Many smartphones don’t detect face biometrics spoofs or properly warn consumers Biometric liveness detection remains a significant “flaw” and a “vulnerability” of most Android smartphones with facial unlocking. Most are still prone to simplistic and low-cost spoofs available to inexpert attackers, according to an analysis by Which?. The publication notes that iPhones are generally immune to spoofs with printed 2D photos, due to the depth-sensing capability of Face ID. Some newer Google Pixel devices were also not fooled by flat images in Which? testing. The convenience factor of native device face biometrics is identified as such sometimes, and Which? acknowledges that “some manufacturers have made strides in providing clearer warnings during setup.” Yet many Android smartphones do not, it says, including models from OnePlus and Motorola. OnePlus did just release a new phone with in-display 3D ultrasonic fingerprint biometrics from Qualcomm. Which? labs has tested 208 phones since October of 2022, and found 2D printed photos were good enough spoofs to fool the face biometric unlock systems of 133 devices, or 64 percent of them. Testing during 2025 revealed a 13 percent improvement, year-over-year, after a brutal 2024 in which the share of spoof-prone devices rose dramatically. Samsung’s Galaxy S26 has adequate biometric presentation attack detection (PAD), Which? says, but previous models including the Galaxy S25 do not. At least the manufacturer properly warns consumers that its facial recognition is a convenience feature, rather than a high-security one. While banking apps and digital wallets no longer accept 2D Android face biometrics as a secure authentication factor, Which? warns that users relying on face biometrics to unlock their phone risk a phone thief with their photo reading their text messages, sending emails from their account, which could allow them to reset passwords for other services, access photos and other sensitive documents
Apr 20, 2026 · via biometricupdate.com
Figures Abstract Human action recognition has become increasingly important for applications in security surveillance, healthcare monitoring, and smart environments. However, existing deep learning models typically require substantial computational resources, making deployment on resource-constrained edge devices challenging. To address this limitation, we propose TinyAct, a lightweight framework for real-time human action recognition that combines edge computing with cloud-based processing through knowledge distillation. TinyAct employs a 3D video autoencoder to extract compact spatiotemporal features from video sequences, coupled with classical machine learning classifiers for action prediction. The framework utilizes an AIoT (Artificial Intelligence of Things) architecture where feature extraction occurs on edge devices while classification is performed in the cloud, enabling real-time processing with reduced bandwidth requirements. To enhance performance, we implement knowledge distillation using the ILA-ViT-B/16 transformer as a teacher model to transfer temporal knowledge to our compact student architecture. Our experiments on the Kinetics-400 dataset demonstrate that TinyAct achieves competitive performance while maintaining computational efficiency. Using 16-frame video clips with 1024-dimensional latent features, Random Forest achieved the highest baseline accuracy of 57.00%, followed by SVM (55.00%) and XGBoost (54.00%). The autoencoder-based feature extraction significantly reduces computational overhead compared to end-to-end deep learning approaches while preserving essential spatiotemporal information for accurate action recognition. The knowledge distillation experiments reveal that training configuration critically affects performance, with non-pretrained student models achieving better results (15.11% with SVM) than pretrained ones under teacher supervision. This suggests that joint optimization of the encoder and classifier is essential for effective knowledge transfer in resource-constrained settings. TinyAct’s modular architecture enables flexible deployment across diverse hardware configurations, supporting both lightweight edge inference and cloud-based training pipelines. The framework demonstrates that effective human action recognition can be achieved without computationally intensive deep networks, making it suitable for smart surveillance systems, IoT applications, and embedded devices where computational resources are limited.
