China’s draft rules on AI ‘virtual humans’ target biometric deepfakes China has issued a new draft regulation on “digital virtual humans,” or AI chatbots, introducing clear labeling requirements and mandating explicit consent for using a person’s likeness, voice, or other personal data to create a virtual representation. The regulation would also ban the use of digital humans to “evade facial recognition, voice recognition, or other identity authentication mechanisms.” The Cyberspace Administration of China (CAC) published the draft rules, titled Measures for the Management of Digital Virtual Human Information Services, last Friday. Public consultations will run until May 6th. Digital virtual humans are defined as virtual figures that exist in nonphysical environments and simulate human appearance and behavior using technologies such as computer graphics, digital image processing, and artificial intelligence. In other words, personas used by chatbots based on LLMs like ChatGPT and Grok, and the myriad applications based on them. The clauses on consent for use of likeness and banning bypass attacks against biometric authentication systems clearly targets the spread of deepfakes. The rulebook introduces special protections for minors, prohibiting the offering of virtual intimate relationships to children under 18, including simulated family members or romantic partners, as well as any services that may trigger excessive spending, promote harmful conduct, or compromise their physical or mental well-being. The draft also introduces measures to prevent the spread of rumors, insults and defamation through digital humans. Organizations and individuals should resist the creation or distribution of content containing sexual innuendo, cruelty, horror, or discriminatory material, according to the draft (translation). The regulation is part of China’s efforts to protect personal data and rein in AI technologies. The draft law builds on CAC’s 2025 Measures for Labeling of AI-Generated Synthetic Content, which require visible and technical labels for AI-generated text, images, audio and
Apr 8, 2026 · via biometricupdate.com
Sponsor Content Created With Dell Technologies Top business tips for the Dell Pro 5 and Dell Pro 7 The Dell Pro 5 and Dell Pro 7 unlock a slew of benefits for businesses So, you’ve picked the Dell Pro 5 and Dell Pro 7 for your workforce. These devices are the latest and greatest in the Dell Pro lineup, providing all the power needed for today’s business software as well as sleek, professional designs that suit any table – be it boardroom or train. For all these reasons and more, leaders who land on the Dell Pro 5 or the Dell Pro 7 for their workforce device upgrade can rest easy knowing they’ve chosen some of the best business devices on the market. To really get the most out of the investment, though, it’s worth knowing the top business tips for the Dell Pro 5 and Dell Pro 7. TL;DR: - One of the primary benefits of upgrading to the Dell Pro 5 or Dell Pro 7 is to make the most of Microsoft Copilot on Windows 11, as well as other AI apps and features that require an NPU to work properly. - Wherever you're headed, be it the office commute or a trans-oceanic flight, the Dell Pro 5 and Dell Pro 7 can meet your needs and provide the battery needed to make the journey with you. - Dell Pro laptops are equipped with top of the line displays, sophisticated cameras, and clear microphones, to remove friction between a user and all the people with whom they interact. Make the most of AI apps Both the Dell Pro 5 and Dell Pro 7 laptops provide ample opportunity for staff to leverage AI applications and features, including those that come as a part of Windows 11. This is because
Apr 8, 2026 · via itpro.com
Man sues City of Reno over use of facial recognition
RENO, Nev. (KOLO) - A man claiming to have been wrongfully arrested at the Peppermill is now suing the City of Reno.
According to court documents, back in 2023, Jason Killinger was at the Peppermill when facial recognition software identified him as a man who was earlier barred from the property.
Killinger was arrested and taken to the Washoe County Detention Facility for fingerprint testing to confirm his identity. Killinger was determined to not be the man in question and he was released.
In 2025, he sued the arresting officer, alleging fabrication of evidence and excessive force. The court denied the claim of wrongful arrest.
In a new filing, a district court has granted his request to add the City of Reno as a new defendant in the case, as well as a new municipal liability claim against the city.
Copyright 2026 KOLO. All rights reserved.
