Pulp nonfiction A 404 investigation reveals that Amazon is buying used books in bulk and scanning them in a warehouse in Las Vegas—often destroying the texts in the process. • 3 min read TL;DR: For months, booksellers wondered why they were receiving bulk orders for a bunch of obscure used books. Now they may have an answer: An Amazon facility in Las Vegas appears to be processing used books and digitizing them, presumably to train its AI. What happened: 404 Media says it got a bookseller to plant an Apple AirTag in a book that was a part of a large order. The AirTag took a rather circuitous journey, from California to Milwaukee, then Colorado, before it arrived at an Amazon facility in Vegas. That facility contains a previously unknown warehouse called VGT3, marked by a logo of a menacing dinosaur gripping a book. There, workers spend their time scanning rare books—sometimes destroying them in the process. We don’t know much else about the operation: An Amazon spokesperson only confirmed to 404 that the company “purchases books through commercial channels to help develop and improve the products and services our customers use.” The “rare” used books mystery: Booksellers noticed the unprecedented uptick in used book sales because of the order sizes and the kind of books being purchased. The texts are considered “rare” because they cover niche topics and few copies remain—an example being How to Use Corel WordPerfect 1991, per one bookseller. So we’re not talking about a first-edition James Joyce. Still, the trend couldn’t definitively be connected to AI firms until now. Tech Brew breaks down the biggest tech news, emerging innovations, workplace tools, and cultural trends so you can understand what's new and why it matters. By subscribing, you accept our Terms & Privacy Policy. Not just
Aug 18, 2026 · via techbrew.com
By Lauren Wilkin Meta has filed a patent for new AI glasses that use facial recognition to capture moments without a command from the user - building up a searchable memory bank. The patent, filed by Meta on August 13, covers the invention of an AI assistant built into a pair of smart glasses that can decide what to capture, when and what to store as a 'memory' - all without the wearer's input. This means the glasses could record events without the wearer commanding them to, focusing on 'interesting' events based on facial expressions, conversations, behaviors and where the user is looking. The AI assistant would also build up a profile of relationships, based on facial recognition - pulling up certain records associated with each person the wearer interacts with. The patent says that the glasses could then "access a plurality of episodic memories associated with the user." In a real-world example, the glasses could capture moments throughout a dinner party, focusing on and zooming in on interesting conversations and events. At the end of the night, it could deliver a 'highlight' file to the wearer, containing videos and pictures captured throughout the evening. The wearer would also be able to ask the assistant "what happened at this time in the dinner party?" and the AI assistant would be able to play back the video footage captured. The patent says that determining what to capture is based on a measure of "interestingness" which can be influenced by what someone is doing, their facial expression, objects they're associated with, and even where the wearer is looking using "eye gaze data." This would mean wearers would have a searchable memory bank, where they are able to recall conversations and events through video and photos captured by the smart glasses. Importantly, this
Aug 18, 2026 · via nbcrightnow.com
Londoners are concerned about the rollout of facial recognition technology (FRT) due to worries about errors, privacy and surveillance, recent polling has revealed. Meanwhile the British Transport Police (BTP) has admitted its trial at railway stations, which has been running for six months, has caught no serious offenders as a result of using the technology, though they say the threshold has been set deliberately high in terms of the offenders it’s being used to find. 72 per cent of respondents to the polling in Greater London want the public to have a say on how FRT is used, while two-thirds worry errors could get people into trouble unfairly. Another 62 per cent are concerned about how images of faces will be stored, while half feel there is a risk of racial bias. The polling, carried out by Opinium earlier this year, comes amid the start of live facial recognition (LFR) cameras being rolled out at some London Tube stations. It was first deployed at Victoria Underground station as part of a trial that started in February, and will rotate between different stations until November. While the majority of Londoners – 70 per cent – support the use of FRT by police forces, more than half say it should only be deployed where there are a clear public benefit and strong safeguards in place. Tony Kounnis, CEO of Face Int, which commissioned the research, said: “It’s far too simplistic to say that people in London are for or against facial recognition. This research shows that it’s far more nuanced than that – people have specific and understandable concerns, particularly the accuracy of the technology, their own privacy, and the security of biometric data. “Public trust cannot be overlooked; nor is the efficacy of the technology enough. Organisations deploying FRT need to
