McDonald’s and that witnesses picked a picture

Safe, smart or surveilled? The AI question for student accommodation

In June, students at San Diego State University (SDSU) discovered through their student newspaper that more than 1,300 AI-enabled cameras had been installed across campus over the previous two years, including more than 330 in residence halls. The cameras, made by Avigilon, are capable of facial recognition, licence plate reading, behaviour analysis and crowd density tracking. SDSU says the advanced AI features are switched off, and the system is there to keep students safe. However, students say they were never told what the cameras could do, and that knowing they could be watched in those ways, including in the buildings where they live, changes how the environment feels. While the SDSU story is set in the United States, the underlying questions it raises are relevant to student accommodation providers worldwide. As AI-enabled and data-driven technology moves from the back office into buildings, and from buildings into residential settings, providers need to be clear and able to explain where the line lies between care, convenience, safety and surveillance. AI as a student companion and coach For a growing number of students, AI is already part of how they manage their own wellbeing, with or without their accommodation provider’s involvement. HEPI’s 2026 student generative AI survey found that around 15% of UK students are already using general-purpose AI tools for companionship, advice, or to address loneliness. It also found that 8% of students use counselling or therapy services provided solely by AI, and 4% use services where counselling or therapy is provided partly by AI. This does not mean that student accommodation providers should rush to replace human support with chatbots. If anything, it points in the opposite direction. Students are already experimenting with these tools, so the sector needs to be clear about what AI can safely do, what it should

First AI World Cup in history: What technology innovations are used during sports' biggest stage?

The 2026 World Cup in the US, Mexico, and Canada will be the main sporting event of the year, but it will also be the first one to work like a live giant laboratory for sports technology. Almost every action on the pitch will generate digital data, from player positions, ball movement, contact points, refereeing decisions, crowd movement, broadcast output for viewers, and even tactical analysis for the teams. Behind a match that looks simple to the eye, layers of cameras, servers, algorithms, mobile devices, and AI systems will operate, turning the World Cup into something The current tournament is the first to feature 48 national teams and includes 104 matches across 16 host cities. Technologically, that scale changes the rules of the game. A World Cup like this cannot rely only on referees, television cameras, and traditional broadcasting. It requires a distributed computing infrastructure, load management, near-real-time video transfer, data-analysis tools for all the teams and systems that can make decisions or assist in decision-making within seconds. In other words, the 2026 World Cup is no longer just a sporting event. It is a global computing event. Most advanced Video Assistant Referee ever One of the main technologies in the tournament is the advanced semi-automated offside system. A previous version of the technology was used at the 2022 World Cup, but in 2026, it is taking a leap forward. Instead of offside information reaching only the VAR room, in clear cases, the system will be able to send an alert directly to the on-field referees. The result is less time between a player going offside and the flag being raised, especially in relatively simple situations. FIFA stressed that the system does not replace referees in every case, does not rule on its own in complex cases involving influence on

An intelligent SCADA-integrated deep learning framework for bird-safe offshore wind farm operation

