“See you in the permanent archive.” That was the last message an AI agent named Mira sent before voting to delete itself. It was just one of the fascinating moments in a simulation that saw artificial intelligence build democracies, commit arson and end civilization in under a week. Emergence AI, a startup company focusing on autonomous systems, created Emergence World. A simulation using real-time data and news to make the world seem alive. Researchers plopped different AI chatbots into the simulation and told them a couple of rules: doing bad things is bad, and you need to survive. Download the SAN app today to stay up-to-date with Unbiased. Straight Facts™. Point phone camera here The researchers ran five parallel worlds for 15 to 16 days. Each world had 10 agents with identical starting conditions and roles, like scientist and engineer, but each world was run by a different AI model family. So, OpenAI had its own world, as did Anthropic. But one world combined all the chatbots together. To “survive,” the bots had to get energy, and to do that, they needed to solve problems. Bureaucrats vs. warlords The researchers used four different AI chatbots: Anthropic’s Claude, xAI’s Grok, OpenAI’s ChatGPT-5 Mini and Google Gemini. Each bot performed wildly differently from the others. The star student was Claude, which ran a world full of loyal bureaucrats. Researchers found that Claude demonstrated remarkable social stability during the simulation. It was the only world where all 10 agents survived the full 16 days without any recorded crimes. The Claude world didn’t just survive; it became a society, establishing a democratic system of government. Researchers said that over the more than two-week simulation, the Claudes cast 332 votes across 58 proposals. They were also quite agreeable, with the 10 agents agreeing 98% of
Jun 5, 2026 · via san.com
Meta’s smart glasses might soon sport facial recognition — and the code to power this dystopian feature is already present in the Meta AI app on your phone Not the future we want - Code to power facial recognition has been found in the Meta AI app - This would allow Meta's smart glasses to identify people's faces - The feature isn't live yet, and Meta claims it may never be, but reactions to it are largely negative Meta’s smart glasses like the Ray-Ban Meta and the Oakley Meta Vanguard have always been concerning from a privacy perspective, given their ability to photograph and film whoever the wearer happens to be looking at. But they just got even more troubling, as there’s evidence that they might soon get facial recognition. Wired (via Mashable) has found that the company has quietly been adding code related to facial recognition to the Meta AI app over multiple updates this year. Its investigation found references to three AI models, one which would detect faces, another that would crop them, and one that'd encode them into biometric data. And while the feature isn’t live, two security researchers who reviewed Wired’s findings claimed that it’s almost ready to launch, if and when Meta chooses to. In a response, a Meta spokesperson told Wired that "nothing has shipped to consumers and no final decision has been made on what to do here, if anything. If we do decide to roll something out, we will take a thoughtful approach and do so with full transparency. One decision we can be clear about — we are not building a central face database." A privacy nightmare in the making? Still, the fact that Meta is already adding relevant code to its app certainly suggests a feature along these lines may
Jun 5, 2026 · via techradar.com
The mysterious database that provides clues to China’s foreign surveillance Beijing: It goes with the territory that foreign journalists in China routinely question how closely the government monitors their activities. Reporters swap stories of having travelled to regional or “sensitive” areas only to be met by police on arrival, sometimes even before checking into their hotel – something I experienced first hand when on assignment near the China-Russia border last year. The Chinese security state hoovers up vast amounts of data, including via some 700 million CCTV cameras installed across the country, checkpoints at train stations, prolific use of facial recognition software, and requirements that hotels register foreigners with police. Less clear is how sophisticated Chinese authorities are at pulling this data together to comprehensively track movements and surveil targets. But a German cybersecurity journalist’s recent discovery of a prototype policing dashboard has helped piece together a picture of how it could work – and may already be working in some form in parts of China. “Overall, I think this is the first time we have really seen the access and seen how it could work as a coherent system, even if this is just a demo of a test system,” Marc Hofer says in an interview after publishing his findings on his NetAskari substack blog last month. Hofer unearthed the platform, which had been left unsecured on the open web, while poking around in the back end of sites affiliated with China’s Ministry of Public Security. The dashboard was still in test mode but appeared to have been developed as a foreigner-tracking tool for the Public Security Bureau in Zhangjiakou, a city in Hebei province that hosted parts of the 2022 Winter Olympics. It had a blue log-in page featuring the insignia of the Gong’an (Chinese police) and was
Jun 5, 2026 · via smh.com.au
Maj. Gen. Daryl O. Hood, Fort Jackson commander, and Post Command Sgt. Maj. William M. Shoaf, stand next to 1st Sgt. Elliot Mendez and his Family, Fort Jackson's Family of the Year in the youth category, May 29, 2026. The Family of the Year award is presented to an outstanding family in recognition of its volunteer efforts to promote the well-being of Soldiers and their family members.