Apr 8, 2026 · via kolotv.com
Startup launches deepfake detection capable of tracing images to specific tools Canada-based content analysis provider Winston AI has launched a forensic image detector that the company says can trace deepfakes back to their source. The new tool can pinpoint which parts of an image were manipulated, according to Winston AI, as it can determine how they were altered, and which AI model or editing tool produced the changes. “Until now, detection tools told you whether to trust an image,” says John Renaud, CEO of Winston AI. “Ours tells you exactly where not to trust it, and which tool put it there. That’s the difference between a smoke alarm and a fire investigator.” More than 10 million people use the AI content-detection platform, which Winston AI designed for high stakes environments such as journalism and fact checking, legal evidence review, academic integrity checks and content moderation teams. In principle, it could also have value for fraud prevention teams handling images submitted for KYC checks that they suspect may be biometric deepfakes. Instead of offering a binary “real‑or‑AI” verdict, the system analyzes images using six independent forensic techniques. These map pixel‑level anomalies such as broken camera‑sensor fingerprints, inconsistent compression, unnatural edges and noise patterns. When combined with metadata and C2PA provenance signals, Winston AI’s tool is, when possible, capable of attributing an image to a specific generative model or editing software. A multimodal reasoning model compiles the findings into a structured report that includes an authenticity verdict and confidence score. The software produces a written summary along with region‑by‑region manipulation breakdowns and tool attribution where possible. The forensic image detector is available now on the company’s website in both a lightweight screening mode and a full advanced forensic mode. Deepfake detection is an emerging area. Biometric Update and Goode Intelligence have a
Apr 8, 2026 · via biometricupdate.com
Introduction Facial Recognition Statistics: Facial recognition technology is becoming a part of our daily lives. It helps identify people by studying their faces. This system makes security faster, smartphones smarter, and online services more personalized. From unlocking devices for use in airports to its growing role, it’s a fast-changing area. However, this technology also brings concerns. There are questions about privacy, safety, and possible mistakes. It is important to understand how it works, along with its benefits and risks, as it becomes more common in everyday life. Editor’s Choice - In 2026, the total market size is projected to be about USD 9 billion. - The software segment is projected to hold a 53.9% share by the end of 2026. - In terms of technology, 2D facial recognition is projected to lead, accounting for 41.7%. - By application, security and surveillance will dominate, accounting for 39.4% in 2026. - North America is expected to remain the largest market, holding 43.1% share. - Ayonix Corporation leads the market with a 15% share, followed by IBM Corporation at 11% and Aware, Inc. at 10%. - About 68% of users apply facial recognition to unlock their phones, laptops, or personal computers. - In 2026, almost 55% of Americans are most comfortable with the use of FRT in airports for safety purposes. - The acceptance of FRT is highest for passport control at 81%, followed by building access at 72%. - FRT is widely accepted for security purposes, with 81% approval for passport control and 72% for building access, while 55% of people support its use in police surveillance. - About 60% of adults are somewhat aware that employers use facial recognition technology. - Adoption is higher among younger users, with 12% of users aged 18-34 using it in shared spaces versus 1% of
Apr 8, 2026 · via bayelsawatch.com