Aug 18, 2026 · via standard.co.uk
The Delhi Police submitted this in an affidavit sworn by DCP Sachin Sharma, which stated the crowd turned violent and breached many layers of barricades in bid to march towards Parliament. On facial recognition software, Delhi Police said that the use of the technology was a proportionate policing measure. The affidavit said the software does not automatically capture the profiles of every individual present at the protest site, nor is it deployed for indiscriminate surveillance or collection of personal information of peaceful protesters unless they have a previous criminal record. The affidavit has been filed in response to petitions alleging police excesses against Cockroach Janta Party and other protesters at Jantar Mantar. Solicitor general Tushar Mehta told a three-member bench headed by CJI Surya Kant that the technology captures the faces of only those persons whose details are recorded in the crime database. The affidavit further claims that no action is taken solely on the basis of facial recognition software. Field verification is also carried out to ascertain whether the person in question was present at the site. Detailing the sequence of events, the affidavit said although permission for a dharna was granted only for June 20, post 5 pm, the protesters did not vacate the venue. The affidavit added the agitation escalated after a call was given for a march towards Parliament on July 20. It further said "permission was neither sought nor granted for any 'Chalo Sansad' march" and that prohibitory orders under Section 163 of BNSS had been in force in New Delhi since June 21.
Aug 18, 2026 · via economictimes.indiatimes.com
The recent use of artificial intelligence-equipped surveillance cameras by Montreal police is raising questions about privacy rights and how the technology will be used, as the use of similar cameras in the United States has become a major issue. The Genetec Cloudrunner cameras are similar to those made by company Flock Safety, an AI surveillance system widely used in the U.S. that has faced widespread public resistance. But how do the two types of cameras differ, and what information are the smart cameras providing to the Montreal police? The Gazette spoke with experts in AI ethics and a representative from Genetec to answer to growing concerns over automatic licence plate reading cameras. What, exactly, makes these cameras controversial? While traditional security cameras only create video, automated licence plate reading (ALPR) cameras can capture information about the type of car, colour of car, direction of travel, and the licence plate, explained Andrew Elvish, an executive at the Montreal-based company Genetec. “It’s looking at the outside of the vehicle. So it’s designed specifically to do that,” he said in an interview. In the U.S., the Flock cameras can tie the licence plate information to a person’s identity, which can be searched in a centralized database system shared between the camera operators. But according to Elvish, Genetec doesn’t have a central database shared with all the company’s camera users in the same way Flock does in the U.S. “We do not as a company sell access to data. Our business model isn’t predicated on aggregating and then selling data to customers, or giving customers as a benefit access to a vast amount of data,” Elvish said. It’s that shared database that’s caused so much concern in the U.S. “People don’t like surveillance. But when you tie surveillance to location, and you tie surveillance
Aug 18, 2026 · via montrealgazette.com
Figures Abstract Protecting facial recognition privacy is crucial amid deep fake threats, biometric risks, and third-party database access concerns. Despite many recent face recognition methods achieving high accuracy, most existing works either ignore privacy protection or apply privacy mechanisms without designing CNN structures that effectively learn from heavily perturbed facial data. This research introduces a secure face recognition system based on Differential Privacy (DP), employing a Convolutional Neural Network (CNN) and face classifiers. In this study, we develop a CNN through the incorporation of multiple batch normalization layers. This CNN is capable of recognizing the randomized image of the DP technique. To ensure privacy, the face database undergoes perturbation using DP techniques before releasing to any unauthorized access. The CNN model learns from these perturbed images, extracting features that are subsequently used by a predictor to classify the face. The CNN model learns from these images and then this trained CNN extracts features from an image that needs