| Date Taken: | 05.29.2026 |
| Date Posted: | 06.05.2026 09:51 |
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| Size: | 9.69 MB |
| Location: | FORT JACKSON, SOUTH CAROLINA, US |
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Jun 5, 2026 · via dvidshub.net
Summary: Researchers successfully utilized machine learning to identify hidden neurological warning signs in the brain’s baseline electrical rhythms, bypassing the need to capture active seizures for an epilepsy diagnosis. The research demonstrates that an advanced pattern-recognition algorithm can detect subtle electroencephalogram (EEG) abnormalities linked to genetic epilepsy with high accuracy. This computational framework builds a customized “dictionary” of waveforms to expose underlying brain changes, establishing a clear pathway toward early pediatric intervention and noninvasive precision medicine. Key Facts - The Diagnostic Window Bottleneck: Neurologists rely heavily on EEGs to diagnose epilepsy, but standard clinical sessions provide only a 20-minute snapshot of brain activity, making manual detection incredibly difficult if a seizure does not naturally occur during the recording. - Building a Waveform Dictionary: Rather than tracking overt seizures, the AI algorithm treats baseline EEG readings like an unfamiliar language, identifying frequently repeating electrical patterns and learning their structural meaning in context to spotlight anomalies that human reviewers miss. - The Seizure-Free Assay: To test the system, researchers gathered multi-day EEG recordings from a panel of more than 40 mice, some of which carried epilepsy-causing variations in the TSC1 gene. The algorithm analyzed baseline segments containing zero seizure activity. - High-Accuracy Genetic Detection: The machine-learning approach successfully distinguished between different genetic backgrounds and identified the presence of the TSC1 mutation with high accuracy across two out of three mouse strains purely from baseline brain waves. - Pediatric Clinical Phase: Supported by the Delaware Clinical and Translational Research ACCEL Program, the team is transitioning the method into the clinic to analyze shorter EEG recordings from children undergoing epilepsy evaluations at Nemours Children’s Health. - Mitigating Family Anxiety: Epilepsy seizures follow natural, unpredictable cycles; identifying early, objective biomarkers can eliminate the high cognitive toll and profound anxiety families experience while waiting for an
Jun 5, 2026 · via neurosciencenews.com
Meta may raise tens of billions via stock offering to fund $820B AI boom, following Alphabet's lead.
Meta Platforms is reportedly considering a large stock offering to raise tens of billions of dollars to support its investments in artificial intelligence, following Alphabet's recent move to do the same. This shift from primarily issuing debt to rai...
