Meta keeps working to add facial recognition to its platforms and AI-powered smart glasses — and it keeps facing massive pushback.
A recent story in WIRED confirmed that a phone app for Meta’s Ray-Ban smart glasses included an unreleased feature called NameTag that could biometrically identify anyone in view of the glasses without their consent.
Tech expert Omar Gallaga says Meta has removed the software, which also sparked concern over a connection to a defense contractor.
Highlights from this segment:
– A WIRED investigation found the NameTag feature, which had not yet been deployed by Meta, in the Meta AI app that’s used to configure its smart glasses.
– Journalists also discovered a software license in the app for a tool from Rank One Computing, a company that provides facial recognition software to the military and law enforcement. Meta would not comment on their relationship to Rank One.
– Meta has attempted to include facial recognition and tagging software on its social platforms in the past, which led to pushback rom civil liberties advocates and users.
Jun 18, 2026 · via texasstandard.org
Artificial intelligence (AI) is a branch of computer science that lets machines perform tasks that normally require human intelligence, like learning, reasoning, problem-solving, recognizing patterns and making decisions. Put more simply, AI is software that learns from data and uses what it learns to make predictions, decisions or new content without being explicitly programmed for each task. Today’s AI runs everything from spam filters and recommendation engines to chatbots like ChatGPT and image generators. It draws on a range of techniques, most notably machine learning and generative AI, and it has moved from research labs into products people use every day. Stanford computer scientist Fei-Fei Li, writing in the Stanford Emerging Technology Review, places AI in the same category as the most transformative technologies in modern history: “AI is a foundational technology that is advancing other scientific fields and, like electricity and the internet, has the potential to transform how society operates.” Adoption is now scaling across every sector, from healthcare and financial services to retail and manufacturing, and the pace is accelerating. This page covers how AI works, the main types of AI, real-world examples, the limitations to watch for and a brief history of the field. Think of AI as teaching a computer by example instead of writing step-by-step instructions. Show a system thousands of photos of cats and it learns to recognize cats on its own, not because someone told it that cats have whiskers and pointed ears, but because it has seen enough examples to figure out the pattern. AI is not “thinking” the way you or I do. It is finding patterns in data and using those patterns to make a best guess. That distinction matters: AI can get remarkably good results in narrow domains, but it does not understand anything in the human sense.
Jun 18, 2026 · via databricks.com
Rep. Hiner Votes in Support of Medicaid Program Integrity and Fraud Prevention Act State Representative Mark Hiner (R-Howard) voted in support of a comprehensive legislative package aimed at fighting fraud, waste and abuse within Ohio’s Medicaid program with the goal of protecting taxpayer dollars. The Ohio Medicaid Program Integrity and Fraud Prevention Act works to strengthen oversight and accountability within the system, ensure transparency, target high-risk providers to ensure quality care, boost fraud reporting requirements, implement guardrails around home-health services, and enhance penalties for Medicaid fraud. Senate Bill 315 was amended to include an extensive, targeted list of key reforms that work to prevent fraud, detect fraud and increase penalties for committing fraud within Medicaid. Preventing Fraud - Delivers transparency within the provider enrollment process by requiring the Ohio Department of Medicaid (ODM) to conduct in-person inspections before approving any new providers for home and community-based care. - Triggers an investigation if a provider seeking enrollment utilizes the same address or other similarities as another provider. - Requires ODM to establish criteria for classifying high-risk providers, allowing them to impose a temporary payment suspension and conduct an investigation if there is a suspicious increase in claims. - Requires that an alternative payer analysis be conducted prior to payment of all Medicaid claims. This will ensure that Medicaid is the payor of last resort in these scenarios. - As a condition of entering into or revalidating a Medicaid provider agreement, requires each person or government entity to disclose the identity of each person with at least a 5% direct or indirect ownership interest in the person or entity, which ODM shall verify. - Maintains options for home caregivers to provide personal care services. Detecting Fraud - Enhances the electronic verification of in-home personal care services by requiring ODM to maintain a
Jun 18, 2026 · via ohiohouse.gov
