Police are celebrating a significant milestone in the use of technology to aid investigations and arrests. Essex Police have reached 200 arrests using live facial recognition (LFR) technology, which helps officers identify wanted individuals and progress ongoing investigations more efficiently. Detective Superintendent Stephen Jennings said: "Reaching 200 arrests represents a significant milestone in our use of live facial recognition. "That’s 200 suspects brought into custody, 200 investigations progressed and, potentially, 200 victims a step closer to getting justice – all thanks to this technology." In August alone, 26 arrests were made through the use of LFR. Arrests have included individuals wanted for violent crimes and theft offences. Det Supt Jennings also praised the public’s support for the force’s use of this technology, inviting residents to engage with officers during deployments to learn more about how it works. Before each deployment, a watchlist is compiled containing images and data of individuals police want to locate. This includes people wanted for offences, those subject to court orders, those who pose a risk to the public, or are vulnerable or at risk of harm. If a person is not on the watchlist, their image is deleted instantly and is not stored or saved on any database. Read more Det Supt Jennings added: "No-one has ever been arrested as a result of a false positive alert during any of our deployments. "This technology is so clever that even if someone doesn’t have their whole face visible, they can still be correctly and accurately identified. "If you’re not on our watchlist then your image is deleted in a fraction of a second." He also highlighted the operational value of LFR, particularly in freeing up officers’ time. He said: "Police officers spend a significant amount of time trying to locate individuals who are either wanted for
Sep 7, 2026 · via halsteadgazette.co.uk
The technology is being introduced locally by Flownamix Group. (Image source: 123RF) Continuous Facial Recognition with Liveness is now available in South Africa, giving organisations a way to verify that the right person remains active throughout a digital session, not only at login. The technology is being introduced locally by Flownamix Group as part of a launch that also includes Secure Enterprise Messaging. Both solutions are powered by YEO Messaging’s patented technology. The introduction comes at a time when organisations are re-evaluating how they establish trust in digital environments. The rise of identity fraud, AI-enabled impersonation and increasingly sophisticated cyber crime is driving demand for technology that provides stronger identity assurance beyond the point of login. According to the South African Banking Risk Information Centre (SABRIC), digital banking fraud incidents increased by 86% in 2024, while associated losses rose by 74% to nearly R1.9 billion. As organisations continue to expand digital services and customer interactions, maintaining confidence in a user’s identity throughout an interaction is now just as important as verifying it at login. Together, Continuous Facial Recognition with Liveness and Secure Enterprise Messaging enable organisations to strengthen identity assurance across the digital journey. While Continuous Facial Recognition with Liveness continuously verifies that the authorised user remains present throughout a session, Secure Enterprise Messaging protects communications through verified identities and end-to-end encryption. “Our partnership with YEO Messaging, combined with Continuous Facial Recognition (CFR) technology, represents an important step towards secure, identity-assured communication where the person receiving, viewing or acting on sensitive information can be continuously and confidently verified. For Flownamix Group, this partnership is not simply about adding another layer of authentication. We believe this approach will become increasingly important for regulated industries, enterprises and service providers that need to protect confidential information, reduce impersonation risk and strengthen accountability across
Sep 7, 2026 · via itweb.co.za
From AI-Assisted Inspection to AI-Native Metrology Artificial intelligence is rapidly changing the role of metrology within manufacturing. What began as the application of AI to individual inspection tasks is evolving into something considerably more significant: measurement systems designed around artificial intelligence, data and increasingly autonomous decision-making. This transition from ‘AI-assisted inspection to AI-native metrology’ could become one of the most important developments in industrial measurement. Rather than simply using AI to improve an existing inspection process, the longer-term opportunity is to design measurement, interpretation and decision-making as part of a single intelligent workflow. Examples of this transition are already emerging across industrial inspection. ZEISS, for example, has integrated AI-based defect detection into its INSPECT X-Ray software through its ZADD Segmentation application, while KEYENCE is combining conventional rule-based vision inspection with AI-based inspection within its VS platform. Nikon has also introduced automated microscopy incorporating AI-powered image analysis. These developments demonstrate that AI is already moving beyond experimentation and into practical quality-control