4chan won’t play by UK age check rules, raising question about enforcement potency If the UK doesn’t like how 4chan operates, it can shut the site down. That’s the gist of the message from the online message board best known for being an incubator for misogyny, in response to demands from UK regulator Ofcom that the site fall in line with the UK’s Online Safety Act (OSA), and pay for violations. In keeping with its generally adversarial stance, 4chan says it won’t follow Ofcom’s rules because “the United Kingdom lost the American Revolutionary War,” and as such UK speech law doesn’t apply to companies based in the U.S. In a letter from its lawyer, Preston Byrne, the firm says it “reserves all rights and waives none,” and punctuates the statement with an image of giant cartoon hamster Nigel J. Whiskerford dressed as Godzilla – per Byrne’s explanation on X, “a private international law service of process joke.” “I told Ofcom in Oct that their letters, which were not properly served, would be shredded for my pet hamster’s enclosure,” Byrne writes. From the beginning, 4chan has treated Ofcom’s demands as a joke. Ofcom has continued to prosecute 4chan, issuing a fine of £450,000 (about $596,000) to the site for “not having age checks in place to prevent children from seeing pornography on its site,” and an extra £70,000 (about $92,000) for not doing a risk assessment and not being complete enough in its terms of service. More fines are coming. But 4chan’s response raises the question: what good is enforcement if foreign companies simply ignore it? Debate over where responsibility for online content lives The question is primarily one of jurisdiction. In the U.S., the First Amendment reigns as holy writ, and American companies are happy to leverage it for their
Apr 6, 2026 · via biometricupdate.com
Facial recognition software will be deployed on drones in the Channel to help prosecute people smugglers steering migrant boats bound for Britain under Home Office plans, The Times can reveal. Border Force is trialling military-grade, radar-enabled cameras that will be able to identify an individual up to half a mile away, regardless of whether they have changed their outfit or appearance. Border Force officers have reported pilots of the migrant dinghies who change their outfits after they see a British rescue boat approaching to blend in with the other passengers. The boat pilots have even been seen shaving, so they cannot be identified as responsible for facilitating the journey, according to Border Force sources. This enabled them to evade prosecution for assisting unlawful immigration, an offence that can carry a sentence of life imprisonment. The Home Office hopes that using the precision technology will help boost the number of people smugglers who are prosecuted. However, the technology requires extensive trials and testing in order to overcome practical, legal and ethical challenges. The measure is the latest initiative being pursued by the Home Office to target the criminal gangs facilitating the crossings. A total of 4,766 migrants have crossed so far this year, which is down 28 per cent compared with the same period last year. Last week, two people died after a dinghy carrying about 50 migrants got into serious difficulty shortly after leaving Gravelines beach in northern France. There are fears that the failure to renew a deal to pay for French beach patrols could lead to a surge in crossings this summer. Shabana Mahmood, the home secretary, agreed last week to extend the present deal by two months until the end of May, after Britain and France failed to reach an agreement on a new three-year deal. Talks
Apr 6, 2026 · via thetimes.com
First implemented in October 2023, the facial recognition scanners haven’t been a main point of entry for Universal Islands of Adventure recently. But we noticed that they have returned. Facial Recognition For Entry During a visit on April 5, we noticed the facial recognition devices were available again at Universal Islands of Adventure. The machines are still often used for the passholder line, but haven’t been available for non-passholder ticket entry for some time—potentially even since 2025. Photo recognition entry is not required, and guests may opt out of it. The facial recognition machines for the non-passholder ticket entry were not in use this past weekend either. This technology is not currently in use at Universal Studios Florida, which implemented it about a month after Universal Islands of Adventure in November 2023. Facial recognition cameras were later installed in 2024 at express lanes throughout Universal Studios Florida. Here is the updated information about photo validation/facial scanning from Universal Orlando’s Privacy Info Center. As a note, although this webpage appears to be current and on the site, it still refers to the photo recognition “technical rehearsal period” which took place a few years ago. What is Photo Validation? Photo Validation is a faster and more seamless way for our Guests to access select experiences throughout Universal Orlando Resort during their visit. How is Photo Validation being used at Universal Orlando? We use Photo Validation to verify tickets and ticket holders – making it a faster and more seamless way for our guests to access select experiences during their visit. Photo Validation is currently used at the park entrances of Universal Islands of Adventure, Universal Studios Florida, and Universal Volcano Bay. Now, Guests may also use Photo Validation to verify and use their Universal Express Pass at select attractions throughout Universal Islands
Apr 6, 2026 · via wdwnt.com