Abstract In-sensor neuromorphic vision platforms with near-infrared (NIR) sensitivity are essential for intelligent imaging in low-light and multispectral environments. Here, a retinocortical dual-mode platform based on evolved-synaptic transistor (Evo-SynT) devices using upconversion nanoparticles (UCNP) and their integration into evolved-retina optical synapse (EROS) arrays is introduced. Evo-SynT devices exhibit key synaptic features, including paired-pulse facilitation indices exceeding 183.93% and 136.36% at a 0.5 s interval under 808 nm and 940 nm illumination, respectively, and analog weight modulation across 512 conductance states. A 12×12 EROS array enables dual-mode operation: retinal-like in-sensor preprocessing and cortical-like in-memory classification. The EROS array improves pedestrian detection accuracy under low-light conditions from 0.7806 to 0.8481 (808 nm) and 0.9071 (940 nm), and achieves classification accuracies of 77.19% and 79.40%, respectively. These results highlight the EROS platform as a scalable solution for integrated NIR-sensitive neuromorphic vision systems. Data availability The data supporting the findings of this study are available within the paper and its Supplementary Information files. The source data underlying the graphs and plots presented in the figures are provided with this paper. Additional data related to this study are available from the corresponding authors upon request. Requests for data will typically be responded to within two weeks, and the data will remain available for at least three years following publication. Source data are provided in this paper. Code availability All custom codes used for data processing, analysis, and simulation in this study are provided with this paper as Source Code files. References Huang, P.-Y. et al. Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction. Nat. Commun. 14, 6736 (2023). Zhou, G. et al. Full hardware implementation of neuromorphic visual system based on multimodal optoelectronic resistive memory arrays for versatile image processing. Nat. Commun. 14, 8489 (2023). Huang, H. et al. In-sensor
Apr 8, 2026 · via nature.com
What began as low-budget, authentic programming evolved into a cable TV industry capable of producing prestige content that redefined media and entertainment. Are today’s creators traversing the same trajectory? The parallels are striking, but so are the differences, and those differences present both potential limitations and inherent advantages as the creator economy continues to evolve and grow. Cable TV’s Evolution: From Raw Authenticity to Prestige Storytelling in Three Phases From the 1990s into the 2020s, the cable TV industry* delivered ever-increasing levels of fidelity in content and achieved greater and greater heights, cementing itself as a backbone of modern media. This evolution unfolded across three distinct phases, each representing a leap in storytelling ambition and production value. With each phase, cable’s audience followed and the industry thrived. Phase 1 - Unscripted Reality: First-Person Storytelling + Low-to-Mid Fidelity - Cable first captured audiences through reality content built on first-person, unscripted authenticity. In first-person storytelling, stories unfold through an individual’s direct perspective and lived experience. The audience participates from within rather than observing from the outside. This immediacy is the core of the parasocial bond that makes reality content so compelling. In the 1990s, cable pioneered this format with shows such as MTV’s The Real World (1992 - 2017) and Road Rules (1995 - 2007), which later extended into Laguna Beach (2004 - 2006), Deadliest Catch (2005 - present), The Real Housewives (2006 - present), Keeping Up With The Kardashians (2007 - 2021) and many others, giving viewers unfiltered access to “real people” in niche communities. This Phase 1 content is cost-effective to produce and sustains engagement across long seasons and/or reruns, building deeply engaged fan bases. Phase 2 - Scripted Animation: Third-Person Storytelling + Low-to-Mid Fidelity/Budget - Soon after reality content, low-to-mid-budget animation found a home on cable. Cable’s Phase 2
Apr 8, 2026 · via lexology.com