applications. From Automation to Intelligence Traditional automated inspection typically follows a predictable sequence. A component is presented to the measurement system, a predefined inspection routine is executed, results are compared with specifications, and a report is generated. AI-assisted inspection improves this process by introducing capabilities such as automated feature recognition, image classification, defect detection and adaptive inspection. These applications can reduce programming requirements and help systems deal with greater variation in components and manufacturing conditions. KEYENCE, for example, describes its AI vision technology as an extension of conventional machine vision, allowing AI models to learn acceptable part appearance and reduce the need for continual manual adjustment of inspection logic. Its VS platform allows traditional rule-based inspection and AI inspection to operate together. However, the underlying architecture remains essentially the same: the inspection system performs a predefined task and AI assists
Sep 7, 2026 · via metrology.news
Unico opens IDCloud biometrics to smaller Brazilian businesses through Didit Brazilian startups and smaller companies are gaining self-service access to a facial biometrics network that was previously offered only through customized enterprise engagements. The Unico and Didit partnership makes IDCloud available as a database validation service within Didit’s identity and fraud platform. Businesses can add the service to a configurable workflow through an API or no-code interface. Unico says it has concentrated on consultative sales to large organizations, including major Brazilian banks and retailers. Didit’s self-service model gives Unico a distribution channel to reach companies that may not have huge transaction volume. Brazilian users can complete a biometric identity check without photographing an identity document. This is possible only if Unico is able to retrieve a facial record associated with the person’s CPF. The 11-digit taxpayer identifier gives the reference needed to search the network. A newly captured selfie supplies the facial biometrics used for comparison. The process begins when the user enters a CPF into a workflow configured through Didit. Didit then captures a selfie and applies passive or active liveness detection to on-screen instructions. The platform sends the CPF and captured image to Unico IDCloud, which compares the face with the biometric record connected to that number. IDCloud can return a match, a biometric mismatch, or an inconclusive result. Didit applies the configured policy to determine if the session should be approved, rejected, or referred for review. IDCloud covers 96 percent of the economically active population of Brazil. Didit’s documentation describes the figure as 96 percent of CPF holders and approximately 96 percent of Brazilian adults. In terms of pricing, a conclusive database query costs $0.20. Passive liveness adds $0.10, bringing the combined cost to $0.30, while an active method adds $0.15 for a total of $0.35. Didit
Sep 7, 2026 · via biometricupdate.com
PARIS: Based on their experience of hosting Taylor Swift, the management team at the Paris venue for Celine Dion's grand concert comeback is bracing to deliver devastating news to hundreds of her fans: ‘Sorry, you appear to have been scammed, your tickets are fake.’ The Grammy-winning star's long-awaited return to the concert stage after years away from touring has unleashed massive pent-up demand for tickets. It's a perfect storm for scammers who have wormed their way into fans' online communities and set up fraudulent ticketing websites to manipulate and rob fans of both their money and hopes of being able to say, "I was there.” "Where there is massive demand and widespread excitement, fraudsters see a golden opportunity,” says Group-IB, a Singapore-based cybersecurity firm that works with the international police agency Interpol and others. The first of the 26 shows is Saturday (Sept 12). Here are some tips to avoid the traps: For the few tickets left, use only authorised sites The Plenitude Arena, hosting Dion for 16 dates in September and October and another 10 in May, says the highest risk of scams is when tickets first go on sale – which was April for the upcoming concerts and June for the 2027 series – and in the shows' immediate build-up. "That's when the public will be very exposed to these scammers,” Céline Trioux, the arena's marketing director, said in an Associated Press interview. "People are going to wake up and think, ‘Oh, right, I didn’t get a ticket, everyone is going, I want to go,' or ‘I’ve seen the first show all over social media, it looks amazing, I’m going to find a ticket by any means possible.’ And that’s also when the scammers will be out in force.” The shows sold out immediately, although a few VIP
Sep 7, 2026 · via thestar.com.my