On July 14, Tennessee grandmother Angela Lippswas arrested and spent more than five months in jail for a crime in North Dakota she did not commit. Her wrongful arrest stemmed from an AI facial recognition match, despite evidence showing she was not the person who committed the crime and had never even visited the state. Unfortunately, her story is not unique. Wrongful arrests tied to technology are happening across the country. Robert Dillon, from Lee County, Florida, was arrested on a warrant out of Jacksonville—hundreds of miles away—accused of luring or enticing a child. Facial recognition technology had produced a 93% match to his photo. His image was even placed in a photo lineup for a witness two months later, who then identified him. But beyond the tech-generated match and the lineup, no evidence connected Dillon to the crime. His charges were eventually dropped and his record cleared, but not before his life was upended. In another case in Orlando, Florida, a man was accused of fraud and theft tied to a hotel stay. The initial encounter was captured on body camera footage when the suspect was issued a trespass warning. Law enforcement believed the man gave a false identity, leading officers in another county to arrest Beau Burgess on those charges. Burgess repeatedly insisted he was innocent and provided a timecard proving he was at work—70 miles away—when the incident occurred. When a local news outlet requested body camera footage and followed up with the Orlando Police Department, officials initially denied that facial recognition had been used. However, a later internal investigation revealed officers had used the FACES program, relying on a decades-old mugshot and placing Burgess in a photo lineup. A hotel employee then identified him. Ultimately, the state attorney dropped the case. Orlando Police Department’s Policy on
Apr 6, 2026 · via rightoncrime.com
In recent city council meetings in Dunwoody, Georgia, a spokesman for Flock Safety, a Georgia-based firm that provides automated license plate readers, has found himself in the hot seat again. For two months running, some residents of the affluent north Atlanta suburb in the region’s tech corridor have been demanding an end to the city’s contract with the security firm, which has drawn similar protest from California to New York. Between a recent change in terms of service that removed a line assuring customers that the company does not own and will not sell customer data – done to eliminate redundancy, Flock says – and videos circulating of hackers showing how they had obtained access to live video feeds from Flock cameras, Dunwoody residents and some members of the city council have been in in revolt. “When you hear from our police department saying they trust Flock, it’s clear that our police are too lazy to verify what a vendor such as Flock says,” said Joe Hirsh, a Dunwoody resident, haranguing the council over privacy breaches last week. “You and I both know the next time Flock is misused in our city, you will turn a blind eye because none of you are trustworthy with our records.” Kerry McCormack, Flock Group Inc’s public relations manager for the east coast, spent about half an hour explaining that the company doesn’t own the images its increasingly ubiquitous license plate reader cameras take, and that it doesn’t sell the data. “One hundred per cent of data, which is the photo of the public license plate, is owned by our customers,” McCormack said. “So, you own that data. It is never sold. We don’t have that in our model. It is written into your contract. We do not sell data.” Skepticism of these statements
Apr 6, 2026 · via theguardian.com
In a decisive move to combat rising digital fraud, the Reserve Bank of India (RBI) is evaluating the deployment of facial recognition technology across ATMs, bank branches, and service counters. The initiative signals a shift toward AI-driven identity verification to strengthen trust in India’s rapidly expanding digital banking ecosystem. The proposed system would act as an additional security layer, enabling real-time identity authentication. By verifying customers through facial biometrics, banks can significantly reduce unauthorized transactions and identity fraud, which have grown more sophisticated in recent years. Experts highlight that cybercriminals increasingly exploit social engineering and digital manipulation to bypass traditional controls. AI-powered facial recognition can help detect anomalies instantly, flag suspicious behavior, and trigger preventive actions before financial damage occurs. To assess feasibility, the RBI has asked both public and private sector banks to submit feedback by month-end. The inputs will cover cost implications, technical readiness, and operational challenges, helping regulators determine the pace and scale of implementation. However, the rollout is not without hurdles. Banks will need to invest in high-quality cameras, biometric systems, and seamless integration with existing ATM and core banking infrastructure, which could be expensive—especially for smaller institutions. Alongside this, the RBI has proposed stricter compensation norms for digital fraud victims. The draft suggests up to 85% compensation for smaller frauds, capped at ₹25,000, reinforcing accountability while encouraging stronger preventive frameworks. As digital transactions surge, security remains the biggest concern. Facial recognition could redefine banking safety, but its success will depend on balancing innovation with privacy, compliance, and robust governance. See What’s Next in Tech With the Fast Forward Newsletter Tweets From @varindiamag Nothing to see here - yet When they Tweet, their Tweets will show up here.