Apr 20, 2026 · via journals.plos.org
Przemek Wasinski Has Automated Plane Spotting, via an ADS-B-Tracking Motorized Camera A low-cost SDR dongle picks up planes' transponders, then feeds their location to a motorized camera linked to a Raspberry Pi 4. Developer Przemek Wasinski has made plane spotting an automated affair — by using a low-cost software-defined radio to pick up aircraft transponders and automatically train a camera on their location. "Aircraft in flight continuously broadcast information about themselves, including their location," Wasinski explains of how the project works. "These radio signals use a technology called ADS-B. My system receives these radio signals using a 1090MHz radio antenna. The signals are then processed by a software called Dump1090, which decodes the radio messages and converts the data into JSON format that can be used by plane_tracker.pu." Wasinski build is split into two parts. The first is the tracker itself, which picks up the ADS-B transmissions using a low-cost receive-only RTL-SDR software-defined radio dongle, decodes them, and plots the plane's location on a two-dimensional map laid out like a classic radar scope. The second part then takes this location data and puts it back into the real world — by training a Raspberry Pi HQ Camera Module, connected to a Raspberry Pi 4 Model B single-board computer and with a telephoto lens fitted, on the plane's location. "When an aircraft is close enough Plane Tracker will send its latitude, latitude and altitude to PlaneCam," Wasinski explains. "PlaneCam will then move the camera on the motorized pan-tilt mount to aim at the aircraft and take a picture. The picture taken by the Raspberry Pi Camera will then be analyzed with OpenCV to check whether a plane has been captured, after this the picture and image recognition results will be sent back to PlaneTracker." More information on the project is available
Apr 20, 2026 · via hackster.io
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Apr 20, 2026 · via youtube.com
DALLAS, April 20, 2026 (GLOBE NEWSWIRE) -- Restb.ai , the real estate industry’s leader in AI-powered computer vision technology, today announced it now reaches more than 1 million real estate agents through its growing network of MLS partnerships across the United States and Canada. With adoption spanning 26 new MLSs over the past 18 months, Restb.ai’s technology is believed to be the most widely deployed AI solution available to real estate agents in North America. Restb.ai’s rapid expansion reflects growing demand from MLSs looking to deliver smarter, more automated tools to their customers. By integrating AI directly into the MLS workflow, real estate agents gain access to a wide range of Restb.ai AI-powered capabilities, including image recognition, automated tagging, compliance insights, and enriched property data, without changing how they work. “These MLSs are leading the way in the deployment of practical and safe AI solutions agents can use right away,” said Dominik Pogorzelski , President, MLS at Restb.ai. “Agents are not being asked to learn new systems. Restb.ai technology is built into the systems they already use every day.” MLSs that have deployed Restb.ai technology for the first time in the U.S. over the past 18 months include ArkansasONE MLS , Beaches MLS (Florida), Billings Association of REALTORS ® (Montana), Charlottesville Area Association of REALTORS ® (Virginia), Coeur d’Alene MLS (Idaho), Colorado Real Estate Network , Indiana Regional MLS , Intermountain MLS (Idaho), MLS Technology, Inc. (Tulsa, Oklahoma), MLS United, LLC (Mississippi), Mammoth Lakes Board of REALTORS ® (California), MetroList ® MLS (California), New Mexico MLS , REALTORS ® Association of Indian River County Inc. (Florida), Realcomp (Michigan), Royal Gorge Association of REALTORS ® Inc. (Colorado), Greater Alabama MLS Inc , San Francisco Association of REALTORS ® (California), Sanibel and Captiva Island Association of REALTORS ® (Florida), Tulare County Association
Apr 20, 2026 · via markets.businessinsider.com
A new 'Perspective' article says generative AI may help scientists read cancer’s hidden complexity across images, molecules, and clinical data, opening a possible new path to smarter diagnosis, discovery, and treatment. Perspective: Tackling the complexity of cancer with generative models. Image Credit: Antonio Marca / Shutterstock A recent Perspective article published in the journal Cell argues that generative models could help address the complexity of cancer. The “Hallmarks of Cancer” provided a framework to systemize the understanding of cancer biology. They proposed a set of principles dictating the transformation of normal cells into malignant cells and subsequent cancer progression. The hallmarks represent a reductionist framework that has unified diverse observations, yielding valuable insights. However, an intentionally simple framework cannot adequately explain the multifaceted mechanisms of cancer. Thus, complementary tools are required to capture the complex, multiscale, and multimodal nature of cancer. In this paper, the authors proposed that generative models built on advances in artificial intelligence (AI) can address the complexity of cancer. AI for Cancer Detection and Biological Understanding AI has achieved significant strides in its ability to model complex patterns over the years. Advances in