Abstract DICOM image pseudonymization is an effective measure to protect patient privacy and ensure compliance with the GDPR. However, no standardized methods guarantee the irreversible anonymization of DICOM images or provide evidence on the robustness of these procedures. Organizations such as NEMA propose pseudonymization profiles for DICOM metadata, but the risk to data protection is assumed by the entity responsible for pseudonymization, as the potential privacy risks associated with their use cannot be accurately assessed. In the Re-identification Challenge, the selected 68 participants were tasked with re-identifying 38 pseudonymized DICOM studies from multiple European acquisition sites, modalities and anatomical regions. The data were pseudonymized using the pseudonymization profiles developed in ChAImeleon1 and ProCancer-I2 European AI4HI projects. No participants were able to trace back the identity of the patients, demonstrating the effectiveness of these pseudonymization profiles. Despite minor vulnerabilities identified in areas such as free-text metadata, 3D reconstructions, and usability limitations, no successful re-identification occurred—even with monetary rewards offered to participants. Similar content being viewed by others Data availability The dataset used in this study is publicly available in Zenodo with https://doi.org/10.5281/zenodo.170346748. Code availability Several software tools were used during the Re-identification Challenge. The dataset8 was pseudonymized using the CTP app (version released on 2023-11-04) with project-specific configurations. The CTP app is available in https://github.com/johnperry/CTP/raw/master/products/CTP-installer.jar and its documentation in https://mircwiki.rsna.org/index.php?title=MIRC_CTP. Moreover, the software used to apply de-facing in the dataset8 is available in https://www.nitrc.org/projects/mri_reface. References Bonmatí, L. M. et al. CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools. Front. Oncol. 12, 742701. https://doi.org/10.3389/fonc.2022.742701 (2022). ProCancer-I Project. An AI Platform integrating imaging data and health records for precision medicine in cancer management. https://www.procancer-i.eu/ (2025). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the
Apr 8, 2026 · via nature.com
Abstract To achieve object detection in UAV vision, an object detector is crucial, but haze seriously affects detector performance by physically suppressing high-frequency information, which makes it difficult to detect tiny objects. Traditional “dehazing-then-detection” paradigms are restricted to inconsistencies in tasks and restoration effects. The article provides Frequency-Domain Modulation Network (FDMNet), which is an aerial non-explicit-restoration haze-resistant object detector. Following a physical prior, FDMNet constructs an estimate-compensate architecture. A Frequency Domain Modulation (FDM) module is one that expressly estimates the loss of spectral information, and a dynamic LMF-Kernel adaptively restores the loss of mid- and high-frequency discriminative information. To be effective, we present a physical-semantic consistency loss strategy, with frequency-domain consistency loss guaranteeing physical accuracy and prompt distillation loss guaranteeing semantic consistency. We do not have enough datasets, and, therefore, we build Hazy-DOTA, Hazy-DroneVehicle, and a real-life UAV test set. Through extensive experimentation, FDMNet achieved a 7.9% improvement in mAP scores on the HazyDet dataset compared to baseline models, alongside respective gains of 9.9% and 11.5% on the Hazy-DOTA and Hazy-DroneVehicle datasets. Furthermore, it attained state-of-the-art performance relative to several advanced algorithms, balancing both accuracy and robustness. Data availability https://www.kaggle.com/datasets/xiaoxiongzhou/hazy-datasetsThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Wang, H. Y. et al. Cross-Modal Oriented Object Detection of UAV Aerial Images Based on Image Feature. IEEE Trans. Geosci. Remote Sens. 62, 1–21 (2024). Xie, X. X. et al. Fewer is more: efficient object detection in large aerial images. Sci. China-Information Sci. 67 (1), 112106 (2024). Hou, T. et al. MFEL-YOLO for small object detection in UAV aerial images. Expert Syst. Appl. 291, 128459 (2025). Tan, Z. W., Jiang, Z. G., Guo, C. & Zhang, H. P. WSODet: A Weakly Supervised Oriented Detector for Aerial Object Detection. IEEE Trans. Geosci. Remote Sens.