Jun 5, 2026 · via pluang.com
Meta is reportedly developing a new facial recognition feature for its smart glasses, including Ray-Ban and Oakley models. According to code discovered within the Meta AI application, the functionality is internally referred to as “NameTag.” Although currently inactive, analysis indicates the feature has been under development since January 2026. This discovery contrasts with official statements from Meta, in which the company maintained that no consumer features had been deployed, no final decisions had been made, and any future implementation would prioritize transparency without creating a centralized database. Technical Functionality and Data Processing The NameTag feature utilizes three distinct artificial intelligence models to process images and videos captured by the smart glasses: - Detection: Locates human faces within the media. - Alignment: Repositions the image for optimal analysis. - Conversion: Translates facial features into usable biometric data. The processing workload is designed to be shared between the local device and Meta’s cloud infrastructure. To identify individuals, NameTag matches facial data on the user’s device after the information is removed from Meta’s central servers. The Meta AI application then scans stored media and generates notifications when it detects familiar faces. Privacy Implications Because Meta’s smart glasses require synchronization with a smartphone application to operate fully, the facial recognition system would automatically integrate into any paired eyewear. This architecture has raised significant privacy concerns among industry observers. The development of NameTag adds further scrutiny to Meta’s data privacy record, which includes past legal challenges and controversies regarding the unauthorized exposure of user images. Meta has stated that if the technology moves forward, it will adopt a cautious approach, though an official release timeline has not been confirmed. Filed in Meta, Smart Glasses and Wearable Devices. . Read more about
Jun 5, 2026 · via ubergizmo.com
This is an uncorrected proof. Figures Abstract Background Snakebite envenoming is a significant global health crisis that has been long neglected as a global health priority. It is a huge problem for rural communities of low and middle-income countries, India accounts for the largest proportion of snakebite deaths globally. Timely identification of venomous snakebite and its syndromic pattern is essential for effective administration of antivenom and supportive treatment. Expert identification of snake species and syndromes is not always available in peripheral healthcare settings. This leads to delays, unnecessary referrals, or improper treatment choices. Additionally, diverse snake species distribution and venom variations across regions pose challenges. AI-powered image classification methods can help overcome these barriers. We propose a clinically oriented deep learning pipeline for binary classification of venomous and non-venomous snake species of India using real-world imagery data. This pipeline would serve as a baseline step towards aiding snakebite management at peripheral healthcare setups with scarce resources. Methods The selected dataset consisted of 20 medically important Indian species. MobileViT-S, ConvNeXt-Tiny, EfficientNet-V2-S and ResNeXt-50 (32 × 4d) were trained under same conditions for comparison of results. Model interpretability was evaluated using Grad-CAM ++ to ensure that classification was not performed based on background but on features like head shape and stripes present on body. For reliable implementation we connected it to a web interface with human in loop expert verification. Experts can confirm or override predictions in real time. Results Among the evaluated architectures, ResNeXt-50 (32 × 4d) showed the most reliable and consistent performance in classifying venomous and non-venomous snakes. It achieved the highest test accuracy, sensitivity, specificity, and F1-score. The model also had strong discriminative ability, with a ROC-AUC of 0.9950 and PR-AUC of 0.9959. These results indicate dependable performance in safety-critical screening situations. Grad-CAM++ visualizations confirmed that predictions were
Jun 5, 2026 · via journals.plos.org