News — Met releases 14 images as 16 May protest investigations continue Detectives investigating alleged offences during protests in central London on Saturday, 16 May have released images of 14 people they want to identify. There were 43 arrests on the day, which saw protests organised by the Palestine Coalition and other groups to mark the anniversary of the Nakba and a protest organised in the name of Stephen Yaxley-Lennon under the ‘Unite the Kingdom’ banner. Five people have been charged so far (details below) and detectives are continuing to investigate a number of further offences including 20 alleged hate crimes. Some of those – for example incidents of chanting – may involve multiple suspects. Officers have already sent a number of files to the Crown Prosecution Service for early investigative advice and they expect to submit further files for consideration in the near future. Chief Superintendent Clair Haynes, who commanded the policing operation on 16 May, said: “We have always said that the policing of protest doesn’t stop when everyone goes home. “There are often many more protesters than there are officers at these events, which combined with the scale of the crowds means it is impossible for every offence to be seen and dealt with in the moment. “Detectives from our Public Order Crime Team painstakingly review footage from events to spot offences and identify those they believe to be involved. “The footage and images are compared against police databases using retrospective facial recognition technology, but where we are unable to find a match we will turn to the public for their help. “I’d urge anyone who recognises someone in the 14 photos released today to come forward, that includes anyone who recognises themselves. Our officers need to speak to you.” Anyone with information is urged to call
Jun 18, 2026 · via news.met.police.uk
U.S. Air Force Col. Dustin Merritt, left, 493rd Fighter Squadron commander, and U.S. Air Force Chief Master Sgt. Paul Fletcher, 493rd Fighter Generation Squadron senior enlisted leader, address Airmen during a superior performers recognition all-call at Pirkkala Air Base, Finland, June 18, 2026. Leadership recognized individuals who distinguished themselves from the pack through proactive airmanship, exceptional leadership and a constant drive to elevate the team during Ramstein Flag 26. (U.S. Air Force photo by Tech. Sgt. Christine Groening)
| Date Taken: | 06.17.2026 |
| Date Posted: | 06.18.2026 12:55 |
| Photo ID: | 9759771 |
| VIRIN: | 260618-F-WZ808-2004 |
| Resolution: | 6048x4024 |
| Size: | 5.95 MB |
| Location: | PIRKKALA (BIRKALA), FI |
| Web Views: | 11 |
| Downloads: | 0 |
This work, 493 FS, FGS leadership recognize superior performers during RAFL26 [Image 7 of 7], by TSgt Christine Groening, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
Jun 18, 2026 · via dvidshub.net
Identifying pills accurately is essential for medication safety and proper usage, especially when tablets or capsules are unlabelled or difficult to distinguish -- PillCap AI is an AI-powered tool designed to identify pills instantly using photo recognition. Users simply take a photo of a pill, and the system analyzes visual features such as shape, color, markings, and size to generate a likely match. This helps users quickly understand what a medication may be and reduces the risk of confusion or misidentification. The platform is designed to provide fast, accessible results that support better medication organization and awareness. It can be especially useful for caregivers, patients managing multiple prescriptions, or situations where pill identification is uncertain. PillCap AI focuses on improving safety and confidence in medication handling. By turning a simple photo into actionable identification results, it helps users take more informed steps in managing their health responsibly. Image Credit: PillCap AI What's Driving This Trend - AI Medication Recognition - Photo-based identification systems are expanding medication safety by turning everyday smartphone cameras into accessible tools for recognizing pills and reducing uncertainty. - Caregiver Health Automation - Digital assistants for medication management create new value in home care by supporting caregivers who oversee complex prescription routines for aging or dependent patients. - Visual Pharmacy Intelligence - Computer vision applied to pill attributes such as color, shape, size, and markings introduces scalable ways to improve verification, adherence, and pharmaceutical data access. Who This Affects Most - Digital Health - AI-powered medication tools strengthen patient-facing health platforms by making clinical information easier to access in moments of confusion or risk. - Pharmaceutical Technology - Image recognition for pill identification connects drug databases with real-world usage, opening new possibilities for safer dispensing, packaging, and post-market support. - Elder Care - Medication identification platforms are
Jun 18, 2026 · via trendhunter.com
