The Lutheran Foundation awards Health Professions Scholarships to Trine University students The Lutheran Foundation is pleased to announce three Health Professions Scholarship recipients from Trine University. June 04, 2026 Spaces are still available in Trine University’s 2026 Allen School of Engineering and Computing summer camps, which will take place July 22-24. The Engineer Your Future and Tech Titans Computing camps provide high school students with the opportunity to gain hands-on experience and learn from Trine University’s expert faculty. Campers stay overnight in Trine’s apartment-style residential facilities and enjoy meals at the award-winning Whitney Commons Café. The Engineer Your Future camp exposes students to engineering fields such as biomedical, chemical, civil, electrical, design and mechanical engineering through hands-on activities. Past activities have included building an electronic cicada, assembling a 3D-printed prosthetic hand, designing and constructing a cantilevered bridge, making ice cream and building and launching a water-powered rocket. The Tech Titans Computing Camp introduces students to virtual reality, Python programming, robotics and embedded computers, AI image recognition and cybersecurity. The camps expose students to specific engineering and computing disciplines and examples of projects that engineering and computing majors at Trine University might design. Cost for the camps is $100. For more information, visit trine.edu/camps.
Jun 4, 2026 · via trine.edu
Figures Abstract Background Postoperative cerebrovascular events, including transient ischemic attacks, infarctions, and hemorrhages, remain a significant concern in pediatric patients with Moyamoya disease (MMD)undergoing surgical revascularization. This study aimed to develop an explainable deep learning-based classification model using intraoperative arterial blood pressure (ABP) waveform analysis for postoperative cerebrovascular events in pediatric patients undergoing surgery for MMD, with exploratory analysis of associated waveform-derived physiologic features. Methods This retrospective study included 181 pediatric patients (≤18 years) who underwent revascularization surgery for MMD, with an independent temporal holdout cohort of 79 patients reserved for validation. ABP signals were preprocessed using detrending, pulse segmentation, and normalization, then converted into image representations for deep learning classification. Various convolutional neural network (CNN) models, including ResNet50, ResNet34, DenseNet121, VGG16, and VGG19, were evaluated against Vision Transformer (ViT) architectures. Multiple image transformation methods were tested, and Grad-CAM analysis and statistical comparisons of waveform-derived physiologic features were conducted between patients with and without postoperative cerebrovascular events. Results The optimal model configuration achieved the best performance using raw pulse waveforms with three consecutive pulses per image. CNN-based models outperformed ViT-based models, with the highest internal classification performance observed using raw pulse waveforms (AUROC = 0.772, SD = 0.070).In the independent temporal validation cohort, the model achieved an AUROC of 0.738 ± 0.011 at the patient level. Grad-CAM visualization highlighted the diastolic runoff phase as a region of interest for classification. Four waveform-derived features related to arterial compliance were significantly associated with postoperative cerebrovascular events (p < 0.05). Conclusions In this study, CNN-based deep learning models demonstrated the feasibility of predicting postoperative cerebrovascular events from intraoperative ABP waveforms, with diastolic runoff dynamics emerging as a potentially relevant physiologic pattern. These findings are exploratory and require prospective multi-center validation before clinical application. Citation: Park J-B, Shin Y, Kim J, Kim YJ, Lee
Jun 4, 2026 · via journals.plos.org
Meta has quietly embedded face-recognition technology for its smart glasses into an app downloaded to millions of phones, according to a WIRED analysis of the company's software. Code discreetly added to Meta’s AI app over multiple updates this year shows that the feature, internally called “NameTag,” identifies people captured by the glasses’ camera and, when activated, alerts the wearer when it recognizes someone. The discovery of NameTag in the live Meta AI app shows that Meta had begun shipping face-recognition code to users' phones while publicly describing it as something the company was still “thinking through.” In April, Meta said if it were to utilize face recognition, it wouldn't be rolled out without first taking "a very thoughtful approach." But WIRED found that as early as January, core components of the system had been integrated into software distributed to millions of people. Though not yet enabled, NameTag sits inside a Meta AI companion app that's been downloaded over 50 million times and is necessary for use of key features of its smart glasses, including Ray-Ban and Oakley models. If activated, it will transform faces captured by Meta's glasses into unique biometric signatures, commonly known as faceprints, and check each one against faceprints stored on the user’s phone—a database that’s currently configured to receive updates from Meta. Recognized faces will trigger notifications, while the rest are cropped, indexed, and saved to a folder marked “pending.” | Got a Tip? | |---| | Are you a current or former Meta employee who wants to talk about the company's technologies? We'd like to hear from you. Using a nonwork phone or computer, contact the reporter securely on Signal at dmehro.89 or dell.3030. | NameTag would revive a type of technology Meta said it had sunsetted in 2021, when the company announced it would