to be recognized. Ultimately, a predictor classifies this face. We evaluate three DP techniques namely Laplacian, Gaussian, and DP-blur using four predictors to evaluate the privacy-preserving capabilities of the proposed method. Each DP technique is evaluated by varying privacy parameters from 0.5 to 8 with an interval of 0.5. This research employs two datasets, namely LFW and IC. The DP blur with Logistic regression predictors provides the highest privacy, achieving excellent accuracy rates of 97% and 77% for these datasets. This outcome surpasses all baseline methods. The research offers an in-depth analysis of various DP techniques to construct a secure face recognition system. The method will aid in the automatic recognition of faces while ensuring privacy. Citation: Hossain MM, Rahman MM (2026) Enhancing face recognition privacy through the integration of differential privacy and convolutional neural network. PLoS One 21(8): e0353565. https://doi.org/10.1371/journal.pone.0353565 Editor:
Aug 18, 2026 · via journals.plos.org
THE clock was ticking. I’d zipped round the supermarket, self-scanning as I went, and I now had about 15 minutes to exit, pack the car and get to work. But here was a security guard telling me everything would need to be scanned again. After unpacking the first bag, he lifted out an empty crisp packet. “Did you eat these while you were going round?” he asked. No, I replied, I was not eating crisps while shopping, and I had not shoplifted a packet of Walker’s Baked. He rummaged in the bag for a few other pieces of forgotten litter – old shopping lists and receipts – and offered them to me. “There’s a bin over there.” I stared at him. “You can put those right back where you found them,” I said. READ MORE: We work with refugees in Glasgow. The BBC film on our city had these glaring flaws Grumpily, he complied. It then transpired that in the process of re-scanning my entire weekly shop, he had somehow accidentally deleted the whole lot from the till, and from my app. The clock kept ticking. As I scanned it all again myself, I asked: “So what was it I missed?” He looked blank. “What was missing, when you checked the first 10 items?” “Oh, nothing. Sometimes we just have to do a full re-scan regardless.” Perhaps it was a coincidence that I had recently written in these pages about supermarkets displaying discounts the night before they come into effect – a clear breach of advertising rules – apparently to avoid having to pay workers for a night shift. Because of course I was neither a known thief nor an anonymous customer. Through my use of the self-scan app and loyalty scheme, the supermarket knows more about my tastes and
Aug 18, 2026 · via thenational.scot
Figures Abstract Large domain-specific foundation models have been widely adopted for retinal image analysis, yet systematic evidence for their advantage over compact general-purpose architectures remains scarce. We benchmarked nine model configurations spanning 22.8M to 303M parameters (vision transformers, hierarchical Swin Transformers, ConvNeXt, and the domain-specific RETFound models) across four tasks: OCT 8-class disease classification, and three fundus photography tasks (DME severity, glaucoma detection, and DR severity grading). All models were evaluated under identical training conditions, with both pretrained (on natural-domain image datasets) and from-scratch initializations compared using Mann-Whitney U tests. Pretraining improved accuracy by 5.18–18.41 percentage points across all tasks (p < 0.05 throughout), with larger benefits for CFP modalities and harder tasks. Compact hierarchical models (27–29M parameters) matched or exceeded larger architectures on three of four tasks. For instance, the SwinV2-tiny architecture ranked first on OCT, DME, and GL classification. The domain-specific RETFound model (303M) achieved the highest accuracy only on the most challenging task (DR severity grading, where the most severe class is underrepresented at 8% of images), where it outperformed the best compact model by 1.54 percentage points. These results indicate that compact general-purpose models may be sufficient for most retinal classification benchmarks, and that domain-specific foundation models may add higher value mainly for severity grading tasks with skewed class distributions. Citation: Isztl D, Spitznagel T, Somfai GM, Santos R (2026) Compact vision models match domain-specific foundation models for several retinal imaging classification tasks: A systematic benchmark. PLoS One 21(8): e0356202. https://doi.org/10.1371/journal.pone.0356202 Editor: Jia-Lang Xu, National Taichung University of Science and Technology, TAIWAN Received: April 14, 2026; Accepted: July 29, 2026; Published: August 18, 2026 Copyright: © 2026 Isztl et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
Aug 18, 2026 · via journals.plos.org