learning algorithms, data availability, and processing power have led to human-level or even higher accuracy in some tasks. The applications of AI to cancer include understanding, detection, and intervention. Much of the progress in AI for cancer has been in detection. The development of deep convolutional neural networks has significantly improved image classification performance. Examples include breast cancer detection using mammographic data, skin cancer classification using lesion images, and lung cancer detection using computed tomography data. Further, many advances in understanding cancer biology have resulted from improvements in its molecular characterization. As the value of epigenomics, proteomics, transcriptomics, and other -omics measures has become clear, there is growing interest in characterizing their high-dimensional
Apr 19, 2026 · via news-medical.net
Connections Unlimited Challenges Players To Group Words By Hidden Links Ellen Smith — April 19, 2026 — Tech References: connectionsunlimitedonline.github.io Connections Unlimited is a word-based puzzle game focused on identifying relationships between groups of terms. Players are presented with sets of words and tasked with organizing them into categories based on shared characteristics or hidden connections. The gameplay emphasizes vocabulary, pattern recognition, and associative thinking, often drawing on general knowledge and cultural references. It is designed as an ongoing experience with no fixed endpoint, offering continuous challenges rather than level-based progression. The game is typically used for casual entertainment as well as cognitive engagement, appealing to users interested in language and logic puzzles. It reflects a broader category of word games that prioritize mental agility and replayability. By removing ads and usage limits, the platform focuses on uninterrupted interaction. Its primary function is to provide an accessible and repeatable puzzle format centered on discovering conceptual links between words. Image Credit: Connections Unlimited The gameplay emphasizes vocabulary, pattern recognition, and associative thinking, often drawing on general knowledge and cultural references. It is designed as an ongoing experience with no fixed endpoint, offering continuous challenges rather than level-based progression. The game is typically used for casual entertainment as well as cognitive engagement, appealing to users interested in language and logic puzzles. It reflects a broader category of word games that prioritize mental agility and replayability. By removing ads and usage limits, the platform focuses on uninterrupted interaction. Its primary function is to provide an accessible and repeatable puzzle format centered on discovering conceptual links between words. Image Credit: Connections Unlimited Trend Themes 1. Continuous Play Cognitive Puzzles - Endless, non-level-based puzzle loops create new formats for sustained user engagement that can redefine retention metrics for casual games. 2. Ad-free Microlearning Entertainment -
Apr 19, 2026 · via trendhunter.com
German Society for Internal Medicine: "Treating people, not data" Staff shortages and more endanger quality of care, according to internists' congress. AI is supposed to fix it, but humans must always remain the focus. At the 132nd Congress of the German Society for Internal Medicine, physicians discussed the use of artificial intelligence, which goes far beyond pure pattern recognition. AI agents are intended to actively relieve doctors and nursing staff of routine tasks, thus counteracting staff shortages and increasing bureaucracy. At the same time, modern technology enables more differentiated diagnostics, the experts emphasized. Artificial intelligence in everyday hospital life is evolving from a consulting to an actively acting system. “We are moving from 'not just advice, but also action',” explained Prof. Jens Kleesiek, Director of the Institute for Artificial Intelligence in Medicine at Essen University Hospital, at a press conference for the congress. Given staff shortages and administrative overload, the use of such technologies is unavoidable: “We can no longer guarantee the quality of care, the security of supply, if we do not use further tools.” Videos by heise As a concrete example, Kleesiek cited “agentic AI,” which autonomously coordinates complex processes such as patient discharge or warns staff if an allergy has not been correctly noted in the record. At the same time, he cautioned that with all the technological support, “common sense should not be switched off.” The danger is to blindly trust technology, similar to a navigation system that drivers follow and “drive into the river or into a field somewhere.” The guiding principle must therefore be clear, according to Kleesiek: “We treat patients, not data.” Re-evaluation through data: The BMI under scrutiny The advancing digitalization also leads to a re-evaluation of established medical parameters. The complexity of metabolic research reaches far back into evolutionary history, as
Apr 19, 2026 · via heise.de
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Apr 19, 2026 · via youtube.com