Apr 8, 2026 · via nature.com
Tech Trends: New Tools for Venue Management, Facial Authentication, Ticketing and More TSNN takes a deep dive into the newest tech solutions for events of all types, plus the latest must-know industry news. April 8, 2026 Event Technology We're Excited About This Month To give every attendee a personalized, AI-powered event guide Event experience platform Bizzabo has introduced BizzyAI, an attendee copilot designed to deliver real-time, personalized guidance throughout the event experience. Built into the Bizzabo mobile app, Bizzy answers questions, recommends sessions and connections, and helps attendees navigate agendas and venues based on live event data—reducing the need for support staff while ensuring consistent, up-to-date information. “Attendees are more selective about where they spend their time. When they commit, they expect relevance, personalization, and clear outcomes,” said Alon Alroy, co-founder and CMO of Bizzabo. “Bizzy helps meet those expectations by delivering timely, personalized guidance throughout the event experience.” To visualize and plan events in real venues before arriving on site Event production company Freeman has launched Blue Echo, an AI-powered 3D visualization platform that turns convention centers into photorealistic, fully navigable digital environments for event planning. By creating accurate, immersive models of venues, the tool allows organizers to test layouts, map attendee journeys, and evaluate sponsorship placements months in advance—helping teams reduce planning time, avoid on-site surprises, and make more informed design and budget decisions. “Innovation is our instinct,” said Janet Dell, CEO of The Freeman Company. “At TFC, we don’t wait for the industry to change; we build what changes it. Freeman Blue Echo reflects our commitment to intelligent innovation: emerging technology with real, practical value for our clients and our teams.” Photo Courtesy of Freeman To manage venue operations and trade shows, all in one place Venue management platform Thynk and exhibition management platform ShowCycle have partnered
Apr 8, 2026 · via tsnn.com
Fargo mayoral candidate Josh Boschee addresses billion-dollar debt, facial recognition controversy FARGO, N.D. (Valley News Live) - North Dakota State Senator Josh Boschee sat down with Valley News Live to discuss his campaign for Fargo’s first full-time mayor position, addressing the city’s billion-dollar debt, a facial recognition case and a proposed flavored nicotine ban which were among numerous topics discussed. Boschee said he views the city’s debt similarly to a mortgage. According to Boschee, about $550 million relates to infrastructure including water, roads and wastewater as the city grows. Another $200 million involves the wastewater treatment plant, and close to $200 million relates to water intake processes and clean water. “Certainly a billion dollars is a large number. I’m used to working with a $20 billion budget out in Bismarck,” Boschee said. Boschee said the city should apologize for its role in the Angela Lipps case. Lipps, a Tennessee grandmother, spent months behind bars after Fargo Police used facial recognition technology that wrongly identified her in a bank fraud case. Charges were dismissed, and the city has not apologized. “Well I think first and foremost better communication again from the city or law enforcement up front would have helped alleviate a lot of concerns the public had,” Boschee said. “Should Fargo apologize? I think Fargo should apologize for the role that we had.” Boschee said he was disappointed the City Commission tabled discussion on a proposed flavored nicotine ban until after the June election. He said the commission is setting itself up to be a lame duck commission. “They still have two months worth of work, three months actually until the new commission takes place,” Boschee said. Boschee said he wants to visit with all stakeholders before any proposal moves forward, including public health advocates, young people and store owners.
Apr 8, 2026 · via valleynewslive.com
Google vs. Ring vs. Arlo: We put 6 security cameras to the test to find the most accurate AI There's a clear winner Here at Tom’s Guide our expert editors are committed to bringing you the best news, reviews and guides to help you stay informed and ahead of the curve! You are now subscribed Your newsletter sign-up was successful Want to add more newsletters? Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Many of the best home security cameras on the market today call themselves "smart," but there's a massive difference between a camera that fires off alerts every time a tree branch moves and one that can actually tell you what's happening at your home. Cameras these days use AI to better analyze motion and classify what they're seeing or hearing, and many of them are leaning into generative AI for things like summaries and descriptions, so you can better wade through the hours of footage they record. Of course, AI has become a bit of a buzzword, so I wanted to compare several cameras to see if they actually delivered on the promise of using AI to improve home security. To do so, I tested cameras from six major smart home companies — Google Nest, Arlo, Wyze, Ring, Blink, and Eufy — to see how they use AI, and if it’s worth the extra expense. Article continues belowThe contenders We deliberately picked models from each brand that carry the company's most capable AI feature set. In other words, while we didn't necessarily use the most expensive model that each manufacturer has to offer, we specifically made sure that it had the same AI features. To be sure, many companies' AI features work off-camera, so the particular type