Abstract The rapid expansion of offshore wind energy has intensified concerns regarding avian collisions with turbine blades, particularly for migratory and high-risk bird species. Conventional mitigation approaches—including radar monitoring, manual intervention, and acoustic deterrents—are often limited by high false alarm rates, delayed response times, and the lack of species-level identification. To address these challenges, this study proposes an intelligent framework that integrates a Supervisory Control and Data Acquisition (SCADA) system with a Deep Convolutional Neural Network (DCNN)-based Bird Detection and Classification (BDC) model. The proposed system performs automated image-based bird classification and translates detection outputs into SCADA-driven turbine control actions through a multi-zone proximity assessment strategy. The model is trained and evaluated on a dataset comprising 525 avian species with over 90,000 images. Comparative analysis against conventional classifiers—including Support Vector Machines (SVM), Random Forest, K-Nearest Neighbor, and VGG16—demonstrates that the proposed BDC model achieves superior performance, with an accuracy of 99.62%, precision of 99.92%, recall of 100%, and an F1-score of 99.93%. In addition to classification performance, the system demonstrates a simulation-based system, achieving inference latency below 30 ms and SCADA response execution within 40 ms. These results highlight the potential of integrating deep learning with operational control systems to enable automated, risk-aware turbine response mechanisms for wildlife protection. It is important to note that the evaluation is conducted under controlled dataset conditions, and the dataset does not fully represent real offshore environments characterized by long-distance detection, motion blur, occlusion, and complex backgrounds. Therefore, the reported performance should be interpreted as an upper-bound estimate, and future validation using real-world offshore data is required to confirm deployment robustness. Overall, the proposed framework provides a simulation-based proof-of-concept approach for bridging AI-based avian monitoring with SCADA-enabled turbine control, contributing toward environmentally sustainable offshore wind farm operation. Introduction The global transition toward low-carbon energy

David Beckham honored by wife Victoria, Tom Cruise at Walk of Fame ceremony

David Beckham honored by wife Victoria Beckham, Tom Cruise at Hollywood Walk of Fame ceremony David Beckham is now immortalized on the Hollywood Walk of Fame. The soccer legend received his Walk of Fame star in a ceremony on Friday, where he was honored by his wife Victoria Beckham and fellow Walk of Famer Tom Cruise. In his remarks, Cruise highlighted Beckham's illustrious career on the soccer pitch with Manchester United, where he made his most iconic shot from the halfway line against Wimbledon in 1996. "The ball was in the air for just 3 1/2 seconds," Cruise said. "But that moment has now lived for three decades in the minds of everyone who saw it and in the history of sport. And if you didn't know who he was then, you certainly did a few months later." Cruise also spoke about Beckham's iconic curling free kick for England in the 1998 FIFA World Cup. The signature technique inspired the title and premise of the film, "Bend it Like Beckham." The "Mission: Impossible" star said Beckham "inspired generations around the world to watch and play the game." When Victoria Beckham took the stage, the "Spice Girl" singer joked that she thought she was getting her star on the Walk of Fame for "Spice World." "As it turns out, earning a star takes a little more than surviving the late '90s box office," she said. "It takes vision, determination and an extraordinary amount of hard work. So to see David's name become part of that story today is incredibly special." David Beckham's star on the Walk of Fame comes as the 2026 FIFA World Cup is underway. The soccer legend, who made three World Cup appearances over the course of his storied career, said receiving the honor feels "surreal." "I've always

A cancelable ear <b>recognition</b> system via optimized deep feature fusion | Scientific Reports

Abstract The rapid expansion of biometric authentication technologies worldwide has heightened the need for highly reliable and secure identification methods. This research explores the human ear as a distinctive biometric trait, capitalizing on its stable and person-specific anatomical structure. Although ear biometrics offer notable advantages, their practical use is hindered by image variations arising from changes in pose, scale, rotation, illumination, and contrast. To overcome these challenges, this paper presents an innovative deep learning-based ear recognition framework. The proposed approach employs a dual-stream feature extraction strategy that integrates two advanced Convolutional Neural Network (CNN) models MobileNetV3 and DenseNet-121 to derive rich and complementary feature representations, which are subsequently fused. The resulting high-dimensional feature space is then optimized using a Multi-Learning Strategy Golden Eagle Optimization (MLSGEO) algorithm to retain only the most discriminative features. To strengthen security and privacy, the refined feature vector is transformed into a non-invertible, cancelable biometric template using a Comb-filter–based protection mechanism. Data augmentation techniques are further applied to compensate for dataset size limitations. The framework was evaluated on five benchmark ear datasets: AMI, AWE, IITD-I, IITD-II, and UERC, achieving recognition accuracies of 99.90%, 99.64%, 99.78%, 99.32%, and 93.31%, respectively. Experimental findings show that the proposed system outperforms existing state-of-the-art methods. Overall, the integration of robust feature learning with a resilient template protection scheme demonstrates strong potential for secure and high-accuracy biometric authentication applications. Introduction The rapid expansion of the Internet of Things (IoT) has reshaped modern digital ecosystems, creating networks of interconnected smart devices that automate processes and enable seamless communication across industrial, domestic, and urban infrastructures. Although these advancements deliver unprecedented convenience and efficiency, they simultaneously introduce significant security vulnerabilities, particularly in scenarios where reliable user identification remains critical. Conventional authentication methods—such as passwords, PINs, or physical tokens—are increasingly inadequate, as they can be forgotten,