Clearview AI contract links Army special forces to wider intelligence ecosystem A small U.S. Army special forces purchase of Clearview AI facial recognition licenses has exposed a broader defense intelligence pipeline connecting biometric search, commercial data, AI-enabled entity resolution, former U.S. intelligence personnel, and a company that is building a separate Pentagon platform for operational data fusion. Biometric Update reported in February on the underlying Army special forces Clearview solicitation and renewal. Independent journalist Jack Poulson later reported that Octaris Technologies served as the intermediary for the March purchase, identifying the Virginia Beach, Virginia company as the vendor on the award. Separately, Biometric Update reported in January that USSOCOM was laying the groundwork for a broader expansion of battlefield identity intelligence and exploitation capabilities. The USSOCOM request for information sought industry input on facial recognition, voice identification, tactical site exploitation tools, rapid DNA analysis, and AI and machine-learning analytics, underscoring that the Clearview purchase sits within a larger special operations push toward identity-driven intelligence. Procurement records [here and here] identify Octaris as the vendor on a March award for Clearview AI service for the 1st Special Forces Command (Airborne), the Fort Bragg-based Army special operations headquarters that includes the Army’s various special forces groups. The 1st Special Forces Command is subordinate to the U.S. Army Special Operations Command, the largest component of USSOCOM. The award summary lists a total potential contract value of $339,415. The summary identified $78,750 as the March 16 purchase order amount for five Clearview AI licenses, which appears to correspond to the base-year obligation rather than a separate transaction. The base period runs from March 20, 2026, to March 19, 2027, with three one-year option periods that could extend the subscription through March 19, 2030. A February memorandum for the record describes the requirement as a
Jun 17, 2026 · via biometricupdate.com
MILTON — When naturalist Laurie DiCesare spotted a tiny blue butterfly in St. Albans six years ago, she almost missed it. The insect turned out to be the first documented European common blue butterfly recorded in Vermont, a discovery confirmed through photographs and identification work shared on the citizen-science platform iNaturalist. Now, DiCesare hopes Milton residents will make discoveries of their own. The Milton Conservation Commission is inviting community members to participate in the town's first BioBlitz, a community science event which will challenge participants to document as many species of plants, animals, fungi and insects as possible between July 18 and Aug. 2 using the free iNaturalist app. The project is designed to create a growing database of local biodiversity while encouraging residents to explore Milton's parks, forests and natural areas. "The idea is to document as many species as you can," DiCesare said. "Anything you find within that time period will go toward our database." Participants can submit photographs through iNaturalist, an online platform used by amateur naturalists, researchers and conservation organizations around the world. The app uses image recognition technology to suggest species identifications, while a community of users helps verify observations. The information collected during the BioBlitz will contribute to a broader understanding of what species live in Milton and could help inform future conservation efforts. "You have to know something's rare to protect it," DiCesare said. The event will center around a BioBlitz weekend July 25-26, featuring naturalist-led walks at several of Milton's conservation areas, including the Milton Town Forest, Eagle Mountain Natural Area and the Lamoille Riverwalk. DiCesare said the walks are designed to be accessible and slow-paced, allowing participants of all ages and experience levels to take part. "We've got different wetlands, woodlands and fields, so different habitats is a good thing," she
Jun 17, 2026 · via miltonindependent.com
CardSight AI Brings AI-Powered Identification to Magic: The Gathering, Expanding Its Trading Card Game Lineup CardSight AI Brings AI-Powered Identification to Magic: The Gathering, Expanding Its Trading Card Game Lineup Press Release Date 06-17-2026 CardSight AI adds full Magic: The Gathering identification to its trading card API, giving developers the infrastructure to build new innovative TCG apps PORTLAND, ME, UNITED STATES, June 17, 2026 /EINPresswire.com/ -- CardSight AI, Inc. today announced that Magic: The Gathering card identification is now live in production on its trading card API, bringing the company's industry-leading trading card identification to the longest-running trading card game still in publication. The company's AI identification system recognizes Magic: The Gathering trading cards from a single photo and returns structured catalog data and card images, delivering the unmatched accuracy and performance that app builders and existing platforms depend on. The launch adds Magic: The Gathering to CardSight AI's growing trading card game lineup alongside Pokemon, continuing the company's expansion beyond sports cards. The launch pairs visual identification with full catalog coverage. CardSight AI's Magic: The Gathering catalog spans every set in the game's history: over 250 releases reaching from 1993's Alpha, the set that started the modern hobby, through Secrets of Strixhaven in 2026. Each identified trading card returns with its catalog information and card image through the same API that already powers identification for Baseball, Football, Basketball, Hockey, and Pokemon. "Magic: The Gathering is the longest-running trading card game still in publication, with a large and dedicated player base, and builders have been asking us to support it," said Eric Nusbaum, CEO and co-founder of CardSight AI. "Adding Magic to our growing trading card game support means anyone with an idea for a Magic app can build on infrastructure that already handles identification and catalog data for them.