Jun 4, 2026 · via wired.com
Sponsored by Google Cloud Choosing Your First Generative AI Use Cases To get started with generative AI, first focus on areas that can improve human experiences with information. The systems, powered by Cosmos 3, are designed to accelerate development of autonomous vehicles, robots and vision AI systems. Nvidia has released a spate of new physical AI research tools, agent workflows and open source models to train more advanced AI systems for the real world. Unveiled this week at the Computer Vision and Pattern Recognition conference in Denver, the updates build on Nvidia's recently launched Cosmos 3 world foundation model and are designed to help researchers automate key stages of physical AI development, including simulation, synthetic data generation, policy training and evaluation. Physical AI refers to AI systems that interact with and operate in the physical world, including self-driving vehicles, industrial robots and embodied AI agents. The company said the new capabilities address a major challenge facing engineers in the industry: creating scalable workflows to train and test AI virtually before real-world deployment. “The core challenge in physical AI research isn’t simply developing stronger models. It’s building a full workflow around them,” Nvidia said in a blog post. “Today, these steps are fragmented across separate tools, slowing the pace of experimentation as researchers struggle to piece them together.” Among the announcements are new agent skills integrated across Nvidia Omniverse, Isaac Sim, Isaac Lab and Cosmos, enabling developers to automate tasks such as scene reconstruction, simulation setup, environment generation and reinforcement learning workflows. For autonomous vehicle development, Nvidia introduced tools to help researchers address the industry's “long-tail problem” --difficult-to-capture driving scenarios that are critical for training and validation. To bridge this gap, Nvidia said its AI agents can now automate the reconstruction of real-world driving environments from fleet data and generate synthetic
Jun 4, 2026 · via aibusiness.com
Amazon faces backlash for AI data center boom amid 30,000 job cuts, Seattle halts new data center projects.
Amazon engineers criticized the company for investing $200 billion in AI data centers while cutting 30,000 corporate jobs, raising concerns about resource use and workforce impact. Seattle City Council responded by approving a one-year moratorium on ...
Jun 4, 2026 · via pluang.com
BuzzFeed GamesIf You Can Solve This Color Puzzle In Less Than 3 Minutes, You Have Perfect Color VisionHuedoku #37! Thursday means the weekend is almost here — treat yourself. 🎨✨Posted 17 hours agocommentFacebookPinterestLinkby Crystal RoBuzzFeedBuzzFeed StaffHi, I’m Crystal, a Senior Editor based in Los Angeles and creator of BuzzFeed’s “That Got Dark” newsletter. Huedoku is a daily color puzzle with simple rules and a satisfying solve. It's like sudoku, but with colors instead of numbers. Sign up here to get notified every time we publish a new Huedoku! One more tomorrow — come back for Huedoku #38 and finish the week strong! 🌈 🌈 New Huedoku drops every weekday at 4:00 a.m. PT / 7:00 a.m. ET. 🧩🗂️ Huedoku Archive — Every past puzzle, all in one place! Comments
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Jun 4, 2026 · via buzzfeed.com
Abstract Deep diffractive neural networks have emerged as an all-optical computing paradigm that overcomes the bottlenecks of traditional electronic computing. However, traditional deep diffractive neural networks are typically limited to single-task processing. Here we demonstrate an orbital angular momentum multiplexing diffractive neural network (OAM-MDNN) that completes several recognition tasks simultaneously by exploiting orthogonal OAM modes to encode and decode information. We develop an end-to-end auto-optimizing strategy that improves mode utilization efficiency by approximately 14 times and the peak signal-to-noise ratio by approximately 14.4% compared with manual encoding. We experimentally demonstrate a 10-mode multiplexing recognition task for 40 object categories, including handwritten digits, letters and fashion items, with an average recognition accuracy of 86.8%. Further experiments validate the scalability and performance of the network for up to 100 object categories. Theoretically, we also show that OAM-MDNN can be scaled to up to 40 modes times 10 classes (400 classifications), showing potential for further extension. In addition, our OAM-MDNN supports simultaneous multitask input, enabling parallel recognition with high accuracy and minimal intermode crosstalk. We applied our architecture to real-world tasks, such as gesture recognition in numerical simulations, which demonstrated its practical application potential in biometric identification. OAM-MDNN paves the way for high-capacity and multi-dimensional parallel optical information processing based on OAM multiplexing. 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 print issues and online access $259.00 per year only $21.58 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 Similar content being viewed by others Data availability All