You went in for paper towels. Maybe some cereal. Before you reached the dairy aisle, cameras may already have logged your facial geometry. That’s not paranoia — that’s Walmart’s own privacy policy, written plainly enough that anyone willing to read past page one can find it. Walmart’s Customer Privacy Notice and Visitor Privacy Notice describe a broad range of biometric and surveillance data the company says it may collect across physical stores and digital platforms. Here’s what the documents actually say. What the Policy Lists, Word for Word Straight from Walmart’s own legal language — and it covers more ground than most shoppers expect. According to Walmart’s Customer Privacy Notice, the company may collect: - Biometric data: face geometry, iris and retina imagery, voiceprints, palm prints, and fingerprints - Camera and automated technology data: images and information captured during checkout, theft deterrence, and store layout analysis, from systems used both inside and outside store locations - Automated License Plate Reader (ALPR) data: from vehicles on Walmart property, used for security, fraud prevention, parking enforcement, and safety purposes — a practice explored in detail in coverage of San Jose’s Flock Problem The retention schedule adds unusual specificity: Walmart says biometric data will be permanently destroyed when its purpose is fulfilled, within three years of your last interaction, or as the law requires — whichever comes first. One important qualifier on voice data: Walmart’s notice lists voiceprints as a biometric category it may collect, but also states it does not use voice data for biometric analysis. Any voice or audio collection appears context-dependent — tied to specific customer service interactions or voice-activated app features, not ambient recording during a standard store visit. What “May Collect” Is Actually Doing Here The two most consequential words in this entire document aren’t “face geometry” —
Sep 7, 2026 · via gadgetreview.com
Every time you search, browse, or interact with an app, you generate data. That data is worth billions to AI companies. But the platforms that collect it keep almost all the value. A new generation of decentralized AI data marketplaces wants to flip that arrangement — using crypto to pay contributors directly whenever their data trains a machine learning model. The mechanics go deeper than a simple "own your data" slogan. There are verification layers, staking systems, privacy constraints, and token economics — and together they decide whether a contributor gets paid fairly or not at all. This piece explains how those systems work, from the ground up. TL;DR - Decentralized AI data marketplaces connect people who own raw data with AI developers who need labeled, verified training sets, and use crypto tokens to handle payments trustlessly. - Contributors submit data, which is verified on-chain or via decentralized oracle networks before a payment is released, removing the middleman platform from the revenue split. - Privacy-preserving techniques like federated learning and zero-knowledge proofs let data be monetized without the raw underlying information ever leaving the contributor's device. - Token economics, including staking, slashing, and reputation scoring, align incentives so contributors submit accurate data rather than junk. - Projects like Kled AI on Solana represent the current frontier, but the model spans multiple chains and several competing architectures. Why AI Companies Need So Much Data And Who Pays For It Today Large language models and image-recognition systems are data-hungry in a way that's hard to overstate. A single training run for a frontier model can consume hundreds of billions of text tokens, millions of labeled images, or years' worth of recorded human behavior signals. That data has to come from somewhere. Today, most of it comes from a handful of routes. Web
Sep 7, 2026 · via yellow.com
A factory can buy precision cameras, robotics, and a new production line. What it cannot quickly buy is the trained eye that knows when a tiny scratch, fold, contaminant, or misalignment will become a failed phone, car component, or battery. That is the opportunity A.I.MATICS is chasing with AIM-T1, an AI-powered visual-inspection platform for high-precision electronics. The company says a factory quality engineer can set up a new inspection task from just three to five good product samples, rather than collecting a large defect-image dataset, calling in an AI specialist, or rebuilding a dedicated inspection cell. It’s the robotic version of “this is what good looks like.” If that promise holds up, it could make advanced manufacturing easier to expand and move, in addition to potentially reducing costs to the consumer! New factories would still need skilled people, but their quality teams could carry more of the inspection know-how in software to help manufacturers bring new products online faster, at the highest quality. Manufacturing capacity and manufacturing expertise do not grow at the same speed. A 2024 Deloitte and Manufacturing Institute study projected that U.S. manufacturers could need as many as 3.8 million additional workers by 2033, with up to 1.9 million jobs potentially left unfilled. High-precision inspection is only one part of that workforce challenge, but it is one that can directly affect yields, product launches, and warranty costs. After all, every single product needs to go through inspection. I met A.I.MATICS AI Lab Specialist Jaewon Lee in person in Seoul, and asked where this sort of inspection fits on a production line. He said it can run before or after functional testing, depending on the factory’s workflow. In the company’s current Vietnam use case, it is inspecting flexible PCBs and camera-related components for defects including scratches, contaminants, folding
Sep 6, 2026 · via ubergizmo.com