Apr 6, 2026 · via varindia.com
Abstract The increasing use of medical imaging in healthcare settings presents a significant challenge due to the additional workload for radiologists, yet it also offers opportunity for enhancing healthcare outcomes if effectively leveraged. Artificial Intelligence (AI)-based 3D medical image retrieval holds the potential to alleviate radiologists’ burden by offering evidence-based diagnostics and predictions that can enhance the scale and accuracy of radiologists, while simultaneously supporting output verification for safety and regulatory compliance. Despite its promise, the field of 3D medical image retrieval lacks established evaluation benchmarks, comprehensive datasets, and rigorous evaluation studies. This paper aims to address these gaps by introducing the first benchmark for 3D Medical Image Retrieval (3D-MIR) and evaluating various pre-trained models and implementation approaches for retrieval. The benchmark includes four anatomies (Liver, Colon, Pancreas, and Lung) imaged using computed tomography (CT). A range of 3D image search strategies are explored, including those that use aggregated 2D slices/3D volumes (Image-to-Image) and text embeddings from popular foundation models as queries (Text-to-Image). Additionally, novel multi-modal and supervised fine-tuning approaches are investigated to generate multi-modal embeddings for 3D image retrieval. The paper provides quantitative and qualitative assessments of each approach, along with an in-depth discussion offering insights for future research and solutions to support clinical decision-making and healthcare applications. To foster advancement in this field, our benchmark, models, and code are made publicly available. Data availability The code and datasets generated and analyzed during the current study are available in this repository: https://github.com/abachaa/3D-MIR. References Harry, E. et al. Physician task load and the risk of burnout among us physicians in a national survey. Jt. Comm. J. Qual. Patient Saf. 47, 76–85 (2021). Wang, D. et al. Medfmc: A real-world dataset and benchmark for foundation model adaptation in medical image classification. arXiv preprint arXiv:2306.09579 (2023). Yang, J., Shi, R. & Ni,
Apr 6, 2026 · via nature.com
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Apr 6, 2026 · via cureus.com
Microsoft announced three new in-house AI models, MAI-Transcribe-1, MAI-Voice-1, and MAI-Image-2, expanding its capabilities across speech recognition, voice generation, and image creation. The models are now available through Microsoft Foundry and the MAI Playground, with the company emphasizing improved performance, speed, and cost efficiency. MAI-Transcribe-1 is designed for speech-to-text transcription and delivers state-of-the-art performance across the top 25 most-used languages based on the FLEURS benchmark. The model is optimized for real-world environments and delivers batch transcription speeds 2.5 times faster than Microsoft’s previous Azure Fast offering. Microsoft also highlighted its strong price-to-performance positioning compared to other large cloud providers. MAI-Voice-1 focuses on generating natural, expressive speech, preserving speaker identity across long-form content while enabling developers to create custom voices with only a few seconds of audio. The model can generate up to 60 seconds of audio per second and is built for high GPU efficiency, supporting scalable deployment for enterprise use cases. It is already being integrated into Copilot experiences, including audio-based features and podcasts. MAI-Image-2 enhances Microsoft’s image generation capabilities, delivering faster performance while maintaining high-quality outputs suitable for professional creative workflows. The model has ranked among the top three on the Arena.ai leaderboard and is being rolled out across Microsoft products, including Bing and PowerPoint. Early enterprise adoption includes WPP, which is using the model for large-scale creative production. Microsoft is positioning these models as “better, faster, and cheaper” than competing offerings, with aggressive pricing aimed at developers and enterprise customers. Pricing starts at $0.36 per hour for MAI-Transcribe-1, $22 per million characters for MAI-Voice-1, and $5 per million tokens for text input and $33 per million tokens for image output for MAI-Image-2. The company also emphasized its broader vision of “humanist AI,” focusing on building models that are aligned with human needs and designed for safe, responsible