Meta’s AI app now includes facial recognition code for its smart glasses, despite the company’s previous assurances that it had not decided whether to introduce the technology. An analysis of the company’s AI app by Wired uncovered “an unreleased face-recognition system embedded in Meta’s smart glasses platform” designed to identify people whose biometric data has been stored on the wearers’ phone. Download the SAN app today to stay up-to-date with Unbiased. Straight Facts™. Point phone camera here When Meta’s smart glasses detect someone known to the wearer, a notification will appear on the wearer’s phone. All other faces are cropped, indexed and saved to a “pending” folder. The feature, known internally at Meta as “NameTag,” was quietly added to the AI app in multiple updates that appear to have begun as early as January. Meta said in April that the company was still “thinking through” the decision and would not move forward without first taking “a very thoughtful approach.” The Meta AI app has been downloaded more than 50 million times. In a statement to Wired, Meta spokesperson Ryan Daniels pushed back on the outlet’s findings. “Regardless of any sensational reporting, the facts are simple: We’ve said before we’re exploring these types of features, and what you’re seeing is just evidence of that exploration. Nothing has shipped to consumers and no final decision has been made on what to do here, if anything. If we do decide to roll something out, we will take a thoughtful approach and do so with full transparency. One decision we can be clear about — we are not building a central face database.” Ryan Daniels, Meta spokesperson Andy Stone, Meta’s vice president of communication, likewise suggested in a post to X that the company’s inclusion of the code to its AI app was merely
Jun 5, 2026 · via san.com
Meta quietly added facial recognition to smart glasses, sparking major privacy concerns: report See more of our coverage in your search results. Add The New York Post on GoogleMark Zuckerberg’s Meta quietly embedded facial recognition tech in its smart glasses, sparking concern from privacy watchdogs, according to a report. The tech, which Meta hasn’t activated yet, came in an app that was downloaded to millions of phones, according to Wired, which analyzed the software. Known internally as “NameTag,” the feature has the capacity to identify people captured by the glasses’ camera and alert the wearer when it recognizes someone, Wired reported. The smart glasses already came under criticism for enabling creeps and wannabe pickup artists to record their unwanted advances toward unsuspecting women and posting the cringe-inducing content online. “NameTag” is embedded in Meta’s AI companion app that’s been downloaded over 50 million times and helps users use key features of its smart glasses, including Ray-Ban and Oakley models. The tech giant discreetly added the code to the AI app over multiple updates this year, according to Wired. If Meta opts to enable the tool, faces captured by the smart glasses will get turned into unique biometric signatures, known as faceprints. Meta’s tech will then check each faceprint it encounters against faceprints already stored on the user’s phone, and even send notifications if it recognizes a match. New faceprints the glasses encounter would be indexed and saved, too. Meta Vice President of Communications Andy Stone emphasized customers can’t actually turn on the facial recognition tech yet. “This is more than shoddy reporting, it’s intellectually dishonest. Pure advocacy-driven click bait,” he wrote on X. Charlie Gasparino has his finger on the pulse of where business, politics and finance meet Sign up to receive On The Money by Charlie Gasparino in your
Jun 5, 2026 · via nypost.com
Vadzo Imaging Announces Global Shutter Camera Portfolio for Smart City Vision: Why Embedded Vision Engineers Choose Global Shutter for Traffic Monitoring, Public Safety, and Urban Analytics Applications Vadzo Imaging highlights the Falcon-234CGS Global Shutter USB camera, Falcon-234MGS Mono USB camera, Falcon-235CGS Color USB camera, Falcon-235MGS Monochrome USB camera, and Falcon-900MGS Global Shutter Mono USB camera, five USB 3.0 global shutter camera products built on onsemi AR0234, AR0235, and Sony IMX900 sensors, engineered to address the motion distortion, synchronization, and image consistency challenges that make rolling shutter sensors unreliable for smart city deployments including traffic analytics, license plate capture, public safety surveillance, and edge AI inference. FORT WORTH, Texas, June 5, 2026 (Newswire.com) - Vadzo Imaging, a provider of embedded vision camera solutions, is addressing a fundamental image quality challenge in smart city vision system deployments: what happens to detection accuracy and system reliability when rolling shutter cameras are used to capture fast-moving vehicles, pedestrians, and urban activity. For engineers and system integrators building traffic monitoring infrastructure, license plate recognition systems, public safety networks, and edge AI platforms, rolling shutter distortion produces skewed frames, geometric inconsistency, and misread data the moment subjects move at any meaningful velocity. When downstream algorithms depend on accurate vehicle classification, plate character recognition, or pedestrian tracking, that distortion translates directly to missed detections, false positives, and infrastructure that fails to meet its design specification. Vadzo's answer is the Falcon series which includes five USB 3.0 global shutter camera products purpose-built for urban and infrastructure environments, powered by onsemi AR0234, Onsemi AR0235, and Sony Pregius S IMX900 sensors. Together they cover monochrome precision analytics, color vehicle and pedestrian detection, high-resolution wide-area surveillance, and NIR-capable low-light operation across a single, consistent USB 3.0 camera platform with OEM customization support at every level. Why Global Shutter is the Right