Nashville Metro Council considers new rules for police drones NASHVILLE, Tenn. (WZTV) — Metro Council is considering new rules that could change how Nashville police use drones as first responders, including when those drones can be deployed and what technology they can use. The debate centers on a proposal originally filed by Councilmembers Sandra Sepulveda and Ginny Welsch, a substitute version of that proposal, and a separate amendment that would add special events to the situations covered by the emergency-use rules. At the center of the discussion is MNPD's Drone as First Responder, or DFR, program. What is a Drone as First Responder? MNPD began a limited DFR trial in May 2026. The department says the program uses small drones that can respond to police and fire calls and, in some cases, arrive before officers. The goal is to give responders an aerial view of what is happening so they can make safer and more informed decisions. The initial trial uses three drones launched from the roof of the Madison Precinct. MNPD said the drones could respond within a two-mile radius to emergency calls, active criminal investigations, missing-person calls and significant traffic crashes. Four FAA-certified officers operate the drones from the Community Safety Center at police headquarters. MNPD says the program is not intended to be a general surveillance or routine patrol system. The department says drones are dispatched to specific calls for service. The department has also pointed to early examples of the technology being used during active calls. In May, MNPD said a DFR drone located a domestic-violence suspect who had fled on foot. In July, the department said drone footage helped officers arrest two suspects in an active robbery and recover a boxcutter used in the crime. PAST COVERAGE | Metro review board raises questions about MNPD
Aug 18, 2026 · via fox17.com
Coles and Woolworths test facial recognition technology In short: Coles and Woolworths have tested facial recognition technology in a bid to combat retail crime. Neither of the supermarket giants have said if it would be rolled out in their Australian stores. It comes after Bunnings won a legal battle to monitor its customers with AI. Coles and Woolworths have conducted tests of facial recognition technology, but it is unclear if either supermarket will be implementing it in stores. It comes after the Australia Financial Review reported both Coles and Woolworths had trialled the technology as part of an ongoing effort to combat retail crime. The article said both supermarket giants had "conducted early testing" of the technology. When the ABC asked Coles about the potential of it being rolled out in stores, a spokesperson made a distinction between the use of the term "test" instead of "trial". "Coles has not done a trial using this technology," the spokesperson said. "A small, one-off, controlled proof-of-concept test of the technology was undertaken which did not use customer or team member information or data. "No decision has been made about the deployment of facial recognition technology." The spokesperson said Coles did not currently use facial recognition technology in stores. The ABC understands Woolworths tested the technology in its New Zealand office. A Woolworths spokesperson did not address the ABC's questions on how facial recognition technology was tested or if it would be used in Australia. "Keeping our team and customers safe is the most important thing we do and we've put significant investment towards this," the spokesperson said. "While our current safety initiatives are making a difference, we are still seeing a concerning amount of aggression and conflict incidents in our stores on a daily basis, including weapons being presented." Facial recognition technology
Aug 18, 2026 · via abc.net.au
Privacy advocates have long had reservations about biometric facial scanning, but some businesses still haven’t gotten the memo – with grocery chains now reneging on promises to avoid biometrics and a major EFTPOS supplier spruiking a terminal that lets you pay by scanning your face. Verifone, which has over 300,000 EFTPOS terminals in everyday use, this month introduced Australian customers to its Victa model, which embraces biometric scanning alongside normal tap and pay features. Customers enrol their biometrics once through merchants, digital wallets, banks, and other companies, with the technology creating a unique digital token that cannot be used elsewhere or reverse engineered to recreate the original face or handprint. By looking into a camera on the device, or scanning their palms to capture the unique pattern of veins in their hands, customers verify their identity against the token data, completing financial transactions or identifying themselves as a member of the store’s loyalty program. It’s part of a suite of products that let merchants sell with back-end integration to e-commerce platforms like Shopify, Bilt, Aevi, PayPal, and Stripe – and the ability to, as Verifone head of strategic partners Kristy Gregory put it, “pay with a smile.” “People already use biometrics to unlock phones, access apps, and confirm payments online,” she said. Verifone is “giving customers that same choice at the point of sale” with a tool that makes checkout “faster, easier and safer for consumers and retailers,” she added. A hard sell for privacy-focused consumers? Retailers may love the cachet of offering biometric capabilities for consumers, but those customers have consistently proven more wary of other technologies built around biometrics. Biometric systems “are becoming more effective as technology advances [but] they are not a foolproof method of authentication or identification” as spoofing, false acceptance, and other issues persist, the