Jun 17, 2026 · via natlawreview.com
Insights on Canadian Society Workplace artificial intelligence use: A profile of sociodemographic and job characteristics Text begins Overview of the study Using data from the Canadian Survey on Working Conditions, this article provides a profile of workers aged 15 to 69 who used artificial intelligence (AI) and automation technologies at work during the previous year. The article focuses on generative AI which refers to tools trained on large datasets that are used to create new content and to support tasks such as answering questions and problem-solving. Examples of Generative AI tools include ChatGPT and Google Gemini. - Generative AI was the most prevalent AI technology used at work from September 2024 to July 2025. - The proportion of workers who used generative AI nearly doubled over the survey period, increasing from 17% in September 2024 to 30% in July 2025. - Workers in three industries—professional, scientific and technical services; educational services; and finance, insurance, real estate, rental and leasing—made up one-quarter of workers overall (25%) but represented half of generative AI users (49%). - Workers with a bachelor’s degree or higher were five times more likely to have used generative AI in the last 12 months (37%) than those with a high school diploma or a lower level of education (7%). Introduction Artificial intelligence (AI) and automation technologies are increasingly being integrated into Canadian workplaces, changing the way tasks are performed, decisions are made, goods are produced and services are Although a growing body of research has focused on the organizational adoption of AI, comparatively little is known about the prevalence of AI use among workers and the characteristics of those This study uses data from the Canadian Survey on Working Conditions, which were collected from September 2024 to July 2025. It provides a sociodemographic and job characteristic profile of
Jun 17, 2026 · via www150.statcan.gc.ca
Growing Demand for Real-Time Processing, Privacy, and Intelligent Devices Fuels Market Expansion SAN FRANCISCO, June 17, 2026 /PRNewswire/ -- The global on-device AI market is entering a new era of accelerated growth as enterprises and consumers increasingly prioritize real-time intelligence, privacy-focused computing, and low-latency digital experiences. According to recent industry analysis by Grand View Research, the global on-device AI market was valued at USD 10.76 billion in 2025 and is projected to reach USD 75.51 billion by 2033, registering a CAGR of 27.8% from 2026 to 2033. The market is witnessing substantial momentum as artificial intelligence capabilities move beyond centralized cloud infrastructure and become embedded directly into devices. From smartphones and wearables to connected vehicles and industrial equipment, organizations are leveraging on-device AI to improve responsiveness, reduce network dependency, and enhance data security. Shift Toward Edge Intelligence Accelerates AI Adoption Artificial intelligence deployment strategies are rapidly evolving. Businesses are increasingly recognizing the benefits of processing data directly on devices rather than relying solely on cloud-based systems. On-device AI enables applications to perform inference locally, allowing devices to respond instantly to user interactions while minimizing latency. This capability has become particularly valuable for applications requiring real-time decision-making, including voice assistants, image recognition, predictive maintenance, navigation systems, and smart automation. The continued expansion of connected devices and edge computing ecosystems is creating strong demand for localized AI capabilities. As enterprises seek faster and more reliable digital operations, on-device AI is becoming a critical component of next-generation technology infrastructure. Privacy and Data Security Become Strategic Priorities One of the most significant factors supporting market growth is the increasing emphasis on privacy and data protection. Organizations across industries are facing mounting regulatory requirements and consumer expectations regarding how personal information is collected, processed, and stored. By keeping sensitive data on the device rather than
Jun 17, 2026 · via prnewswire.co.uk