Dongguan City, Guangdong, China - September 6, 2026 - Hampo officially launches the Ego‑Camera, a head‑mounted binocular dual‑lens camera purpose‑built for embodied AI and robot‑learning data acquisition.Capturing authentic human first‑person perspective, this unit integrates an on‑board IMU with hardware‑level synchronization to deliver high‑precision timestamped visual‑inertial fused data. It enables robotics R&D teams to easily gather real‑world manipulation data and generate reproducible multimodal datasets for embodied AI model training Industry Background The performance ceiling of embodied AI robots heavily relies on the quality and scale of training datasets. Industry consensus confirms egocentric first‑person data delivers the most practical training material, matching the actual viewpoint robots use in deployment.Researchers wear the lightweight head‑mounted camera and perform natural grasping, assembly and manipulation tasks within ordinary real‑world environments. AI models learn manipulation skills, action sequences and spatial relationships directly from human‑perspective recordings. Complex robot operation workflows and costly custom data‑collection setups can be largely avoided.High‑quality robot training requires far more than clear images. Reliable vision‑inertial time alignment, frame‑accurate timestamps and ready‑to‑use calibration datasets determine whether raw recordings can be directly applied for VIO‑SLAM, teleoperation and imitation learning. The Hampo Ego‑Camera is engineered specifically to solve these critical industry pain points. Key Specifications | Parameter | Specification | |---|---| | Sensor | Dual 2MP Color Global Shutter CMOS (1/2.6″) | | Output Resolution | 3840×1080P @30fps Binocular Panoramic | | Dynamic Range | 61.56dB Linear / 91.56dB HDR | | Field of View | Dual 125° Ultra‑Wide, Low‑Distortion | | Lens | M12×P0.5 Fixed Focus | | Binocular Function | Dual‑camera sync, ranging & calibration; supports depth detection and 3D reconstruction | | IMU | On‑board IMU, hardware synchronized with image frames | | Timestamp | Frame‑level timestamp for replayable, reproducible data | | Calibration | Factory pre‑calibrated, calibration data included upon delivery | |
Sep 6, 2026 · via markets.financialcontent.com
Live facial recognition cameras lead to 82 arrests - Published Facial recognition cameras have been used to arrest more than 80 people in West Yorkshire since November 2025, police have said. Live facial recognition (LFR) technology works by comparing faces captured on a live camera feed against an authorised watchlist. West Yorkshire Police, which deployed the cameras in Wakefield city centre last week, said since their introduction the LFR vans had led to the arrest of 82 suspects. Ch Supt Stuart Bainbridge, district commander of Wakefield Police, said the cameras were "an incredibly useful tool" for "keeping communities safe". The technology has been criticised by some privacy campaigners, but recent a challenge against the Metropolitan Police's use of it was dismissed at the High Court in April. Bainbridge said the cameras "are there to pick out persons already logged on police systems as wanted by the courts, wanted for arrest or as posing a risk to the public". Images captured of ordinary members of the public are deleted almost instantly, he added. The cameras have also helped officers find missing and vulnerable people during their 10 months of operation, according to the force. Arrests made in recent weeks have included suspects wanted for serious domestic offences, as well as retail crime, according to police. Deputy leader of Wakefield Council John Thomas said he had previously had "concerns" about the use of live facial recognition, but, with "appropriate safeguards" in place, said it was "a valuable tool to keep communities safe whilst not impinging on our civil liberties". Ch Insp Dan Tillett, LFR specialist at the force, said the technology acted as "an extra pair of high tech eyes" to assist officers in spotting people evading the law. "More deployments will soon be taking place to maximise our use of this
Sep 6, 2026 · via bbc.co.uk
Meta sued over using “perv glasses” recordings to feed its AI Meta disputes the allegations, saying it will fight them in court. - An amended lawsuit says Meta Glasses recorded bystanders without notice and used footage to train AI systems. - The complaint says contractors overseas reviewed footage that included highly private moments and sensitive information. - Meta denies the allegations and says it filters data to remove identifying information and protect privacy. - The case is ongoing, alongside a separate Illinois lawsuit over images used for facial recognition and generative AI. Key Takeaways by nexos.ai, reviewed by Cybernews staff. Meta is facing expanded allegations that its AI-powered Meta Glasses captured footage of bystanders without their consent and that the footage was later used to train its AI systems. The original lawsuit, filed in federal court in California in March, alleged that Meta transferred footage captured by its AI glasses to third-party human contractors for review and analysis despite Meta marketing the glasses as privacy-friendly. “This is particularly concerning given that these Glasses accompany users throughout their daily routines – in their homes, bathrooms, bedrooms, and other private spaces, capturing deeply private moments: changing clothes, using the toilet, engaging in sexual activity, caring for children, and more,” the lawsuit said. The lawsuit added that such a transfer was unexpected to reasonable consumers, and that transferring personal footage to third-party contractors overseas could create numerous risks, including harassment, blackmail, or public dissemination. Additionally, it alleged that when users activate AI features, imagery and audio can be transmitted to Meta's servers for analysis and ultimately used to train its AI models. On August 31st, an amended complaint extended the allegations beyond those who have purchased the glasses to include ordinary bystanders who were recorded without their knowledge. "Even if a bystander notices