The Internet remembers more than most people realize. Every photo that appears online can remain available for years, often without the person's knowledge. PimEyes, one of the most advanced face search tools on the Internet, responds to this reality. At first glance, it seems like a useful tool. In fact, however, it raises very sensitive questions about privacy, anonymity and control over one's own digital identity. The principle of operation is very simple. The user uploads a photo of a face and the system then uses artificial intelligence to search the publicly available Internet. Within a few seconds, it can display places where the same or very similar face can be found. Unlike conventional image searches, the technology does not focus on the context of the photo, but purely on biometric facial features. The result is links to specific websites where the person appears. The service itself claims that it does not identify specific people as such, but only connects similar photos across the Internet. According to the authors, PimEyes is primarily intended to have positive uses. Users can check where their photos are located and, if necessary, resolve their removal. At a time when content spreads extremely quickly and often without consent, it is a tool that can help protect one's own identity and digital footprint. At the same time, however, it is also necessary to speak openly to the other side. The same technology can be very easily abused. All it takes is a photo of a stranger and within a moment it is possible to find other images, social profiles or the context in which the person appears on the Internet. This significantly increases the risk of abuse, whether it is stalking, invasion of privacy or revealing identity without consent. This accessibility is a fundamental difference compared
Apr 19, 2026 · via letemsvetemapplem.eu
BlabbyAI Speech to Text is a voice input tool designed to convert spoken language into written text across desktop and browser environments. It enables users to dictate content directly into websites or applications, supporting workflows such as email writing, note-taking, and messaging. The platform offers multilingual transcription capabilities, accommodating a wide range of global users and use cases. By replacing manual typing with voice input, it aims to improve speed and accessibility in content creation tasks. It is typically used by professionals, content creators, and individuals seeking more efficient input methods or hands-free operation. The tool reflects a broader trend in productivity software toward speech-based interfaces, driven by advances in automatic speech recognition technology. Its primary function is to streamline text entry processes and reduce reliance on traditional keyboard-based input across digital platforms. Speech Recognition Tools BlabbyAI Enables Voice Typing Across Websites And Applications Trend Themes 1. Voice-first Productivity - Real-time dictation replacing keyboard input in everyday workflows creates potential for interfaces that prioritize speech as the primary mode of content creation. 2. Multilingual Speech Interfaces - Support for many languages opens possibilities for tools that normalize cross-language collaboration through accurate, localized transcription and translation layers. 3. Cross-platform Voice Integration - Seamless voice input across browsers and desktop applications suggests ecosystems where voice capabilities are universally available regardless of platform boundaries. Industry Implications 1. Enterprise Software - Embedding speech-to-text into productivity suites could substantially reduce meeting note burdens and accelerate internal documentation lifecycles. 2. Education Technology - Classroom and remote-learning platforms equipped with reliable transcription can expand accessibility and create richer study materials for diverse learners. 3. Customer Service & Contact Centers - High-quality, real-time transcription in support systems enables faster resolution metrics and more accurate capture of customer interactions for analytics.
Apr 19, 2026 · via trendhunter.com
Testing has revealed that smartphones from major brands including Samsung and Motorola can be unlocked using printed images of the owners face. Consumer experts have warned that this security loophole could be exploited by criminals to unlock devices and access personal information. Which?, the UK’s largest independent consumer organisation, has been carrying out lab tests on hundreds of phone models since 2022, assessing features from battery life to security features. While most smartphones now offer facial recognition to unlock mobile devices, Which?’s testing found that as many as 64% of phones – 133 devices since 2022 – could be tricked by a printed image. Phones that failed the organisation’s tests include top-of-the-range models such as the Oppo Find X9 Pro, which retails for upwards of £1,000. According to Which?, Samsung’s former flagship range of Galaxy S25 phones could all be fooled by a 2D photograph, while the some lower-priced Android phones also struggled, often relying on a standard 2D facial recognition system. Which? Found that the newest Google Pixel models and Samsung Galaxy S26 series passed their tests and Apple Face ID was considerably harder to trick. The non-profit says that some device cameras take flat pictures, which means they cannot always distinguish between a real person and a high-resolution photo. Most phones that failed Which?’s test did have an onscreen message warning that face recognition cannot be relied upon for security. Lisa Barber, Which? Tech Editor said: “These security flaws are far from isolated incidents. “The majority of Android phones we’ve tested in the last four years can be easily unlocked using a 2D image, and some manufacturers are still failing to adequately warn their users that this is the case. “We’d urge affected users to set up alternative methods of security, like a fingerprint or a PIN, which