Figures Abstract Accurate classification of terrestrial habitats is critical for biodiversity conservation, ecological monitoring, and land use planning. Several habitat classification schemes are in use, typically based on analysis of satellite imagery and validation by field ecologists. Here, a methodology is presented for classification of habitats based solely on ground-level imagery (photographs), offering improved validation and enhanced ability to classify habitats at scale (e.g., using imagery from citizen science). In collaboration with Natural England, a public sector organisation with responsibility for nature/biodiversity conservation in England, this study develops a classification system that applies deep learning to ground-level habitat photographs, categorising each image into one of 16 distinct classes following the established ‘Living England’ framework. Images were pre-processed using resizing, normalisation, and augmentation techniques, while resampling was used to balance classes in the training data and enhance model robustness. A custom deep learning classifier based on the DeepLabV3-ResNet101 architecture was developed and fine-tuned to assign a habitat class label to ground-level photographs. Using five-fold cross-validation, the model demonstrated strong overall performance across 16 habitat classes, with accuracy and F1-scores varying between classes. This approach supports robust, scalable habitat classification based on balanced and well-prepared training data. Across all folds, the model achieved a mean F1-score of 0.63, with some habitat classes such as Bare Sand (BS) and Coniferous Woodland (CW) reaching values above 0.87. High performance was achieved for visually distinct habitats and lower performance for visually mixed or ambiguous classes. These findings demonstrate the potential of this approach for ecological monitoring. Ground-level imagery is easily obtained and accurate computational methods for habitat classification based on such data have many potential applications. To support use by practitioners, a simple web application is also provided that allows classification of uploaded images using the trained model. Citation: Tourian M, Vandaele R, Rowlands S,
Jun 17, 2026 · via journals.plos.org
Redditors Spent Years Trying to Find Mysterious Photo Known as ‘Celebrity Number Six’ An innocent Reddit post asking for help identifying the face of a mystery celebrity would spark a four-year-long international search involving facial recognition technology and photo copyright infringement. As Boing Boing reported yesterday, the wild story — that became known as “Celebrity Number Six” — began in 2020 when a Finnish Reddit user posted a photo of curtains that had eight famous faces on them. Reddit quickly identified all the celebrities, including Orlando Bloom, Jessica Alba, and Josh Holloway. All except one face. The Search for Celebrity Number Six As the source photo for each famous face was tracked down, number six continued to evade the Reddit sleuths, who couldn’t even agree on the gender of the person. The original post was shared to r/TipOfMyTongue, but the search for number six widened to other subreddits and, eventually, r/CelebrityNumberSix was created to focus efforts. According to Wikipedia, one Redditor searched through every picture taken by a photographer-of-interest between 1998 and 2007 on the Getty Images archives in a bid to find number six. But no luck. The community began keeping spreadsheets of all the possible celebrities it could be. Popular guesses included Olivia Wilde or Taylor Kitsch, but no source photo could be found. Leticia Sardá A Reddit user took the image from the curtains, colorized it, and then ran it through facial recognition website PimEyes. The tool returned a prominent name: Leticia Sardá. A Spanish Reddit user and member of r/CelebrityNumberSix contacted photographer Leandre Escorsell, a fellow Spaniard who photographed Sardá. Escorsell was shown the image and recognized it immediately. Escorsell expressed disappointment that his photo had been used on the fabric without permission, but he sent over the original photo to put the mystery to bed
Jun 17, 2026 · via petapixel.com
Back to Journals » Clinical Interventions in Aging » Volume 21 Artificial Intelligence for Osteoporosis Diagnosis, Risk Prediction and Therapy: Current Advances, Clinical Challenges, and Future Perspectives Authors Zhang Z, He Y , Mo Z, Zhang P, Tian Z, Huang L Received 5 March 2026 Accepted for publication 4 June 2026 Published 18 June 2026 Volume 2026:21 607232 DOI https://doi.org/10.2147/CIA.S607232 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 3 Editor who approved publication: Dr Maddalena Illario Zhaochen Zhang,1,* Yuxi He,2,* Zhanhao Mo,3,* Peng Zhang,4 Zhenya Tian,5 Lanfeng Huang1 1Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 2Department of Ophthalmology, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 3Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 4Department of Radiology, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 5The First Norman