Aug 18, 2026 · via ia.acs.org.au
Microsoft ends support for Internet Explorer on June 16, 2022. We recommend using one of the browsers listed below. Please contact your browser provider for download and installation instructions. August 18, 2026 NTT's paper was accepted at ICPR 2026, the International Conference on Challenges in the Fields of Pattern Recognition, Computer Vision and Machine Learning, to be held in Lyon, France from August 17, 2026 to 22nd. The adopted papers are as follows. Abbreviated names of the laboratories: HI: NTT Human Informatics Laboratories Shogo Sato (HI), Kazuhiko Murasaki (HI), Ryuichi Tanida (HI) We propose a training-free and low-cost rendering method for generating photo-realistic images from colored point clouds. Colored point clouds captured by LiDAR are sparse, so they are not suitable for producing high-quality images directly. In our method, we first upsample the point cloud and geometrically assign 3D Gaussian Splatting parameters to each point. This enables dense and natural image rendering. We also use pre-trained models to restore missing or blurry regions. In addition, multi-view refinement helps recover structures that are difficult to reconstruct from a single view while maintaining geometric consistency. Experiments show that our method achieves rendering quality comparable to conventional learning-based methods without requiring training data and with lower computational cost. Information is current as of the date of issue of the individual topics. Please be advised that information may be outdated after that point. WEB media that thinks about the future with NTT
Aug 18, 2026 · via group.ntt
Merlin Bird ID is an app likened to Shazam for birdsong, and it taps into the world's largest database of bird sightings, sound and photos to share a fun way to identify birds. With this free app from the Cornell Lab of Ornithology, users can ask simple questions, explore birds in their region, upload photos, and record singing birds to learn something about the natural world. "Birding" is no longer a pastime for retirees, since Gen Z is increasingly picking up birdwatching as a low-cost, low-pressure way to unplug and be present outdoors. On TikTok, #birdwatching, #birdtok and #birding content are only becoming more popular. After discovering the hobby through social media, this younger, unexpected group is finding themselves quickly drawn in to its mix of mindfulness, mild adventure and the dopamine hit of seeing or hearing something rare. Bird Identification Apps Merlin Bird ID Helps with Identifying Birds Seen and Heard Trend Themes - Audio-driven Nature Recognition — AI-powered sound matching turns casual outdoor moments into instant learning experiences, creating openings for platforms that identify biodiversity through ambient audio. - Gen Z Birding Culture — Social media is reshaping birdwatching into a youthful wellness hobby, revealing potential for community tools that blend nature discovery with digital sharing. - Mindful Micro-adventures — Low-cost outdoor activities are gaining appeal as accessible alternatives to screen-heavy leisure, supporting new services centered on calm exploration and local discovery. Industry Implications - Mobile Applications — Feature-rich identification apps can expand beyond utility into habit-forming discovery ecosystems that combine AI, education and user-generated data. - Outdoor Recreation — The rise of casual birding signals demand for approachable gear, guided experiences and beginner-friendly formats that make nature participation less intimidating. - Education Technology — Interactive species recognition creates fresh possibilities for informal science learning, where real-world observation
Aug 18, 2026 · via trendhunter.com
Bastrop’s Flock camera policy could soon include additional safeguards and a shorter data retention period. The overview During an Aug. 11 meeting, Bastrop City Council directed staff to return with an updated Flock policy, including additional safeguards. City Manager Sylvia Carrillo-Trevino said it would add “checks and balances,” comparing the goal to ensuring “the cashier isn’t also the one taking the money to the bank.” On Aug. 13, Flock announced it cut the default data retention period from 30 days to seven. Community Impact reached out to city officials to learn if the new recommendation would be part of the changes. Bastrop Police Chief Vicky Steffanic said her department follows Flock's default data retention period, confirming Bastrop's retention period will also be