Apr 19, 2026 · via news.stv.tv
Specialists from the Unified Center for Biometric Testing (ECBI) conducted the first testing of Russian facial recognition systems. Seven IT solutions were tested for accuracy, the press service of the Department of Information Technology (DIT) of Moscow reported. The tests involved four companies from Moscow and one from Chelyabinsk. Their biometric algorithms had to find similar faces in a database of 750 thousand images. How the algorithms were evaluated When evaluating IT solutions, the following parameters were taken into account: data collection reliability (processing images of a person in glasses, in a half-turn) and recognition accuracy (error rate). The final result was calculated based on the arithmetic mean of all metrics. Dmitry Golovin, Deputy Head of the DIT of Moscow, said that the algorithms analyzed images from city video surveillance cameras. The test participants demonstrated their developments in real, not laboratory conditions, he added. As a result, the market receives a transparent tool for selecting technologies for a specific business task. The DIT of Moscow also noted that the ECBI will regularly conduct such tests. This will allow tracking progress in the development of domestic biometrics. Read more materials on the topic: - In Russia, they began to let into trains using biometrics — how it works - Face instead of a passport: biometrics is gaining popularity in Russia - Payment by "face" in buses: a new biometric travel system will be launched in Moscow
Apr 19, 2026 · via www1.ru
Abstract At present, multi-scale learning is a popular and effective method to improve the accuracy of real-time semantic segmentation. However, these multi-scale methods do not consider the influence of CNN receptive field on the feature discriminability. They still suffer from the small receptive field and insufficient feature extraction, which limits the accuracy of real-time segmentation. To solve the problem, we propose a novel Triple-Branch Multi-Scale Network (TBMSNet) for real-time semantic segmentation. Specifically, in initial feature extraction stage, we propose the Simple Inverted Residual (SIR) module with reducing the number of input channels, using two successive SIR modules to initially extract features, which can enhance the feature extraction capability of lightweight backbone network. Subsequently, we design a new multi-scale triple-branch structure to parse detail, semantic, and boundary information respectively. In triple-branch structure stage, we propose the Dilation-wise Residual (DWR) module in Semantic branch, which combines the multi-scale detail and boundary branches down-sample semantic feature maps to 1/64. The design can extend the valid receptive field and improving the capture efficiency of multi-scale information. Besides, we also design a Multi-scale Semantic Aggregation Pyramid Pooling (MSAPP) module in semantic branch, which connects multi-scale pooling maps before the convolutional layer to form local and global context representations for further enriching the semantic information, and extract multi-scale features more efficiently. Experiments show that our TBMSNet achieves an accuracy of 80.5% mIoU on Cityscapes and an inference speed of 50.4 FPS, achieving the best trade-off between inference speed and accuracy. Similar content being viewed by others Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Corresponding authorshould be contacted if someone wants to request the data from this study. Code availability The code are available from the corresponding author upon reasonable request. References Long et
Apr 19, 2026 · via nature.com
DES MOINES – A plea deal has been reached in the murder trial of a woman accused of killing her stepfather. After being charged with Murder in the Second Degree in the shooting death of stepfather Anthony Hartmann, 29-year-old Sera Alexander entered a guilty plea to two amended charges—Involuntary Manslaughter (Class D Felony) and Reckless Use of a Firearm Causing Serious Injury (Class C Felony). Alexander’s trial began Monday at the Drake Legal Clinic in Des Moines, with first responders, as well as Alexander’s brother and mother, testifying. The prosecution argued that Alexander was driven by anger and hatred, not fear, in shooting Hartmann after he was in the house in May 2017. “While he was collecting his tools, she was collecting her loaded gun, she was focused, focused on confronting him and removing tony from her life once and for all,” said Assistant Polk County Attorney Shannon Archer. “The imminent threat was his presence” Defense attorneys, however, said a history of violence and abuse with the family made Alexander feel threatened. “Tony displayed a smorsgesborg of behaviors that instilled fear in the whole family, in Sera Alexander, and ultimately contributed to his death,” said defense attorney F. Montgomery Brown. Alexander’s mother and Hartmann’s estranged wife, Susan Hartmann, testified Wednesday that she didn’t feel safe in the home, often spending increased time at work. “I never knew when I was going to get hurt. When he wasn’t physically hurting me he was threatening. He would threaten to destroy the house,” Hartmann testified. “If I stayed, things would get destroyed in the house. If he wasn’t harming me physically … I never knew when he’d be on a rant and literally be up all night long screaming.” As part of the plea agreement, Alexander waives her right to appeal, and both