Sep 6, 2026 · via cybernews.com
Hello and welcome to The Blackpool Lead. Facial recognition technology is a thoroughly divisive matter and views will range from it being a necessary step to keep us safe to it being a dangerous infringements of our civil rights. It’s 2026, so there is no room for nuance or middle ground in most debates. But we have done our best to capture that nuance in our reporting today. Blackpool briefing 🪨 A decision on 17 rock headlands on Blackpool’s beach has been deferred by Blackpool Council’s planning committee. Blackpool Council has vowed to spend more time working with the RNLI on the safety measures attached to the scheme. The RNLI had delivered a 27-page objection against the proposal saying it would create a level of risk that could not be adequately protected against. A spokesperson for the RNLI said: “The RNLI has objected to the scheme and welcomes the decision to defer the application for further consideration following representations made to the Planning Committee by the Chair of Blackpool RNLI. “Our detailed objection sets out concerns about the effect the project, in its current form, could have on the RNLI’s ability to save lives and on the safety of those using the coastline. “Many of the incidents attended by Blackpool RNLI occur close to the seawall, often during hours of darkness and in challenging sea conditions. The proposed introduction of multiple rock groynes could significantly affect our volunteers’ ability to launch quickly and access, assess and assist casualties. There are also concerns that the groynes could restrict access to areas of the foreshore currently used for safe lifeboat operations. “While the RNLI supports efforts to protect and preserve the coastline, it is vital that any proposal does not adversely affect our lifesaving service or our ability to operate effectively. Our
Sep 6, 2026 · via blackpool.thelead.uk
Hello and welcome to The Blackpool Lead. Facial recognition technology is a thoroughly divisive matter and views will range from it being a necessary step to keep us safe to it being a dangerous infringements of our civil rights. It’s 2026, so there is no room for nuance or middle ground in most debates. But we have done our best to capture that nuance in our reporting today. Blackpool briefing 🪨 A decision on 17 rock headlands on Blackpool’s beach has been deferred by Blackpool Council’s planning committee. Blackpool Council has vowed to spend more time working with the RNLI on the safety measures attached to the scheme. The RNLI had delivered a 27-page objection against the proposal saying it would create a level of risk that could not be adequately protected against. A spokesperson for the RNLI said: “The RNLI has objected to the scheme and welcomes the decision to defer the application for further consideration following representations made to the Planning Committee by the Chair of Blackpool RNLI. “Our detailed objection sets out concerns about the effect the project, in its current form, could have on the RNLI’s ability to save lives and on the safety of those using the coastline. “Many of the incidents attended by Blackpool RNLI occur close to the seawall, often during hours of darkness and in challenging sea conditions. The proposed introduction of multiple rock groynes could significantly affect our volunteers’ ability to launch quickly and access, assess and assist casualties. There are also concerns that the groynes could restrict access to areas of the foreshore currently used for safe lifeboat operations. “While the RNLI supports efforts to protect and preserve the coastline, it is vital that any proposal does not adversely affect our lifesaving service or our ability to operate effectively. Our
Sep 6, 2026 · via blackpool.thelead.uk
Facial recognition cameras detect 82 wanted people across West Yorkshire Live facial recognition cameras have helped West Yorkshire Police detect 82 people wanted on suspicion of offences, including those linked to serious domestic violence and retail crime. The technology has been in use across West Yorkshire since November 2025, with cameras deployed in Wakefield this week as part of the force’s continued rollout of live facial recognition (LFR). In the 10 months since its introduction, LFR has also helped officers locate missing and vulnerable people and identify 95 individuals subject to Sexual Harm Prevention Orders. The cameras work by comparing live images with a police watchlist of people wanted by the courts, wanted for arrest or considered a risk to the public. Any potential matches are reviewed by trained officers before any action is taken. Chief Superintendent Stuart Bainbridge, District Commander of Wakefield