recommended to change from 30 days to seven days. What else? Although officials would not provide details about what specific policies are under review, Steffanic said the BPD's rules are "consistent with applicable best practices and comply with requirements established by the state." "Any potential changes to the department’s current policy are presently under review," Steffanic told Community Impact. "At this time, no specific changes have been approved or implemented." What we know According to the city's current policy, Flock can only be used for: - Criminal cases: Searches must be tied to a criminal investigation - No facial recognition: Cameras only capture license plate information - Enforcement limits: Not used for citations or minor offenses Looking ahead The policy is expected to return to Council on Aug. 25. Before you go BPD is not the only local law enforcement agency using camera-based technology. As previously reported by Community Impact, Bastrop County Commissioners Court approved on March 24 a one-year, $17,100 Clearview AI licensing agreement for facial-recognition software that officials said can help identify people involved in cases
Aug 18, 2026 · via communityimpact.com
Do these creepy patent drawings reveal what’s next for Meta’s smart glasses? “Pervert glasses” that remember faces. Cute. - A new Meta patent shows smart glasses using facial recognition to scan a dinner party and pick out who's worth filming. - The AI reads expressions and actions, then auto-creates personalized highlight reels and searchable memories of people met. - It's just a patent, not a confirmed feature – but the illustrations are likely to unnerve privacy advocates. - Meta is already facing backlash over the glasses: facial-recognition tool NameTag was scrapped in June, and courts in UK and New York have banned the specs. Key Takeaways by nexos.ai, reviewed by Cybernews staff. Eerie drawings in a newly published Meta patent application show smart glasses scanning guests at a dinner party, recognizing their faces – and deciding who is interesting enough to film. The application, filed by Meta Platforms Technologies – the maker of Meta's Ray-Ban smart glasses and VR hardware – describes an AI camera system that identifies people via facial recognition, interprets their actions, and turns what it sees into personalized media and searchable memories. The latest application was filed on February 4 2026 and published on August 13. It is a continuation of earlier filings, meaning some of the underlying technology has been in Meta’s patent pipeline for years. And the patent’s illustrations show just how invasive technology could become if applied to Meta’s glasses business, which, to date, has sold around 7 million pairs. Figure 5A depicts someone wearing AR glasses at a dinner party. The system analyzes the people in the room, uses facial recognition to identify one guest as the wearer’s wife and selects her as a “point of interest.” Continuing the fun, Figure 5B shows the camera automatically zooming towards the wife, centering her
Aug 17, 2026 · via cybernews.com
Woolworths has been running a trial of facial recognition technology at its New Zealand office, as the supermarket giant explores using it in its Australian stores. A spokesperson for Woolworths told 1News the technology had been tested at its support office in Auckland to "further understand the use of this technology to improve safety". “While our current safety initiatives are making a difference, we are still seeing a concerning number of incidents of aggression and conflict in our stores on a daily basis, including weapons being presented." They said that between 2019 and 2025, acts of violence and aggression had increased by 238%. "We have also seen a shift from opportunistic shoplifting to more brazen confrontations often involving weapons, threats to kill, and physical violence." They said the corporation was "still at an early stage" and could not comment further. The test comes after a February ruling by Australia's Privacy Commissioner that gave hardware giant Bunnings the green light to use facial recognition, following a previous ruling that found it had breached privacy laws. Facial recognition technology is already being used in New Zealand. Bunnings has rolled it out across its network, while Foodstuffs, which operates New World, Pak'n'Save, and Four Square, has also implemented it at some locations. Briscoes Group, which is behind Briscoes and Rebel Sport, has been running a year-long trial of the technology at its stores. Before using facial recognition technology, the New Zealand Privacy Commissioner said organisations must justify its necessity, ensure the problem is serious, and check whether less intrusive alternatives would work. SHARE ME
Aug 17, 2026 · via 1news.co.nz