Jun 4, 2026 · via nature.com
Xiao-I Regains Full Nasdaq Compliance, Securing Continued Listing for ADSs Claim 55% Off TipRanks - Unlock trusted, data-backed investing tools with TipRanks Premium, from analyst ratings and forecasts to breaking news and portfolio analysis. - Discover high-conviction stock picks and new investing opportunities with the TipRanks Smart Investor Newsletter An announcement from Xiao-I Corp. ADR ( (AIXI) ) is now available. Xiao-I Corporation, a Shanghai-based cognitive intelligence specialist, develops enterprise AI products spanning natural language processing, voice and image recognition, machine learning, and affective computing for Chinese industries. Since 2001, it has built a broad portfolio designed to support digital transformation and intelligent upgrading across multiple commercial applications. On April 23, 2026, Xiao-I regained compliance with Nasdaq’s minimum market value requirement after its publicly held shares stayed above $15 million for ten consecutive business days. Subsequently, Nasdaq confirmed on May 29, 2026 that the company also met the minimum $1.00 bid price standard for ten straight trading days, restoring full compliance and ensuring its ADSs continue trading on the Nasdaq Global Market under the ticker AIXI. The resolution of both December 2025 deficiency notices removes an overhang on Xiao-I’s U.S. listing status and reduces near-term delisting risk for investors. By securing continued access to Nasdaq’s capital markets, the company preserves an important funding and visibility platform as it competes in the fast-evolving enterprise AI sector. Spark’s Take on AIXI Stock According to Spark, TipRanks’ AI Analyst, AIXI is a Neutral. The score is weighed down primarily by very weak financial performance (sharp 2025 revenue contraction, rapidly widening losses, negative equity, and ongoing cash burn). Technicals provide only modest support (near-term rebound vs. shorter moving averages and oversold signals, but weak momentum and below the 200-day trend). Valuation is also constrained by loss-making results (negative P/E) and no dividend yield data.
Jun 4, 2026 · via theglobeandmail.com
Hi. My name is Hoan Ton-That, and I’m addicted to Claude Code. I’m a lifelong programmer and the founder and former CEO of Clearview AI, the country’s first major facial recognition company that used AI, and where I wrote the first version of our software myself.
When I started Clearview, it ended up landing on the front page of The New York Times in January 2020 with the headline “The Secretive Company That Might End Privacy as We Know It.” We had built a groundbreaking facial recognition technology, which allowed law enforcement to search billions of public images just by uploading a photo of a face. The technology helped law enforcement solve crimes involving children, human trafficking, and financial fraud.
The reaction to our new technology raised concerns from privacy advocates and the public. Today’s simultaneous fear and excitement around AI coding tools remind me of what I went through with Clearview, and what any new technology goes through.
Two months ago I started using Claude Code, OpenAI’s Codex, and Cursor. I’m having the most fun I’ve ever had programming, and I can now build software that used to take months in a matter of days.
Jun 4, 2026 · via thefp.com
At the end of the day, an AI model is only as good as the data behind it. More examples, greater variety, and higher-quality inputs lead to better, more reliable results. But without the right training dataset, even the best architecture will fall short. In this article, we’ve rounded up five powerful sources for image datasets that are helping developers and researchers build smarter AI models in 2026. Whether you’re working on object detection, image classification, or facial recognition, you’ll find a dataset worth exploring. What is an image dataset? An image dataset is a structured collection of labeled images used to train, test, and evaluate computer vision models. By exposing AI to thousands or even millions of examples, these datasets help models learn to recognize patterns and identify objects, powering everything from facial recognition and object detection to image classification. Common use cases for image datasets - Reverse image search Image datasets are the foundation of reverse image search, a feature that allows users to find similar or identical images by uploading a picture or providing a URL instead of typing text. It’s widely used by stock content platforms like DepositPhotos, e-commerce apps such as Vinted, and search engines like Google. By training on large collections of labeled images, AI models learn to compare visual features and match an uploaded image with visually similar content across the web or within a platform. As a result, users can quickly identify a product in an image or find a higher-resolution version of a photo without typing a single word. - Behavior analysis Image datasets are also central to behavior analysis, where AI models are trained to detect and interpret human actions, facial expressions, and behavioral patterns. This can be used to monitor a driver’s attention on the road or measure student
Jun 4, 2026 · via markets.financialcontent.com
Amazon adds AI-generated images to US search to help shoppers refine product searches.