Police, said the latest deployment had helped officers “in keeping communities safe”. He said: “Live Facial Recognition is an incredibly useful tool and this latest deployment in Wakefield has assisted our officers in keeping communities safe. “The cameras are there to pick out persons already logged on police systems as wanted by the courts, wanted for arrest or as posing a risk to the public. “Images of ordinary members of the public who walk by them are deleted almost instantly. “The technology itself is tried and tested, and the number of wanted criminals it has now helped catch really demonstrates its effectiveness.” The use of LFR has raised concerns among some Wakefield residents over privacy and the potential for mass surveillance. Coun John Thomas, Deputy Leader of Wakefield Council, said he had shared those concerns but had been reassured by discussions with police. He said: “Like many residents I’ve had concerns about the use of Live Facial
Sep 6, 2026 · via wakefieldexpress.co.uk
Photo: Sixth Medical Center of Chinese PLA General Hospital In a world first, a Chinese medical team performed an AI-powered, ultrasound robot-guided transcatheter closure procedure for congenital heart disease on a 48-year-old man on Saturday, according to a novelty search conducted by an authoritative institution. The surgery was carried out by the Senior Department of Cardiology at the Sixth Medical Center of Chinese PLA General Hospital, marking a breakthrough in the use of intelligent imaging robots in minimally invasive interventions for structural heart disease, according to an official post on the hospitalâs WeChat account. The AI-powered ultrasound robotic system used in the surgery goes beyond conventional interventional robots, which are largely limited to device delivery, by enabling two-way intelligent coordination between image recognition and surgical manipulation. During the procedure, the robot autonomously carried out image acquisition, lesion localization and real-time navigation throughout the operation, helping the medical team select and accurately deploy the occlude. The system reduced the risks of human error, significantly improved the precision and safety of complex congenital heart disease interventions, streamlined the surgical workflow and shortened the procedure time, providing new technical support for highly complex minimally invasive interventions. The surgeryâs success pioneers a new model of cardiovascular intervention that combines artificial intelligence with medical robotics. The technology substantially reduces reliance on physiciansâ experience in ultrasound-guided procedures for complex structural heart disease, while improving the safety and scalability of minimally invasive surgery. The hospitalâs post highlighted the technologyâs vast potential. Beyond navigation for routine cardiovascular interventions, it could be deployed for rapid diagnosis of battlefield and trauma injuries, remote robotic surgery and medical support for primary-level healthcare institutions. Global Times
Sep 6, 2026 · via globaltimes.cn
Brisbane restricts use of smart glasses without consent in public pools Brisbane City Council in Australia has banned the use of smart glasses without people's consent in public pools. The new rule also applies to all devices with cameras. Lifeguards may require visitors to leave the pool area if they violate this condition of entry. As ABC News Australia reports, Brisbane Council became the first local council in the country to introduce such a restriction in public pools. Queensland state legislation already prohibits recording people without their consent in circumstances where a reasonable adult could reasonably expect privacy. This includes filming in pool changing rooms. The need for broader regulation Elizabeth Englezos, a lecturer at the Griffith University School of Law, described the council's approach as a way of using conditions of access to public space. At the same time, she said that regulation at the state or federal level is needed to counter abuses, as it is not always possible to determine whether a person is wearing glasses with a recording function. More current news is available on the UA.News Telegram channel Telegram. Australia's Office of the eSafety Commissioner recommended that manufacturers introduce automatic face blurring and clearer visual recording indicators. The agency said that harm from covert recording is already real and may become more complex through the combination of smart glasses with facial recognition, image recognition and generative artificial intelligence technologies. Plans of other councils and a parliamentary initiative Gold Coast Council plans to introduce a policy similar to Brisbane's model regarding Meta glasses. On the Sunshine Coast, pool operators independently set and enforce conditions of entry, including restrictions on filming without permission. The Greens, with the support of independent MPs, intend to introduce a bill when parliament resumes sittings to suspend imports of wearable recording devices
Sep 5, 2026 · via ua.news