Apr 19, 2026 · via weareiowa.com
Abstract With advancements in big data and internet technologies, images are becoming central to professional and recreational activities. While watermarks are crucial for copyright protection, their robustness against common manipulations such as compression or filtering also makes their removal for legitimate restoration purposes highly challenging. Traditional approaches to watermark removal almost always require manual tuning of parameters and complex optimization, resulting in limited applicability in practical use. To address these issues, this paper presents an improved self-supervised convolutional neural network (CNN) for image watermark removal, enhanced with Particle Swarm Optimization for hyperparameter tuning. The proposed approach performs self-supervised learning to generate training data, while avoiding the preparation of clean reference images, and benefits from PSO-based optimization in pursuing faster convergence and higher restoration quality. Experimental results on the PASCAL VOC 2012 dataset show that the proposed PSO-SWCNN has achieved the best performance among several state-of-the-art methods with the highest SSIM and PSNR. This integrated approach offers an effective and efficient solution in removing watermarks from images and restoring them for research and archival purposes. Similar content being viewed by others Data availability Data are publicly available. The PASCAL VOC 2012 dataset, which was used for training and evaluating the models, can be accessed at: https://huggingface.co/datasets/nateraw/pascal-voc-2012Additional data, scripts, and code generated and/or analyzed during the current study are available at: https://github.com/maedeh-dashti/PSO-SWCNN. References Petitcolas, F. A., Anderson, R. J. & Kuhn, M. G. Information hiding-a survey. Proc. IEEE 87(7), 1062–1078 (1999). Islam, M. S. & Chong, U. P. A digital image watermarking algorithm based on DWT DCT and SVD. Int. J. Comput. Communication Eng. 3(5), 356 (2014). Cox, I., Miller, M., Bloom, J., Fridrich, J. & Kalker, T. Digital watermarking and steganography (Morgan kaufmann, 2007). Petitcolas, F. A. & Katzenbeisser, S. Information hiding techniques for steganography and digital watermarking (Artech House Computer
Apr 19, 2026 · via nature.com
DES MOINES – A plea deal has been reached in the murder trial of a woman accused of killing her stepfather. After being charged with Murder in the Second Degree in the shooting death of stepfather Anthony Hartmann, 29-year-old Sera Alexander entered a guilty plea to two amended charges—Involuntary Manslaughter (Class D Felony) and Reckless Use of a Firearm Causing Serious Injury (Class C Felony). Alexander’s trial began Monday at the Drake Legal Clinic in Des Moines, with first responders, as well as Alexander’s brother and mother, testifying. The prosecution argued that Alexander was driven by anger and hatred, not fear, in shooting Hartmann after he was in the house in May 2017. “While he was collecting his tools, she was collecting her loaded gun, she was focused, focused on confronting him and removing tony from her life once and for all,” said Assistant Polk County Attorney Shannon Archer. “The imminent threat was his presence” Defense attorneys, however, said a history of violence and abuse with the family made Alexander feel threatened. “Tony displayed a smorsgesborg of behaviors that instilled fear in the whole family, in Sera Alexander, and ultimately contributed to his death,” said defense attorney F. Montgomery Brown. Alexander’s mother and Hartmann’s estranged wife, Susan Hartmann, testified Wednesday that she didn’t feel safe in the home, often spending increased time at work. “I never knew when I was going to get hurt. When he wasn’t physically hurting me he was threatening. He would threaten to destroy the house,” Hartmann testified. “If I stayed, things would get destroyed in the house. If he wasn’t harming me physically … I never knew when he’d be on a rant and literally be up all night long screaming.” As part of the plea agreement, Alexander waives her right to appeal, and both
Apr 19, 2026 · via weareiowa.com