Amazon has introduced AI-generated images in its US online shopping search to visually illustrate product concepts and improve search accuracy. These images are not of actual products but serve to guide customers who may not know exact product terms,...
Jun 4, 2026 · via pluang.com
Amazon has just been hit with a class-action lawsuit over its controversial facial recognition feature in Ring video doorbell cameras. The lawsuit was filed on Monday in Seattle by Virginia resident Charles Sigwalt. The suit seeks $5 million in damages. Last fall, Amazon launched a new "Familiar Faces" feature inside Ring doorbells. Utilizing AI, Familiar Faces scans and identifies visitors to a Ring owner's home. When Familiar Faces recognizes a regular visitor — whether it's a family member, mailman, or delivery driver — Ring can tell users who is at their door instead of providing a generic notification. Familiar Faces is completely optional to use, and Ring owners can turn the feature off if they want. However, as the lawsuit points out, visitors to a Ring doorbell owner's home can't consent before their face is scanned. "Millions of other Americans passed by a Ring security camera and unknowingly had their facial recognition information collected," reads the lawsuit. Ring has long faced criticism from privacy advocates. In fact, when the Familiar Faces feature was announced in September, it too faced swift blowback from advocacy groups like the EFF, who said that it violated state privacy laws. "Many biometric privacy laws across the country are clear: Companies need your affirmative consent before running face recognition on you," said an EFF report at the time. The EFF report also pointed out that the Ring feature was unavailable in certain states due to biometric privacy laws. U.S. Senator Ed Markey also warned about the issues with Familiar Faces in a letter demanding Amazon cancel the rollout of the feature last year. "This announcement represents a dramatic expansion of surveillance technology, creating vast new privacy and civil liberties risks," Senator Market wrote. "Americans should not have to fear being tracked and recorded while visiting a
Jun 4, 2026 · via sea.mashable.com
On Monday, a Virginia man filed a class-action lawsuit against Amazon Ring, claiming its facial recognition feature violated his privacy and that of millions of other Americans. The lawsuit, filed by Charles Sigwalt in Seattle federal court, seeks at least $5 million from the retail giant. The case focuses on a Ring feature that uses AI to detect and remember the faces of friends and family. The feature, which arrived on Ring security cameras and video doorbells in 2025, is available only to Ring subscribers who opt into both Familiar Faces and smart alerts on their Ring device. When Familiar Faces is activated, Ring sends personalized phone alerts that identify people by name (based on the profiles users create) when those individuals approach a home. The problem is that the facial recognition software scans and categorizes everyone who passes by the camera, not just family and friends who might have profiles. Ring can also detect the faces of nearby drivers, mail carriers and strangers, potentially even people walking down a nearby street (aided by the newest 2K and 4K resolution devices Ring released, which can gather finer details farther away). Sigwalt's lawsuit focuses on consent and the storage of biometric data. Although laws can vary by state and haven't always kept pace with this new technology, recording faces without consent could violate privacy rights. In Washington state, where Amazon has one of its headquarters, consumers have some control over access to their personal data. Another sticking point is that the Ring app doesn't automatically delete the faces it captures but keeps them for 30 days. While Ring says this face data is encrypted and stored so users can take their time creating face profiles, it's unclear whether the data can be used to train its AI features or for other
Jun 3, 2026 · via cnet.com
The Walt Disney Company is facing a $5 million class action lawsuit alleging Disneyland and Disney California Adventure failed to properly disclose the use of facial recognition technology at park entrances and collected sensitive biometric data from visitors, including children, without consent. The lawsuit, filed May 15 in federal court... Read More » Amazon Faces Class Action Over Ring Facial Recognition Feature Amazon is facing a class action lawsuit in federal court over claims that its Ring doorbell cameras used facial recognition technology to scan, identify, and store people’s faces without their consent. The complaint was filed on June 1 by Virginia resident Charles Sigwalt in federal court in Seattle, where Amazon has one of its headquarters. Sigwalt claims Ring’s “Familiar Faces” feature creates a digital faceprint of visitors who appear in front of enabled cameras, allowing the system to recognize them later without their knowledge or consent. According to the lawsuit, Sigwalt’s facial data was collected while he visited friends and family members who had Ring cameras using the feature. He claims he never bought a Ring device, never agreed to Ring’s terms of service, and never gave Amazon permission to collect or store his biometric information. Amazon acquired Ring in 2018 for about $1 billion. Familiar Faces is an optional Ring feature that provides personalized doorbell alerts. Instead of receiving a generic alert that a person is at the front door, a Ring customer can label frequent visitors and receive a notification identifying a specific person. Ring says users can turn the feature on or off and manage the faces stored in their personal directory. Consent is the central problem raised by the complaint because the person using the Ring camera is not always the person being identified. A homeowner may choose to activate Familiar Faces, but Sigwalt