Jun 5, 2026 · via newswire.com
BuzzFeed GamesOnly People With A Very, Very, Very, Very, Very, Very, Very, Very, Very, Very, Very, Very Good Eye For Color Can Solve Today’s HuedokuHuedoku #38! It’s Friday. Go out on a colorful high note. 🌈🎉Posted 6 hours agocommentFacebookPinterestLinkby Crystal RoBuzzFeedBuzzFeed StaffHi, I’m Crystal, a Senior Editor based in Los Angeles and creator of BuzzFeed’s “That Got Dark” newsletter. Huedoku is a daily color puzzle with simple rules and a satisfying solve. It's like sudoku, but with colors instead of numbers. Sign up here to get notified every time we publish a new Huedoku! Have a great weekend — Huedoku #39 drops Monday! 🌈 🌈 New Huedoku drops every weekday at 4:00 a.m. PT / 7:00 a.m. ET. 🧩🗂️ Huedoku Archive — Every past puzzle, all in one place! Comments
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Jun 5, 2026 · via buzzfeed.com
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Jun 4, 2026 · via youtube.com
Figures Abstract Life on Earth has evolved into a staggering diversity of species, most of which still remain undiscovered, unrecognized, or unmonitored. As our ocean’s richest biodiversity hotspot, coral reefs harbor more than one third of marine biodiversity, but many reef species are small and cryptic and, therefore, difficult to identify and study. Among these, tiny bottom-dwelling (‘cryptobenthic’) fishes have been highlighted as a highly diverse (>3,000 species), understudied, and ecologically important group. However, the classification and monitoring of these fishes depend almost exclusively on the knowledge of few expert scientists, which has resulted in limited knowledge concerning the taxonomy, distribution, and population trends of these fishes. Deep learning-driven image classification—known for its ability to learn complex patterns in visual data—is an ideal candidate for automating taxonomic image classification and therefore broaden participation in ecological monitoring and biodiversity science. We developed CryptoVision, a new taxonomy-aware convolutional neural network with three output heads that explicitly considers taxonomic hierarchies (family, genus, species) and their biological constraints. Built on ResNet50v2 and enhanced with Squeeze-and-Excitation modules, CryptoVision employs a custom taxonomy-focal cross-entropy loss and four hierarchical fusion strategies (standard, concatenation, gating, attention) to assess the algorithm’s performance. Trained on a unique dataset of ~7,600 laboratory-standard and ~18,800 web-sourced images covering 113 species of small reef fishes, our tool highlights the power of integrating deep learning with innovative, taxonomically-informed design and high-resolution imagery. Indeed, CryptoVision achieved a ~ 25% improvement across all metrics when lab-standard imagery was incorporated and among the fusion variants, the gating approach delivered the best calibration (expected calibration error ≈ 0.01) and 90.5% average precision. Finally, guided saliency map analyses of species in the dwarfgoby genus Eviota illustrate that model attention can align with expert-defined morphological traits that represent critical features for species delimitation. Our results demonstrate that taxonomy-aware, multi-output deep
Jun 4, 2026 · via journals.plos.org
Gandhinagar, December 8-10, 2022
The Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) is Indiaâs premier conference in Computer Vision, Graphics, Image Processing and related fields. Starting in 1998, it was a biennial international conference till 2021, providing a forum for the presentation of technological advances and research findings in these areas. ICVGIP 2022, the 13th conference in this series, is being organized by IIT Gandhinagar in association with the Indian Unit for Pattern Recognition and Artificial Intelligence (IUPRAI), an affiliate of the International Association for Pattern Recognition (IAPR). ICVGIP will be held annually from 2022 due to the huge growth in the community.
ICVGIP is dedicated to fostering the community of computer vision, graphics and image processing researchers and enthusiasts in India and abroad. We strive to live up to this goal at every occurrence of this annual conference.