Apr 8, 2026 · via tomsguide.com
Wide-area search 2.0: Strong increase in police facial recognition AI upgrade and mobile apps are causing BKA facial image query numbers to rise sharply. Critics warn of digital stigmatization of entire groups. Digital surveillance in public spaces is reaching a new dimension. Figures from the Federal Ministry of the Interior show a significant increase in the use of the police facial recognition system (GES). Last year, German authorities used the system, which is part of the Federal Criminal Police Office (BKA), much more frequently for identifying people than before. With a total of around 343,856 searches in 2025, the frequency more than doubled compared to the previous year. According to a response from Interior State Secretary Christoph de Vries (CDU) to a request from Bundestag member Lea Reisner (Die Linke), the criminal police offices of the federal and state governments stand out: in 2024, they still generated around 121,000 queries. But recently, the figure shot up to over 313,500 searches in 2025. The Federal Police also intensified its use, accessing the central photo database about 30,000 times – an increase of around 50 percent. Established in 2008, the system officially serves as an assistive tool to clarify the identity of suspects or victims. The procedure is based on comparing image material from surveillance cameras or mobile phones with the Inpol file. This currently contains 7.6 million photographs of approximately 5.4 million people. The software encodes anatomical features of a face into a mathematical template and compares it with the database in a fraction of a second. The result is a list of candidates sorted by probability. Results must subsequently be manually verified by photo experts. AI use and mobile investigation via app The technical modernization is the driving force. Since September 2024, the BKA has been using a system based
Apr 7, 2026 · via heise.de
Live facial recognition cameras will target knife crime hotspots under new plans to slash rates by a third - Get your news delivered straight to you - sign up to the Morning Mail newsletter for FREE to be first with the day's biggest stories Live facial recognition cameras are to be introduced across the UK in knife crime hotspots under new plans to slash offences by a third. New national mapping technology is being shared with police which is capable of identifying the worst knife crime hotspots down to 100 square metres, even identifying the specific times it is most likely to occur. Forces will be able to switch on cameras to catch out offenders on specific streets associated with knife crime. Under a plan to slash rates by a third in two years, police will also be able to use visible police patrols, CCTV cameras and knife detection arches in an unprecedented crackdown. On Tuesday, ministers announced a £26million Knife Crime Concentrations Fund will be allocated to the 27 police forces in England and Wales that deal with 90 per cent of knife crime. The move comes after live facial recognition camera trials have shown impressive results, with police in the first UK town to get a static camera catching criminals every 34 minutes, spotting suspects on the run for 20 years in some cases. In October, Scotland Yard installed fixed cameras on lamp posts at the entrance and exit to Croydon town centre during a trial which resulted in over 100 arrests for offences including possession of knives, strangulation and sexual assault. The cameras work by taking digital images of passing pedestrians, feeding them into a computer using biometric software to measure facial features. Live facial recognition cameras are to be introduced across the UK in knife crime
Apr 7, 2026 · via dailymail.co.uk
License plate readers have become a familiar part of everyday physical security and access control. What started as a specialized law-enforcement tool is now used on toll roads, in parking garages, at gated entrances, and throughout city infrastructure to quickly identify vehicles at scale. As LPR technology shows up in more places, people are asking tougher questions about how accurate it is, who’s watching over it, and what it means for privacy. This article explains how these systems work, where they are commonly used, what data they collect, and why they are still important in ongoing legal and ethical discussions. Key Takeaways - License plate readers (LPRs) are fast cameras that take pictures of license plates, record the time, and note the GPS location of the reader, creating a timestamped location record of the vehicle - Law enforcement uses LPRs to find stolen cars, locate people with outstanding warrants, and help with criminal investigations. Commercial