Jun 3, 2026 · via lawcommentary.com
Figures Abstract To address the limitations of single-image feature information and the insufficient recognition capability of traditional power quality disturbance (PQD) identification systems, this paper proposes a PQD recognition method based on feature-image combination and an improved ResNet-18, following the concept of feature fusion. First, the PQD signal is subjected to variational mode decomposition (VMD) to obtain a series of intrinsic mode functions (IMFs) and a residual component. Second, the IMFs, residual component, original disturbance signal, and Subtract component are vertically concatenated into a component matrix, from which a color feature-component image is generated via a signal-to-image transformation method. Third, the original disturbance signal is processed using continuous wavelet transform (CWT) to produce a time–frequency scalogram. Finally, the color feature-component image and the wavelet time–frequency image are combined and input into an improved six-channel ResNet-18 for training and disturbance classification. Simulation analyses of the proposed PQD identification method are conducted and compared with commonly used recognition systems. The results demonstrate that the proposed method exhibits strong noise robustness, effectively extracts PQD feature information, and achieves higher recognition accuracy. Citation: Zhang J, Zhao Y, Zhang J, Bai Z (2026) Research on anomaly detection and operational status evaluation methods for smart electricity meters based on hybrid deep learning. PLoS One 21(6): e0350561. https://doi.org/10.1371/journal.pone.0350561 Editor: Keshun You, University of South China, CHINA Received: January 12, 2026; Accepted: May 14, 2026; Published: June 3, 2026 Copyright: © 2026 Zhang 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, provided the original author and source are credited. Data Availability: All relevant data are within the manuscript and its Supporting Information files. Funding: This work was supported in part by the State Grid Science and Technology Project:
Jun 3, 2026 · via journals.plos.org
Facial Recognition and Emotion Detection Using Quantum Neural Networks (QNN)
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Jun 3, 2026 · via springerprofessional.de
Amazon and its subsidiary brand, Ring, are now facing a lawsuit in Virginia, with a plaintiff from the state alleging that the smart home devices of their friends and family collected and stored their images. The plaintiff said that the Ring camera's facial recognition technology and tools were used by the company to take their image and keep it without consent. Amazon Ring Faces Privacy Lawsuit After Alleged Violations Reuters reported that Amazon is now facing a lawsuit from a Virginia man involving the company's smart home brand, Ring, and the brand's doorbell cameras and its specific feature. Charles Sigwalt, the plaintiff, sued Amazon in a federal court in Seattle, and the lawsuit focuses on the feature of Amazon's Ring cameras called "Familiar Features." The man who raised the concern to the court is not a Ring user but claims that whenever he passes by the doors of friends and family members' homes, the smart doorbell camera took a photo of his face. According to Ring, the Familiar Faces feature is one of the latest technologies on the cameras, which uses facial recognition tech and what Amazon calls "advanced intelligence" to recognize people who are at or pass by doors. For people who have already registered on their Ring app, whenever a familiar face passes by, it will no longer alert users that there is a "Person at Front Door." Rather, Ring will say "[Name] at Front Door." Virginia Plaintiff Said Ring Kept Photos from Facial Scans Because of this exact intuitive feature that tells users to register and keep a profile of another person so that they would be recognized when they are at the door, Sigwalt alleged that the company did not ask for his consent to be identified by the Ring camera. According to Sigwalt, the feature
Jun 3, 2026 · via techtimes.com