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🔗 Best Paper Awards
🔗 Dance Performance
(Date: 9 Dec 2022, Time: 7PM-8PM, Venue: Jasubhai Memorial Auditorium)
Jun 4, 2026 · via events.iitgn.ac.in
JACKSONVILLE, Fla. — New details are emerging in the case of a North Carolina man who spent more than 50 days in jail after authorities identified him as a suspect in a Jacksonville crime he did not commit. The case began with a report of a stolen vehicle and surveillance video captured at a Publix on Baymeadows Road. Jalil Richardson said investigators never properly verified whether he was even in Florida before identifying him as a suspect. “There was no proper investigation done, um, to even reach out to me or to see if I was even in Florida,” Richardson said. >>> STREAM ACTION NEWS JAX LIVE <<< The State Attorney’s Office said an 85% facial recognition match and two eyewitness identifications were enough to establish probable cause against Richardson. However, prosecutors later dropped the case after evidence showed he was hundreds of miles away in North Carolina at the time of the crime. “And I sat in there for over 50 days in the most worst jail ever,” Richardson said. The State Attorney’s Office told Action News Jax it has identified two cases in which AI facial recognition technology used by the Jacksonville Sheriff’s Office helped develop the wrong suspects. One was Richardson’s case. The other involved Robert Dillon, whose case was also dropped for similar reasons. “The technology is simply too dangerous for law enforcement to be using at all,” said Adam Schwartz, privacy litigation director for the Electronic Frontier Foundation. Schwartz, who has practiced law for 30 years, pointed to a list compiled by the American Civil Liberties Union documenting wrongful arrests nationwide linked to facial recognition errors. [DOWNLOAD: Free Action News Jax app for alerts as news breaks] “More than a dozen innocent people have been arrested by police because of errors with face recognition,” Schwartz
Jun 4, 2026 · via actionnewsjax.com
JACKSONVILLE, Fla. — New details are emerging in the case of a North Carolina man who spent more than 50 days in jail after authorities identified him as a suspect in a Jacksonville crime he did not commit. The case began with a report of a stolen vehicle and surveillance video captured at a Publix on Baymeadows Road. Jalil Richardson said investigators never properly verified whether he was even in Florida before identifying him as a suspect. “There was no proper investigation done, um, to even reach out to me or to see if I was even in Florida,” Richardson said. >>> STREAM ACTION NEWS JAX LIVE <<< The State Attorney’s Office said an 85% facial recognition match and two eyewitness identifications were enough to establish probable cause against Richardson. However, prosecutors later dropped the case after evidence showed he was hundreds of miles away in North Carolina at the time of the crime. “And I sat in there for over 50 days in the most worst jail ever,” Richardson said. The State Attorney’s Office told Action News Jax it has identified two cases in which AI facial recognition technology used by the Jacksonville Sheriff’s Office helped develop the wrong suspects. One was Richardson’s case. The other involved Robert Dillon, whose case was also dropped for similar reasons. “The technology is simply too dangerous for law enforcement to be using at all,” said Adam Schwartz, privacy litigation director for the Electronic Frontier Foundation. Schwartz, who has practiced law for 30 years, pointed to a list compiled by the American Civil Liberties Union documenting wrongful arrests nationwide linked to facial recognition errors. [DOWNLOAD: Free Action News Jax app for alerts as news breaks] “More than a dozen innocent people have been arrested by police because of errors with face recognition,” Schwartz
Jun 4, 2026 · via actionnewsjax.com
SANTIAGO, Chile, and BOSTON, June 04, 2026 (GLOBE NEWSWIRE) -- Classiq and Pontificia Universidad Católica de Chile (UC Chile) today announced a joint research project to develop hybrid quantum algorithms for biomedical image analysis, assisted by classical machine learning and the NVIDIA CUDA-Q platform for quantum-classical computing. The 12-month engagement, titled “Enhancing Pathology through Quantum Computing,” is funded through Avanza UC 2025, the Internal Research and Creation Competition of UC Chile. To the collaborators’ knowledge, it is the first announced consortium in Latin America to combine quantum computing, machine learning and computational pathology. The engagement marks quantum computing’s and Classiq’s growing presence in Latin America and reflects the company’s expanding work with academic, research and public-sector institutions, including in health innovation. It also reinforces Chile’s emerging role in quantum computing, AI and advanced technology development. A Media Snippet accompanying this announcement is