Apr 5, 2026 · via pulse2.com
Artificial Intelligence (AI) is transforming the modern world at an incredible pace, creating powerful opportunities across industries. From healthcare to finance, entertainment to education, AI is driving innovation and reshaping how businesses operate. If you are planning your future, exploring the Top Careers in Artificial Intelligence can help you secure a high-demand, future-proof profession. In this article, we will explore the Top AI Careers, their roles, required skills, and why they are in such high demand. Whether you are a student or a professional looking to switch careers, understanding the Top Careers in Artificial Intelligence can guide you toward a successful path. Machine Learning Engineer One of the most in-demand roles among the Top Careers in Artificial Intelligence is a Machine Learning Engineer. These professionals design algorithms that allow machines to learn from data and improve over time without being explicitly programmed. To excel in this field, you need strong programming skills (Python, R), knowledge of statistics, and experience with frameworks like TensorFlow or PyTorch. Machine Learning Engineers are at the core of many Top AI Careers due to their role in building intelligent systems. Data Scientist Data Scientists are key players in the Top Careers in Artificial Intelligence landscape. They analyze large datasets to extract insights and help businesses make data-driven decisions. This role requires expertise in data analysis, statistics, machine learning, and visualization tools. The increasing reliance on data makes this one of the most important Top AI Careers today. AI Research Scientist AI Research Scientists focus on advancing the field of artificial intelligence. They work on cutting-edge technologies such as deep learning, natural language processing, and computer vision. This is one of the most advanced Top Careers in Artificial Intelligence, often requiring a PhD in computer science or a related field. These professionals push the boundaries of
Apr 5, 2026 · via academiamag.com
AI can identify mushrooms in seconds by analyzing a photo and matching it against massive datasets using advanced computer vision. Powered by models like Convolutional Neural Networks, the system detects patterns such as cap shape, color, gills, and texture to predict the species instantly. Instead of relying on bulky field guides, users simply upload an image. The AI scans features, compares them with thousands of labeled samples, and delivers accurate results within seconds. This makes mushroom identification faster, safer, and accessible—even for complete beginners exploring nature. AI mushroom identification uses intelligent algorithms to recognize fungi from images. It blends data science with visual recognition to simplify a traditionally complex process. Rather than memorizing species, users rely on trained systems that “learn” from millions of images and improve over time. Together, these technologies simulate expert-level identification—but in seconds. Manual identification is a skill that takes years to master, especially in Mycology. Many mushrooms look nearly identical but differ significantly in safety, making the process risky for beginners. The genus Amanita contains both visually appealing and highly toxic mushrooms. Misidentification here can have serious consequences. AI reduces these risks by offering quick, data-backed insights. AI follows a structured process to ensure fast and reliable results. The user takes or uploads a clear photo of the mushroom. The system scans: The AI compares extracted features with a trained dataset of thousands of mushroom images. The system returns: This entire process takes just a few seconds. AI-powered tools offer advantages that traditional methods cannot match. These benefits make AI tools ideal for both casual users and serious foragers. AI is transforming how people interact with nature and fungi. Imagine walking through a forest and spotting an unfamiliar mushroom. Instead of guessing, you scan it with an AI tool and instantly learn its identity and
Apr 5, 2026 · via ocnjdaily.com
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Apr 5, 2026 · via hackernoon.com