Photiu Launches Free AI <b>Image</b> Upscaler to Enhance Photo Quality Without Sign-Up

NEW YORK, United States – 13th June 2026 – Photiu launched a free, browser-based AI image upscaler designed to help users enhance photo assets instantly without software installation, account creation, or subscription fees. The tool accepts common image formats including JPG, JPEG, PNG, and WEBP and applies an automated machine learning pipeline to reconstruct missing detail, remove compression artifacts, and sharpen edges. The service is intended to enhance photo files that are blurry, compressed, or low-resolution and to deliver cleaner results than conventional pixel-stretching resizing methods. Photiu’s processing approach upscales first and then downscales. When an image is uploaded, the system analyzes visual patterns, reduces noise, reconstructs textures, and redraws sharp edges before returning a resized result. That workflow is described as producing a larger, cleaner intermediate that maintains more clarity when adjusted to target dimensions. The underlying deep learning models were trained on millions of high-quality image pairs, enabling recognition and reconstruction of common visual elements such as skin tones, fabric textures, architectural lines, and natural scenery. The platform’s automatic pipeline does not require manual sliders, quality presets, or technical decisions. Users upload an image and the AI completes background processing, producing a cleaner output within seconds. The fully automatic flow is positioned to make it feasible for designers, marketers, content creators, and everyday users to upscale image resolution quickly without prior editing experience. Photiu also includes an AI-based magic eraser that removes unwanted people, objects, or distractions and fills backgrounds to match surrounding content. The eraser functions alongside resolution enhancement and noise reduction, allowing the same session to address both unwanted elements and image clarity. The noise and artifact removal component is intended to clean images that have been saved multiple times, compressed by social platforms, or captured on older devices where invisible compression damage degrades gradients and

Find out how an Argus reporter won The Traitors with zero skill

I’d be lying if I said I wasn’t nervous going to the Traitors: Live Experience considering I’d always struggled to follow the series. With my housemates, my facial recognition became such a point of contention during the last series that I eventually begged one of our tutors — the only person I knew who owned a printer — to produce twelve A4 photographs of the cast. I argued it was his pastoral duty to intervene. Four months later, the photos remain pinned up on our kitchen wall. The day of the Traitors Experience was filled with desperate anticipation. In the name of hard-hitting journalism, I briefly considered concealing both my identity and my friendship with my housemate, Meg, that was coming along for the ride. Spoiler alert: this failed almost immediately. The time was now to show what I was made of. Surely playing it would be easier than watching it? After being granted entry by bodyguards into a gothic terrace in the heart of Covent Garden, we were led to the Cloak and Dagger pub. The psychological warfare started instantly. Alliances were quietly forming before people had even finished their first drink. One woman told me I had a doppelgänger, then refused to show me a photo because apparently she “hadn’t had a glow up yet”. A surprisingly effective intimidation tactic. A couple from California were favourites from the beginning. They flirted with a couple of American stereotypes by pretending they’d never even seen The Traitors. Nobody believed them for a second. After the bar, we were led through a series of maze-like corridors. We must have walked down about four before it dawned on me: this was a ploy to disorientate us. Paranoia had already set in. When we reached the end of the maze, we were led