operators use them for toll collection, parking management, and controlling access to areas. - Collecting a lot of license plate data raises important privacy and civil rights concerns, especially when this data is kept for a long time or shared beyond where it was collected. - LPR systems collect data on billions of vehicles, documenting the movements of individuals who are not connected to any criminal activity. This increases concerns about the surveillance capabilities these systems can provide. - The actual accuracy of LPR systems is often lower than what vendors claim. Their performance can vary greatly depending on environmental factors and conditions. What Is a License Plate Reader (LPR/LPR/ANPR)? A license plate reader is a surveillance technology designed to automatically capture and interpret vehicle registration plates from images or video footage. These systems go by several names: LPR (License Plate Reader), LPR (Automated License
Apr 7, 2026 · via omnilert.com
OCR Studio KYC onboarding tool for APAC recognizes diverse character sets Identity verification provider OCR Studio, which specializes in advanced optical character recognition, is unveiling an AI system for Know Your Customer (KYC) and client onboarding designed for the APAC region. A release from the firm says its APAC-Focused AI System, showcasing this week at GITEX AI Asia in Singapore, addresses the complex challenge of recognizing languages that can involve thousands of character classes, cursive writing, and unusual letter connections. The on-device tool “addresses these scripts’ features and reliably recognizes ID cards, passports, driving licenses, and other identity documents issued across the region.” Its scope covers identity documents in the region’s most widely used logographic, alphabetic, abugida and syllabary writing systems and languages, including Chinese, Japanese, Korean, Thai and Urdu. By keeping the KYC process on device, with no biometric data sent to clouds or external servers, the product helps companies comply with stringent data protection rules in certain APAC nations, such as Singapore’s Personal Data Protection Act (PDPA), China’s Personal Information Protection Law (PIPL) and Indonesia’s Law No. 27 on Personal Data Protection (PDP Law). The announcement follows the launch of OCR’s specialized anti-fraud toolset for advanced on-device document forensics, which includes three layers. The first considers data printing techniques and font controls, format and validity checks, and includes an image tampering detection module that identifies deepfakes, synthetic media and morphed IDs. The second enables document integrity checks and forgery detection, identifying inconsistencies across data fields. And the third uses selfie-to-ID biometric face matching to check whether the legitimate document holder is genuinely present. On April 23, OCR Studios will host a webinar focused on navigating compliance in the EU regulatory landscape. The eIDAS 2.0 regulation underpins the EU’s digital identity infrastructure and ecosystem. The webinar, “eIDAS 2.0 and
Apr 7, 2026 · via biometricupdate.com
The Ouroboros of Faces - Dates2025 - Ongoing - Author - Locations Berlin, Helsinki, Hong Kong - Shortlisted The advent of synthetic face data marks the latest phase of facial recognition. First, humans taught machines how to see faces. Now, machines are trained to recognize faces made by other machines —the logic forms a self-devouring snake, an ouroboros. Synthetic face data are deepfakes or digitally rendered 3D faces generated solely as training material for facial recognition algorithms. Technologists have proposed them as a solution to the insatiable data demands of large-scale AI models, claiming the added benefit of circumventing issues of privacy and consent. These statistical artefacts of facial recognition are fed back into the models themselves. The advent of synthetic face data marks the latest phase of facial recognition, where the logic of statistical inference is stretched to its breaking point. First, humans taught machines how to see faces. Then, networks learned to generate digital faces modeled on human ones. Now, machines are trained to recognize faces made by other machines—a self-devouring snake, an ouroboros. In the near future, our faces may be judged by algorithms that have never “seen” a real one. Through the machinic eye, a facial recognition algorithm looks back at us. They claim the power to predict sexuality and political ideology from facial landmarks. Like a magic mirror, it was believed to have the sacred power of statistical prophecy. Sacred powers are rarely questioned. When facial recognition fails, the error is attributed to flawed algorithms or noisy training data, but rarely the underlying logic of physiognomy itself: the assumption that a person can be known, measured, and judged by appearance. This project expands on my ongoing project (Inter)Faces of Predictions, which offers a critical reading of facial recognition alongside the forgotten pseudo-science of physiognomy and
Apr 7, 2026 · via phmuseum.com