Microsoft launches new MAI family of AI models for reasoning, voice, coding, and images Microsoft used its Build 2026 developer conference on Tuesday to announce a new family of in-house AI models, alongside a slew of other news. The announcements, delivered during CEO Satya Nadella's conference keynote, span the company's full product stack, from silicon to operating system to cloud infrastructure. Besides the new AI models, highlights include Microsoft Scout, a new personal agent for workplace tasks, and an upcoming Microsoft Surface Ultra laptop designed to run large AI workloads locally. The centerpiece of this new family is MAI-Thinking-1, Microsoft's first reasoning model. It's a mid-sized, 35 billion active parameter model with a 128K context window built for high efficiency and performance, but importantly, at a low-token cost. "MAI-Thinking-1 was designed to be good at complex multi-step instructions, long context reasoning, and code generation," said Kyle Daigle, Microsoft Developer CMO and COO of GitHub, at a virtual media briefing ahead of the keynote. According to Daigle, MAI-Thinking-1 was built from scratch on commercially licensed data. The company says independent evaluators preferred it over Anthropic's Claude Sonnet 4.6, and that it matches Claude Opus 4.6 on the SWE Bench Pro coding benchmark. Six additional MAI models were announced, covering image generation, transcription, voice, and code: You May Also Like The new models are: MAI-Thinking-1 MAI-Image-2.5 and a Flash variant MAI-Transcribe-1.5 MAI-Voice-2 and a Flash variant MAI-Code-1 How can you try the new MAI models? Per Microsoft, MAI-Thinking-1 is available in Microsoft Foundry as a private preview. The MAI-Image-2.5 models are already live in PowerPoint and OneDrive, and will be arriving soon in Foundry. MAI-Code 1 is available now in Copilot and VS Code. Microsoft said that MAI-Transcribe-1.5 will be available soon in 43 languages, while MAI-Voice-2 and a Flash variant are
Jun 3, 2026 · via mashable.com
Amazon faces class action suit over Ring facial recognition feature Amazon has just been hit with a class-action lawsuit over its controversial facial recognition feature in Ring video doorbell cameras. The lawsuit was filed on Monday in Seattle by Virginia resident Charles Sigwalt. The suit seeks $5 million in damages. Last fall, Amazon launched a new "Familiar Faces" feature inside Ring doorbells. Utilizing AI, Familiar Faces scans and identifies visitors to a Ring owner's home. When Familiar Faces recognizes a regular visitor — whether it's a family member, mailman, or delivery driver — Ring can tell users who is at their door instead of providing a generic notification. You May Also Like Familiar Faces is completely optional to use, and Ring owners can turn the feature off if they want. However, as the lawsuit points out, visitors to a Ring doorbell owner's home can't consent before their face is scanned. "Millions of other Americans passed by a Ring security camera and unknowingly had their facial recognition information collected," reads the lawsuit. Ring has long faced criticism from privacy advocates. In fact, when the Familiar Faces feature was announced in September, it too faced swift blowback from advocacy groups like the EFF, who said that it violated state privacy laws. "Many biometric privacy laws across the country are clear: Companies need your affirmative consent before running face recognition on you," said an EFF report at the time. The EFF report also pointed out that the Ring feature was unavailable in certain states due to biometric privacy laws. U.S. Senator Ed Markey also warned about the issues with Familiar Faces in a letter demanding Amazon cancel the rollout of the feature last year. "This announcement represents a dramatic expansion of surveillance technology, creating vast new privacy and civil liberties risks," Senator Market
Jun 3, 2026 · via mashable.com
Amazon faces lawsuit over Ring facial recognition software A Virginia resident is suing Amazon for privacy violations after the e-commerce company’s Ring video doorbell camera allegedly used facial recognition technology to record and store images of his face without his consent. Charles Sigwalt, who filed a lawsuit on Monday in Seattle federal court, where Amazon has one of its headquarters, alleges that Ring’s “Familiar Faces” feature uses facial-recognition software to scan anyone who passes by the doorbell camera and categorizes them using artificial intelligence. The system then collects a “face print” that allows it to re-identify the person, according to his complaint, which seeks class-action status. “When plaintiffs and class members entered the homes and businesses of places which had Ring cameras that deployed Familiar Faces, they did not consent to have their privacy rights violated at the entrance way,” the suit alleges. Sigwalt alleges Ring collected his facial recognition data without warning while he was visiting friends’ and family members’ homes. He believes the company is still storing his biometric data, according to the lawsuit. Amazon declined to comment on the suit. “Familiar Faces” draws criticism Ring introduced the “Familiar Faces” feature in September 2025, billing it as a way for owners of its doorbell camera to receive more personalized alerts when someone arrives at their residence. Instead of seeing “Person at Front Door,” for example, they might receive an alert with a name, such as “John at Front Door.” “Your camera learns to recognize friends, family and frequent visitors over time,” the company says on its website. Users can turn the feature on and off, according to Ring. Groups like the nonprofit Electronic Frontier Foundation have pushed back on the feature, claiming it violates people’s privacy. The biometric data could be used for mass surveillance or be leaked
Jun 3, 2026 · via wdef.com