I write about tech every day, and taking screenshots in Windows is a big part of my work. And for the longest time, I relied on the Windows Snipping Tool for taking screenshots and doing basic annotation. It's actually not that bad, and recent Windows updates have made Snipping Tool even better: it now includes Quick Markup, a color picker, and screen recording. However, it still falls short compared to my current favorite, Greenshot, a lightweight, free, and open-source screenshot tool. Greenshot lets me do more than just basic editing Obfuscation, auto-cropping, speech bubbles, it's all there One of the most glaring Snipping Tool misses is the lack of a good image editor. Yes, you can click the Edit in Paint option and make your edits there, but it's an added step to something that should be there from the get-go. What you do get in the Snipping Tool itself is basic markup, cropping, and optical image recognition (OCR). Granted, these features are usually enough for the average user who seldom takes screenshots, but they don't nearly cut it for users who take screenshots frequently and want to modify them in more ways. Greenshot comes with a more fleshed-out editor, which is impressive considering how lightweight the tool is. One of my favorite features is the ability to obfuscate sensitive information in the editor itself: this lets me hide my email, the IMEI, and other sensitive device info when taking readers through certain Windows Settings that display them. Additionally, there's a counter that lets me number multiple steps in one screenshot. And this is just the tip of the iceberg. Greenshot also lets you add speech bubbles, text boxes, shapes (or draw freehand), and effect presets to your screenshots. Again, you may not use these features all the time, but
Apr 5, 2026 · via makeuseof.com
Angela Lipps was at her Tennessee home babysitting in July when armed federal agents showed up and arrested her in connection with a string of bank fraud incidents in North Dakota.
Just a moment.
We are getting your experience ready.
Angela Lipps was at her Tennessee home babysitting in July when armed federal agents showed up and arrested her in connection with a string of bank fraud incidents in North Dakota.
Just a moment.
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Apr 5, 2026 · via nbcnews.com
Abstract As a key indicator of structural integrity and in-service performance, crack detection is essential for the condition assessment and preventive maintenance of bridges. To address the challenges of detecting cracks with various scales and shapes under low-contrast backgrounds in bridge inspection tasks, this paper proposes a robust detection method named CLGDS. It is based on YOLO11 with enhanced feature fusion and SIoU loss optimization, which effectively improves the accuracy and robustness of crack identification. The proposed framework includes three key innovations. (1) A Cross Stage Partially Large Separable Kernel Attention (C2LSKA) module is integrated in the backbone network to enhanced the representation of crack features in the case of morphologically diverse and complex background interference. (2) A Gathering and Distributing (GD) mechanism serves as the neck network, facilitating multi-scale feature fusion and improving the detection performance for cracks of varying scales and geometrically irregular edges. (3) A Scylla-IoU (SIoU) loss function is introduced to replace the commonly used Complete IoU (CIoU) loss. By explicitly incorporating directional sensitivity and multi-scale adaptability, SIoU effectively mitigates angle-dependent misalignment during bounding box regression. Experimental results demonstrate that CLGDS achieves a mean average precision (mAP@50) of 93.5%, outperforming YOLOv5, YOLOv8, and YOLO11 by margins of +1.5%, +0.6%, and +1.2%, respectively. Furthermore, it attains a mAP@50-95 of 68.5%, significantly higher than that of YOLOv5 (61.3%), YOLOv8 (62.6%), and YOLO11 (65.3%). These results validate the effectiveness of CLGDS in accurate bridge crack detection, providing a solid technical foundation for automated structural health monitoring and preventive maintenance. 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 Zinno, R., Haghshenas, S. S., Guido, G. & VItale, A. Artificial intelligence and structural health monitoring of bridges: A review of the state-of-the-art. IEEE
Apr 5, 2026 · via nature.com