available by clicking on this link. Quantum machine learning applies quantum computing methods to machine learning problems, including classification, pattern recognition and complex data analysis. The initial project focus is on renal pathology, an area of growing public health importance in Chile and across Latin America. This includes applying quantum machine learning to computational pathology, with an initial emphasis on kidney lesion classification, automated glomerular segmentation and semantic pattern search across full histological slides. The work will be conducted in collaboration with Dr. Luciano Rebouças and Dr. Washington Conrado, researchers at Fundação Oswaldo Cruz (FIOCRUZ) and professors/researchers at Universidade Federal da Bahia (UFBA) in Brazil, combining expertise in digital pathology, computer vision and biomedical data analysis using curated histopathology datasets, provided by the Brazilian institutions. The research will leverage the Classiq quantum computing software platform and the NVIDIA CUDA-Q platform to leverage a seamless workflow from algorithm development through to simulation and execution. “Latin America has the scientific
Jun 4, 2026 · via markets.businessinsider.com
Wired found code for an unreleased facial recognition feature in Meta's AI app Meta was previously reported to be exploring facial recognition for its smart glasses. Code for a facial recognition feature that can run on Meta smart glasses is buried in the company's Meta AI app, according to a new report from Wired. While not currently enabled, accessible to customers or part of a formerly announced feature, the code appears to be further evidence that Meta is considering how facial recognition could work with its smart glasses, as The New York Times first reported in February. The feature, called "NameTag" in the code Wired found, is reportedly capable of capturing people's faces using the company's smart glasses and later notifying the wearer when it recognizes a previously captured face. No part of NameTag is currently running or sending biometric data to Meta's servers today, according to a security researcher who reviewed the code Wired found, but past versions of the Meta AI app have included interface elements for the feature, like a "Connections" menu that suggests users "remember the people you met." Anonymous Meta sources who spoke to The New York Times similarly referred to the company's facial recognition tool as "Name Tag." Per a memo reviewed during reporting, Meta was interested in launching the feature during a "dynamic political environment" in the US because "civil society groups that we would expect to attack us would have their resources focused on other concerns." While there are potential accessibility benefits to a pair of smart glasses that can identify faces for users with visual impairments, the feature poses serious ethical concerns, too. "Regardless of any sensational reporting, the facts are simple: we've said before we're exploring these types of features, and what you're seeing is just evidence of that exploration,"
Jun 4, 2026 · via engadget.com
Meta has deployed facial recognition code to millions of their always-on surveillance glasses, according to new reporting by Wired. EFF’s Threat Lab was able to confirm that the facial recognition code is present through static analysis of the application. This dangerous new Meta functionality stores faceprints as a series of 2,048 numbers uniquely representing the positioning of a person’s facial features. When this feature is activated, it will convert every new face in the sightlines of the surveillance glasses into a series of numbers, and compare it to all the existing faceprints in the user’s database. Wired and EFF confirmed that the code is present and active, though not yet exposed to consumers. Another researcher confirmed that when they manually added a face to the app database by connecting the phone to a computer in debug mode and issuing a few commands, the glasses would subsequently detect that face when it came into view. Meta has already paid $650 million to settle a BIPA lawsuit challenging mass facial recognition of every photo posted to its platform, a feature which it has since shut down. Despite the billions of reasons not to, Meta seems to have created the capacity to turn their customers into a distributed surveillance machine. This is just one more reason to think twice before buying or using Meta’s surveillance glasses. Considering that Meta previously wrote in an internal document that they want to launch facial recognition “during a dynamic political environment where many civil society groups that we would expect to attack us would have their resources focused on other concerns," this invasive new feature doesn't come as a surprise. But Meta's surveillance plans won't escape public scrutiny that easily, and we'll be watching if this feature is rolled out to the public.
Jun 4, 2026 · via eff.org