Can everyone use local AI? We tested it on a budget phone, and the results were disappointing. In April this year, Google released the new-generation open-source large model, Gemma 4. This time, it launched four versions at once, covering everything from mobile phones to workstations. The two smallest versions are specifically designed for mobile devices and are mainly for fully offline operation. This isn't really that rare, but more importantly, Google now wants mobile phones to run local models. You may have come across a lot of content about the actual installation and testing of Gemma 4. However, most of the existing online tests are conducted on the latest iPhones or flagship phones. These flagships are the latest models, with top-notch performance and computing power, so it's reasonable that they perform well. At this point, Xiaolei can't help but ask, If you use an ordinary Android phone that costs a few hundred to over a thousand yuan, with a mid-range processor and not top-notch computing power, can the local model still be used normally? How big is the gap compared to those flagship phones? (Image source: Photographed by Lei Technology) Digging deeper, is local AI destined to be an exclusive feature of flagship phones? We want to figure this out, so we directly took a thousand-yuan Android phone with a mid-range chip to test Gemma 4 and see how it performs. A thousand-yuan phone running a local model is a complete "disaster" The phone we used for this test is the vivo Y500 Pro, a typical thousand-yuan Android phone. Although it's not an old model, the overall performance of its SoC is still average. After all, its price is set like this, and there's really not much to say. It uses the MediaTek Dimensity 7400, manufactured by TSMC using a
Apr 19, 2026 · via eu.36kr.com
TOPEKA, Kan. — Following a federal investigation, the U.S. Department of Education’s Office for Civil Rights and the Student Privacy Policy Office concluded that four school districts in the Kansas City metropolitan area, including Topeka Public Schools, violated federal law through their transgender student policies and now face the potential loss of federal funding if no resolution is reached. According to The Topeka Capital-Journal, the possible federal funding cuts could affect Topeka USD 501, Kansas City USD 500, Olathe USD 233 and Shawnee Mission USD 512. As The Topeka Capital-Journal reported, the Trump administration announced that policies in the Kansas districts violated Title IX and the Family Educational Rights and Privacy Act, or FERPA. Further, the Trump administration stated in a press release that “Topeka Public Schools violated Title IX with policies that allow male students to use female restrooms, locker rooms, and changing rooms, as well as participate in single-sex athletics, based on ‘gender identity.’” The Topeka district has confirmed to the Office for Civil Rights that “male students have been allowed to use female restrooms and locker rooms based on ‘gender identity.’” Further, the Trump administration stated that USD 501 violated parents’ rights under FERPA by “concealing from parents” school records and information regarding a child’s “gender transition,” different pronouns, names and related matters. Kimberly Richey, a Trump administration official and assistant secretary for civil rights, stated, “These Kansas school districts have allowed ‘gender ideology’ to run amok in their schools.” She continued, stating that “These policies not only violate federal law, but are contrary to the sound judgment we expect from our educational leaders, and thoroughly disrespectful to parents who entrust school personnel to keep their children safe.” With this, the Trump administration warned it could pull federal funding from the four school districts. According to USD
Apr 19, 2026 · via davisvanguard.org
New intelligent infrastructure framework brings predictive operations, stronger security, and consistent performance across on-premise and cloud environments Ahmedabad (Gujarat) [India], April 17: Cygnet.One today announced an expanded direction for its Managed IT Services portfolio with the introduction of Cygnet STRATA, a layered infrastructure framework built to support modern businesses that depend on stable, secure, and high-performing IT environments. As IT systems take on greater operational responsibility, the cost of outages, security gaps, and performance slowdowns continues to rise. Many organizations still rely on reactive support models that respond after issues occur. Cygnet.One is positioning its managed services approach to move beyond that model, focusing on predictability, visibility, and continuous improvement across the infrastructure lifecycle. At the center of this shift is STRATA, a six-layer infrastructure stack designed to connect physical systems with cloud ecosystems while enabling real-time monitoring, analysis, and response. Built on AIOps principles, STRATA integrates telemetry ingestion, event correlation, anomaly detection, and automated remediation into a unified operating model. This allows infrastructure to shift from fragmented monitoring to coordinated, intelligence-driven operations. STRATA operates across six core layers. The SENSE layer focuses on physical infrastructure. It uses telemetry pipelines, sensor-based monitoring, and AI-driven diagnostics to continuously track servers, storage systems, and environmental conditions such as temperature, power, and network health. This layer builds a live operational baseline and detects early signs of hardware degradation or capacity stress. The TRANSMIT layer manages signal flow across the infrastructure. It aggregates and normalizes data streams from multiple sources, filters noise, and prioritizes actionable alerts. This ensures that only relevant signals are passed to operations teams and centralized NOC environments, reducing alert fatigue and improving response accuracy. The REASON layer applies AIOps intelligence. It uses pattern recognition, event correlation, and predictive modeling to identify anomalies across systems. By linking events across compute, storage,
Apr 19, 2026 · via ahmedabadmirror.com