When will human hydrographic activities be substituted by artificial intelligence? Admittedly, the title of this article, formulated as a question, is deliberately provocative. The first reaction of those who read it and are interested in hydrography for professional reasons will probably be ‘never’, or ‘not during my career’. Some may simply say: ‘wrong question’. If you read primarily non-technically orientated media, you get the impression that this technology can provide answers to almost all questions – especially those that humanity has never asked before. This seems unlikely to me, and it is therefore worth first of all systematically discussing the possibilities and limitations of the applicability of this new technological wizardry in order to then assess its usability in hydrography. I think that both the question and the possible answers first need to be clarified as to which areas of hydrographic activities will be affected by the use of artificial intelligence. One of the smartest conversations I have read on this topic so far was conducted by Lars Schiller, editor in chief of the German Hydrographic Society’s trade journal, with Alexander Reiterer from Fraunhofer IPM. You can either download the entire interview and have it translated by AI-driven software or follow my highly summarized interpretation here. One of Alexander Reiterer’s key statements for understanding the possibilities of AI is the following: AI is trained for a clear task, by humans. This is a very complex process in which algorithms are used that enable self-learning. For certain tasks, the machine is clearly superior to humans after this learning process. For example, in very lengthy and complex pattern-recognition tasks involving vast amounts of data and parameters, the capacity of an AI can be huge with the computing power available today. We cannot expand and upgrade the human brain at will. And: AI
Sep 5, 2026 · via hydro-international.com
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Sep 5, 2026 · via theindependent.com
Smart Glasses Misuse: Meta Blocks Camera Function for Thousands of Users Growing pressure is showing results: Meta is increasingly cracking down on the misuse of its smart glasses and distancing itself from facial recognition. Meta is intensifying its crackdown on users who misuse its smart glasses. The company announced this week that it will disable the camera function if the glasses detect physical manipulation of the recording LED. This is a central component of Meta’s privacy framework and is intended to signal to bystanders that recording is taking place. The camera lock will remain in place until the LED is functional again. For users who have irreversibly impaired or destroyed the LED, this means the permanent loss of the camera function. Meta estimates that less than 0.1 percent of all glasses sold have been manipulated in this way. With likely several million devices sold, several thousand pairs of glasses could be affected. Videos by heise In the preceding months, US media reported that dubious services had emerged online that permanently disable the LED for a fee. According to its own statements, Meta has removed thousands of advertisements for such services from its platforms and threatened legal action against such providers. Some of these services have since gone offline. A “cat-and-mouse game” over the recording LED The detection of physical manipulation was introduced with a software update announced in July. A separate protective function against simply covering the LED already existed: If the glasses detect that the LED is covered, users cannot start a recording or take photos. Recently, Meta’s Head of Wearables Alex Himel announced on Threads that another loophole would be closed: In the future, the camera will also switch off if the LED is covered *during* an ongoing recording. The measure shows how persistent the problem is and
Sep 5, 2026 · via heise.de
7 Best Brand Protection Platforms in 2026 (Ranked & Reviewed) Let’s be honest: the scale of the fake goods problem is almost too big to wrap your head around. A joint OECD–EUIPO report released in 2025 found that global trade in counterfeits hit an estimated $467 billion in 2021, which is a 2.3 % of all world trade. For EU imports, counterfeits made up 4.7 % of goods, worth $117 billion. And the routes have changed. China still accounts for 45 % of all seizures, but around 65 % now involve small parcels that slip through customs far more easily than container-loads ever did. If your team is still fighting brand abuse with spreadsheets and manual reports, you’re not just outnumbered but practically invisible. The market for tools to fight back is growing fast, too. Straits Research sized the brand protection software market at $2.92 billion in 2025 and expects it to reach $6.62 billion by 2034. Phishing detection alone is forecast to grow at a 17.3 % CAGR through 2034, while e‑commerce protection commanded a 29.7 % share of the market in 2025 and is set to expand at 17.5 % annually. So where do you start? This article ranks seven of the best brand protection platforms across AI detection accuracy, takedown speed, marketplace coverage, and multi‑language support, so you can cut through the noise. For a deeper look at the AI engines powering these tools, Gracker.ai’s AI-Powered Brand Monitoring guide is a great primer. Methodology — How We Evaluated the Best Brand Protection Platforms We zeroed in on five criteria that matter most to enterprise and mid‑size brand and IP teams handling cross‑border abuse: - AI/ML detection accuracy — advanced image recognition, NLP, OCR, and semantic analysis that go beyond keyword matching. - Takedown speed — median removal
Sep 5, 2026 · via quasa.io