Abstract Artificial intelligence for medical imaging is required to be accurate and interpretable to clinicians. However, current multimodal biomedical foundation models often prioritize performance over explainability. Here we present ConceptCLIP, an explainable biomedical foundation model that achieves state-of-the-art diagnostic accuracy while delivering human-interpretable explanations across diverse imaging modalities. We curate MedConcept-23M, a large-scale dataset comprising 23 million biomedical image–text–concept triplets. Leveraging this dataset, we pretrain ConceptCLIP via joint image–text and region–concept alignment for precise and interpretable medical image analysis. Across a large-scale benchmark covering 78 datasets in 10 imaging modalities, ConceptCLIP demonstrates superior diagnostic performance while providing human-understandable explanations. In a clinician user study spanning three modalities, the concept-based explanations provided by ConceptCLIP help clinicians verify model predictions and identify potential errors. As an explainable biomedical foundation model, ConceptCLIP represents a critical milestone towards the widespread clinical adoption of AI, thereby advancing trustworthy AI in medicine. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Subscribe to this journal Receive 12 digital issues and online access to articles $119.00 per year only $9.92 per issue Buy this article - Purchase on SpringerLink - Instant access to the full article PDF. USD 39.95 Prices may be subject to local taxes which are calculated during checkout Data availability This study incorporates a total of 79 datasets. Among these, the proposed MedConcept-23M dataset is used for training the ConceptCLIP model. The image part of the pretraining dataset, MedConcept-23M, is open-sourced and can be obtained directly from the publicly available PMC Open Access Subset (PMC-OA). The captions and concepts are available at https://huggingface.co/datasets/JerrryNie/MedConcept-23M. To enable reconstruction of the full dataset, we provide a dataset reconstruction script as part of
Aug 17, 2026 · via nature.com
Supermarket duopoly tests facial recognition
Coles and Woolworths have conducted tests of facial recognition technology that they could use in their Australian supermarkets to combat crime, although it is not clear whether they will implement it fully.
Dr Jason Pallant, a marketing expert at RMIT University, said the trials posed a “security versus privacy dilemma” (The Guardian).
Tom Sulston, the head of policy at Digital Rights Watch, flagged that facial recognition was “wildly inaccurate”, and also raised concerns that Coles and Woolworths wouldn’t be able to control the way their biometric data was used (The Guardian).
Both Coles and Woolworths say they have not decided whether to deploy the technology after the trials. “Keeping our team and customers safe is the most important thing we do, and we’ve put significant investment towards this,” a Woolworths spokesman said (AFR).
The testing revelations follow hardware chain Bunnings’ legal battle win earlier this year that allowed it to monitor its customers with artificial intelligence (ABC).
Aug 17, 2026 · via thesaturdaypaper.com.au
“The Federal Circuit concluded the reference ‘logically would have commended itself to an inventor’s attention in considering his problems.’” The U.S. Court of Appeals for the Federal Circuit (CAFC) issued a precedential decision on Friday, August 14, in The Nielsen Company (US), LLC v. TVision Insights, Inc., affirming a Patent Trial and Appeal Board (PTAB) final written decision that invalidated challenged claims of a Nielsen audience measurement patent as obvious. The court rejected arguments that the Board improperly relied on a scientific publication as analogous prior art and that the publication failed to disclose the claimed resolution reducing and facial recognition steps. TVision Insights, Inc. filed a petition for inter partes review (IPR) of U.S. Patent No. 11,470,243, owned by The Nielsen Company (US), LLC, titled “Methods and Apparatus to Capture Images.” The patent relates to systems for measuring and identifying the audience of a media presentation device such as a television. The specification describes a camera-based system that uses a “people counter” to detect audience members based on features such as heads and faces in low-resolution images. A “person identifier” then compares the detected faces against stored facial signatures using higher-resolution images. TVision’s petition challenged 14 claims, but Nielsen disclaimed the 3 independent claims at issue in its preliminary response, and the Board instituted review of 11 dependent claims, with claims 4 through 6 becoming the focus of the appeal. Claim 4 recites processor circuitry that reduces the resolution of a first image to obtain a reduced resolution image and determines head orientation based on that image. Claims 5 and 6 add a two-step process that generates a facial signature from a separate image corresponding to the head location identified in the reduced resolution image, then compares that signature against a database of stored signatures. The Board considered two
Aug 17, 2026 · via ipwatchdog.com
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Aug 17, 2026 · via cureus.com