Abstract Clouds significantly affects the power output of solar energy systems, and it also decrease the life of modules in photovoltaic system and receivers in the concentrating solar power system, resulting in costs of operation and maintenance. In the present study, the MRR-YOLO model was proposed, which was based on deep learning and instance segmentation technique. The MSDA, the RCS-OSA, and the RFAConv modules were used, and their functions to the cloud segmentation were investigated. Results found that the MSDA module helped maintain the model’s lightweight, the RFAConv module had a better feature extraction of the clouds. The instance segmentation method was better than semantic segmentation in clouds detection, especially for clouds of varying shapes. The PB, the RB, and the mAP50B of the MRR-YOLO model were 79.2%, 66%, and 74.7%, respectively. For the segmentation task, the PM, the RM, and the mAP50M were 79.3%, 64.8%, and 73%, respectively. The MRR-YOLO model was validated by the SWIMSEG, the CCSN, the all-sky datasets, and the real cloud images in Zhengzhou city, it had a better detection performance and applicability than other models. A heatmap comparison was also conducted, showing that the model accurately detected all features of the clouds. Similar content being viewed by others Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Abdalla, S. A mathematical model for economic and prognostic studies of solar photovoltaic power: Application to China, the EU, the USA, Japan and India compared to worldwide production. Renew. Energy Focus. 50, 100607 (2024). Borodiņecs, A., Lebedeva, K. & Odineca, T. Evaluation of household electricity consumption in multi-apartment buildings for optimization of rooftop PV systems. Energy Build., 114971. (2024). Rakhmatov, A. et al. Advancements in renewable energy sources (solar and geothermal): A brief review[C]//E3S Web of
Apr 7, 2026 · via nature.com
Fujisoftis developing an AI-enhanced physical security system built on the AMD Embedded+ platform that integrates FPGA adaptability with x86 processing performance into a unified architecture.
Fujisoft’s next-generation security system moves beyond merely detecting motion. It enables AI-based image recognition that dramatically increases detection accuracy and reduces false positives. Fujisoft completed a demonstration unit in 2025 and is now refining the solution for broader deployment.
At the core of the solution is the AMD Embedded+ platform. It combines an AMD Ryzen™ Embedded processor and a Versal™ adaptive SoC on a single board to enable AI inference and low-latency processing on a variety of sensors using programmable I/O. The pre-integrated architecture minimizes design complexity and costs, and it helps accelerate time to market.
“By combining both adaptive and x86 embedded technologies into a single, integrated solution, the AMD Embedded+ platform fully leverages Fujisoft’s strengths in both hardware and software development,” said Naoya Yanagitsubo, Fujisoft manager. “Through conversations with various customers, we have identified specific challenges, and we believe that Embedded+ is well positioned to address and solve these issues.”
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Apr 7, 2026 · via digitalterminal.in
Over-the-Air Computation Uses Radio Interference to Crunch Data Sensor networks could improve capacity faster than they grow Picture a highway with networked autonomous cars driving along it. On a serene, cloudless day, these cars need only exchange thimblefuls of data with one another. Now picture the same stretch in a sudden snow squall: The cars rapidly need to share vast amounts of essential new data about slippery roads, emergency braking, and changing conditions. These two very different scenarios involve vehicle networks with very different computational loads. Eavesdropping on network traffic using a ham radio, you wouldn’t hear much static on the line on a clear, calm day. On the other hand, sudden whiteout conditions on a wintry day would sound like a cacophony of sensor readings and network chatter. Normally this cacophony would mean two simultaneous problems: congested communications and a rising demand for computing power to handle all the data. But what if the network itself could expand its processing capabilities with every rising decibel of chatter and with every sensor’s chirp? Traditional wireless networks treat communication as separate from computation. First you move data, then you process it. However, an emerging new paradigm called over-the-air computation (OAC) could fundamentally change the game. First proposed in 2005 and recently developed and prototyped by a number of teams around the world, including ours, OAC combines communication and computation into a single framework. This means that an OAC sensor network—whether shared among autonomous vehicles, Internet-of-Things sensors, smart-home devices, or smart-city infrastructure—can carry some of the network’s computing burden as conditions demand. The idea takes advantage of a basic physical fact of electromagnetic radiation: When multiple devices transmit simultaneously, their wireless signals naturally combine in the air. Normally, such cross talk is seen as interference, which radios are designed to suppress—especially digital
Apr 7, 2026 · via spectrum.ieee.org