Bethune Clinical Medical College, Jilin University, Changchun, Jilin, People’s Republic of China *These authors contributed equally to this work Correspondence: Lanfeng Huang, Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, People’s Republic of China, Email [email protected] Abstract: Osteoporosis (OP) is a chronic systemic skeletal disorder that predominantly affects the elderly. It is characterized by an imbalance in bone homeostasis, reduced bone mass, microarchitectural deterioration of bone tissue, and increased bone fragility, ultimately leading to a higher risk of fractures and related complications. With the progression of global population aging, the prevalence of OP continues to rise, underscoring the importance of early diagnosis and timely intervention. However, the diagnosis and management of OP—particularly its early detection—remain limited by material constraints such as diagnostic equipment and by subjective factors including clinician experience, which hinder widespread screening. In recent years, artificial intelligence (AI)
Jun 17, 2026 · via dovepress.com
Local TV station operator Sinclair is going to let viewers interact with its on-air programming — and ads — in a new way under a partnership with IRCODE. Sinclair has made a strategic investment in IRCODE, a computer vision and AI company that claims its system makes TV interactive and shoppable in real time. The amount of the investment isn’t being disclosed. Other IRCODE investors include Craig Kallman, former chairman and CEO of Atlantic Records who recently was named chief music officer of Warner Music Group. Alongside the investment, Sinclair will roll out IRCODE-powered interactive television at its stations in Salt Lake City and Austin beginning in July 2026, with additional markets to follow through the year. The deployments will let the stations make interactive television a native capability inside its own platforms. Popular on Variety According to IRCODE, its real-time image recognition system works like “Shazam for images.” It identifies what is on screen (without QR codes) and connects the viewer to relevant content and commerce. In Sinclair’s implementation, viewers can open the app for the local Sinclair station and point their phone at the TV. At that point, the app kicks off an action to let the viewer purchase a product, enter to win a sweepstakes or link to additional info. Because it happens inside the station’s app, the viewer is identified and opted in, and every step from first scan to conversion is captured as first-party data. For example, advertisers running spots on Sinclair’s stations in Salt Lake City or Austin can now measure who engaged, what they did next, and whether it led to a purchase. Using their smartphone cameras and the Sinclair app, viewers can participate in real-time polls, comment on local news and interact with advertisers, said Del Parks, president of technology. “IRCODE is
Jun 17, 2026 · via variety.com
SNS has published a guide addressing growing demand for AI-powered video indexing, transcription, facial recognition, and searchable metadata across media libraries, positioning its AI Suite platform as an on-premise solution to these requirements. The SNS AI Suite performs automatic speech-to-text transcription with multi-language translation, multi-speaker diarization, facial recognition and identity mapping, custom AI model training for specific faces and voices, object and scene detection, OCR text extraction from on-screen graphics, and natural language search across indexed metadata. All processing runs on-premise under a flat perpetual license with unlimited processing hours, without cloud processing fees or external data transmission. The guide contrasts on-premise AI processing with cloud-hosted alternatives, citing two primary concerns with cloud approaches for organizations processing large video volumes: unpredictable cost scaling as processing volume grows, and data exposure when proprietary footage or biometric information is transmitted to external platforms. Key evaluation criteria the guide recommends for organizations selecting an AI media indexing system include custom training capability, scalability, licensing model predictability, and on-premise versus cloud architecture. All AI-extracted metadata — including transcripts, speaker logs, face mappings, object tags, and scene descriptions — is indexed into a searchable on-premise database with timecode-level precision. The AI Suite includes an API for integration with external MAM and DAM systems at no additional charge and can be deployed alongside EVO or existing storage infrastructure. More information and demo access is available at snsevo.com.