Hong Kong International Airport (HKIA) has switched on 12 additional Face Easy e-Channels, bringing the arrival concourse total to 26 and sharply expanding the city’s fully touch-less immigration capacity. Unlike traditional e-Channels that require an ID-card swipe and fingerprint check, the upgraded lanes authenticate travellers solely through facial recognition. Once the gate opens, clearance takes under seven seconds—around a third of the legacy process. The Immigration Department says the roll-out will continue in phases until 2027, when 52 biometric lanes will replace all ageing kiosks. For organisations coordinating frequent trips through HKIA, specialist services like VisaHQ can streamline the visa side of the journey. Their online portal (https://www.visahq.com/hong-kong/) walks applicants through Hong Kong employment, dependant and business visa requirements, freeing travel managers to focus on flight bookings and biometric enrolment logistics. With passenger throughput at HKIA rebounding to 61 million in 2025, automation is critical to keeping corporate travellers moving: peak-hour queues dropped by an average of 18 minutes after the first batch of lanes went live last September. Employers with frequent-flyer staff should ensure workers update their smart ID cards and consent to facial-image use; holders of valid dependants’ and employment visas are automatically eligible. The technology will be integrated with One-ID boarding later this year, allowing end-to-end curb-to-gate processing without paper documents. Privacy concerns remain subdued—Hong Kong’s Personal Data Privacy Commissioner reports no complaints linked to the system so far—but companies may wish to update internal travel policies to reflect biometric opt-out options for sensitive assignments. For organisations coordinating frequent trips through HKIA, specialist services like VisaHQ can streamline the visa side of the journey. Their online portal (https://www.visahq.com/hong-kong/) walks applicants through Hong Kong employment, dependant and business visa requirements, freeing travel managers to focus on flight bookings and biometric enrolment logistics. With passenger throughput at HKIA rebounding
Apr 5, 2026 · via visahq.com
Abstract Conventional end-to-end deep neural networks often degrade under domain shifts and require costly retraining when deployed in unpredictable, noisy environments. Inspired by biological brains, we propose a modular framework where each module is a recurrent neural network pretrained via a simple, task-agnostic protocol to learn robust, transferable features. This shapes stable yet flexible low-dimensional representations as invariant input-driven continuous attractor manifolds embedded in high-dimensional latent space across different tasks, supporting robust transfer and resilience to temporal perturbations. At deployment, only a lightweight adapter needs training, allowing rapid adaptation to new tasks. Validated on gesture and rehabilitation action recognition tasks, our framework achieves accuracy competitive with state-of-the-art methods, especially in few-shot settings, while requiring an order of magnitude fewer parameters and minimal training. By integrating biologically inspired attractor dynamics with cortical-like modular composition, the framework offers a practical path toward robust, continual adaptation in real-world information processing. Data availability All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. The customized RGB rehabilitation action dataset76 is available at https://doi.org/10.5281/zenodo.16454040 and https://doi.org/10.5281/zenodo.16473362. Code availability Computer code for all simulations and analysis of the resulting data is available at https://doi.org/10.5281/zenodo.16441066. References Xing, W., Li, M., Li, M. & Han, M. Towards robust and secure embodied AI: a survey on vulnerabilities and attacks. Preprint at arXiv https://doi.org/10.48550/arXiv.2502.13175 (2025). Liu, J. et al. Towards out-of-distribution generalization: a survey. Preprint at arXiv https://doi.org/10.48550/arXiv.2108.13624 (2021). Roy, N. et al. From machine learning to robotics: challenges and opportunities for embodied intelligence. Preprint at arXiv https://doi.org/10.48550/arXiv.2110.15245 (2021). Jaeger, H. & Haas, H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 304, 78–80 (2004). Barry, C., Hayman, R., Burgess, N. & Jeffery, K. J. Experience-dependent rescaling of entorhinal grids. Nat. Neurosci. 10, 682–684 (2007). Anderson, M.