Jun 17, 2026 · via sportsvideo.org
25 Years of Inspection Technology: What Has Changed, What Hasn’t, and What Still Matters Twenty-five years of transition from paper clipboards to AI image recognition have drastically accelerated inspection speed, yet checkbox fatigue and unresolved hazards remain. - By Naaman Shibi - Jun 17, 2026 Cast your mind back to 1999. Most workplace inspections were done on paper. Clipboards, carbon copies, filing cabinets. A completed checklist was folded, handed to a supervisor and often never looked at again unless something went wrong. Deficiencies lived in a drawer. Follow-up was whoever remembered to follow up. A lot has changed since then. And some things, frustratingly, haven’t changed at all. What Has Changed The Medium The most visible shift has been the move from paper to digital. Over the past 25 years, clipboards gave way to PDAs, PDAs gave way to tablets and smartphones, and smartphones gave way to purpose-built mobile applications designed specifically for field data collection. Today, an inspector on a mine site, a construction scaffold or a warehouse floor can complete a structured inspection, photograph a deficiency, assign a corrective action and submit a report before they have walked back to the site office. That workflow used to take days. The Data Paper inspections produced records. Digital inspections produce data. That distinction matters more than it might first appear. A paper record tells you what happened at a point in time. Digital data, accumulated across hundreds or thousands of inspections, tells you what is happening across your entire operation. Trends become visible. Patterns emerge. You can see that the same piece of equipment fails its pre-start check every third Monday, or that one particular site consistently generates corrective actions that are never closed. That kind of insight was impossible to extract from a filing cabinet. Speed And Accountability The
Jun 17, 2026 · via ohsonline.com
U.S. Army Spc. Peter Wenzel, with bravo company, 628th Aviation Support Battalion, 28th Expeditionary Combat Aviation Brigade, is awarded the Army Commendation Medal and a commemorative plaque in recognition of winning both the brigade and state Best Warrior Competitions. (U.S. Army National Guard photo by Command Sgt. Maj. Jeff Huttle)
| Date Taken: | 06.12.2026 |
| Date Posted: | 06.17.2026 11:22 |
| Photo ID: | 9745396 |
| VIRIN: | 260612-Z-A3544-8060 |
| Resolution: | 4032x3024 |
| Size: | 3.89 MB |
| Location: | FORT INDIANTOWN GAP, PENNSYLVANIA, US |
| Web Views: | 1 |
| Downloads: | 1 |
This work, ARCOM award [Image 3 of 3], must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
Jun 17, 2026 · via dvidshub.net
Evan Spiegel doesn't want you to call Snap Specs AI glasses Snap's CEO sat down with Engadget after his keynote at AWE. Snap's newly announced AR Specs might seem similar to other smartglasses, but Snap CEO Evan Spiegel says that's the wrong way to think about the product. Specs, he says, is "a new type of computer, a see-through computer." Shortly after unveiling Specs at AWE, Spiegel sat down with Engadget to tell us more about the device we got a glimpse of onstage. The CEO repeatedly referred to Specs as a "computer" and that really is core to understanding how Snap is positioning the product (and justifying the price). Specs, Spiegel said, "is able to overlay computing on the world around you and bring computing into the world, which is so important if you want to make computing feel more human." But Snap will have to do more than just persuade people to buy a computer for their face. When Specs go on sale later this year, the company will face a very different environment than when it first started experimenting with camera-enabled glasses in 2016. For one, it has a lot more competition now. But today, there's also increasing suspicion of smartglasses, given that there have been some very public cases of people misusing the tech. There's the Meta of it all, too. The company was recently caught with an unreleased facial recognition feature on its Ray-Ban glasses (that it removed soon after outside researchers discovered it). Spiegel, not surprisingly, isn't a fan of facial recognition. "There are certain use cases, like facial recognition, that we don't allow in Lenses, and one of the benefits of having our own developer ecosystem and our own developer tools is that we're able to moderate the Lenses that are submitted and
Jun 16, 2026 · via engadget.com
Meta Ray-Bans have been under increased public scrutiny following revelations about the facial recognition work Meta has been doing on its smart glasses. Consumers are rightly wary of products that could convert wearable tech into everyday surveillance devices. In early June, an investigation by Wired exposed how Meta had quietly embedded code for dormant facial recognition software under the internal designation "NameTag." The feature, if rolled out, could have allowed Meta smart glasses to biometrically identify anyone in view -- in real time, without consent -- using a stored digital faceprint. The code, which was never made active for users, was removed a day later. The Electronic Frontier Foundation's Threat Lab verified the initial findings and reported that Meta reversed course following public blowback. But the privacy nonprofit noted that Meta deleting the code "does not equal a permanent change of heart." Now, just a week after Meta removed the code, the company is facing new questions about its facial recognition software prototype. A new investigation by Wired uncovered that Meta partnered with Rank One Computing, a supplier for the US military and law enforcement agencies, for its biometric identification technology. Wired said it uncovered a software license tying the Pentagon vendor to the Meta AI app, the same one used for Meta's smart glasses products. The license agreement would authorize Meta to use Rank One's military-grade facial recognition and "liveness detection," which confirms whether someone is seeing a live person or a mask or photo. This business relationship, as Wired pointed out, "shows how thin the line has grown between the surveillance technology sold to law enforcement and the military and the consumer products sold to everyone else." According to Wired, Rank One Computing declined to comment on the findings. The Denver-based firm, which earns roughly 80% of its
Jun 16, 2026 · via cnet.com