Apr 4, 2026 · via doi.org
04 Apr MACHINE LEARNING EXPERT WITNESS TESTIMONY FOR ML & AI TRIAL TESTIFYING NEEDS Machine learning expert witnesses for trial testifying note that ML is a subset of AI focused on systems that improve through experience. In legal contexts, reviewers and thought leaders analyze algorithms, assess predictive models, and of course also as best machine learning expert witnesses evaluate the integrity of data used in ML systems. Thought leaders’ expertise helps courts understand whether models function as intended, comply with standards, or caused errors or harm. Top machine learning expert witnesses tend to have advanced knowledge in data science, statistics, and computer programming. SMEs and KOLs interpret training data, model accuracy, overfitting, and algorithmic biases. Famous machine learning expert witnesses get retained in patent disputes, software contract cases, product liability claims, and regulatory investigations involving predictive analytics, recommendation systems, autonomous systems, or data-driven decision-making tools. Via providing independent analysis, detailed reports, and testimony in court, any given machine learning expert witness helps clarify whether models are reliable, ethical, and accurate. Folks turn technical jargon into accessible explanations and can cross-examine opposing experts to ensure impartial evaluation of ML claims. 50 Sample Products and Areas Machine Learning Expert Witnesses Cover - Credit scoring systems - Fraud detection models - Autonomous vehicles - Predictive maintenance systems - Speech recognition software - Image recognition models - Chatbots - Recommendation engines - Algorithmic trading platforms - Smart home automation - Robotics - Personalized marketing tools - Facial recognition applications - AI-driven HR tools - Autonomous drones - Self-driving forklifts - Predictive healthcare software - AI for legal research - Sentiment analysis tools - E-commerce analytics - Customer churn prediction - AI supply chain systems - Predictive policing tools - Insurance claim models - Stock market forecasting algorithms - Natural language processing systems - AI
Apr 4, 2026 · via futuristsspeakers.com
Residents rallied outside Troy City Hall on Friday over the city's contract with Flock and its license-plate reading cameras.
Mayor Carmella Mantello issued a public safety emergency on Wednesday to fund the company's contract, after the city council ordered the auditor to pause payments.
Mantello accuses the council of inappropriate interference with public safety.
City Council President Sue Steele argues Mantello is violating the city charter.
Protesters raised concerns over citizen privacy.
“Flock also does human detection. Flock also does sound detection. These are all getting fed into the same national database. And where’s the line with public safety and privacy? I think that we have a lot of questions about that,” Dierdre Shea of Troy said.
Flock says it only looks at vehicles and does not use facial recognition.
Apr 4, 2026 · via spectrumlocalnews.com
This Week’s Awesome Tech Stories From Around the Web (Through April 4) Every week, we scour the web for important, insightful, and fascinating stories in science and technology. Image Credit NASA/Joel Kowsky Share Artificial Intelligence How AI Helped One Man (and His Brother) Build a $1.8 Billion CompanyErin Griffith | The New York Times ($) "From his house in Los Angeles, Mr. Gallagher, 41, used AI to write the code for the software that powers his company, produce the website copy, generate the images and videos for ads and handle customer service. ...This year, they are on track to do $1.8 billion in sales." Computing The First Quantum Computer to Break Encryption Is Now Shockingly CloseKarmela Padavic-Callaghan | New Scientist ($) "A quantum computer capable of breaking the encryption that secures the internet now seems to be just around the corner. Stunning revelations from two research teams outline how it could happen, with one suggesting that the current largest quantum machine is already more than halfway towards the size needed." Space Four Astronauts Are Now Inexorably Bound for the MoonEric Berger | Ars Technica "For NASA and the Artemis II crew members, [Thursday's main engine burn] marked a point of no return for more than a week. About three-quarters of the American population has not witnessed humans leaving low-Earth orbit in their lifetimes. The last time this occurred was 1972, with the final Apollo Moon mission." Be Part of the Future Sign up to receive top stories about groundbreaking technologies and visionary thinkers from SingularityHub. Computing New Fiber-Optic Record Allows 50,000,000 Movies to Be Streamed at OnceMatthew Sparkes | New Scientist ($) "Faster speeds have been achieved before in highly regulated experiments, but this work crucially used existing cables that have been heavily used, have dirty connectors, sit underneath a
Apr 4, 2026 · via singularityhub.com