The integration connects AI-powered image recognition from the store floor directly into Pitcher's commercial workflows, giving field teams the visibility and direction needed to win at retail. DENVER, May 26, 2026 /PRNewswire/ -- Pitcher, the AI-native sales enablement platform for enterprise commercial teams, today announced a strategic partnership with EasyPicky, a specialist in retail execution optimization and field data collection for consumer goods companies. The partnership brings together two platforms already trusted by leading CPG manufacturers, including Mondelēz International, one of the world's largest snack companies and the makers of globally recognized brands like Oreo and Cadbury. "The strategic alignment of Pitcher and EasyPicky represents a powerful convergence of two critical capabilities: meaningful sales representative engagement with store managers and the precise execution and validation of in-store display standards for merchandising teams," said Rensilin Pathrose, Senior Director of Digital Experience, Digital Business Transformation & Digital Commerce at Mondelēz International. "Together, this integration bridges the gap between sales and shelf-level compliance, delivering end-to-end visibility across the retail execution lifecycle." EasyPicky gives field teams instant visibility into shelf conditions, from product availability to out-of-stocks, merchandising compliance, and display placement — all captured via a short smartphone video, even offline. That intelligence now flows directly into Pitcher, where it becomes the foundation for Next Best Action (NBA) recommendations, prioritized visit planning, and real-time commercial guidance. This empowers commercial leadership to replace field rep guesswork with data-driven decision-making at scale, impacting store visits, display negotiation, and on-shelf outcomes. Connecting Strategy to Field Performance The new partnership solves a common challenge across CPG companies: turning Perfect Store data into real-time action that reps can take to capitalize on in-store opportunities and capture lost revenue. Both platforms are designed for field realities: offline-capable, mobile-first, and built to work in environments where connectivity is unpredictable and every
May 26, 2026 · via prnewswire.com
The longest whale journey ever recorded links Australia to Brazil An international team has documented humpback whales making record-breaking crossings between eastern Australia and Brazil, with one individual confirmed travelling 15,100 kilometres - the longest movement ever recorded for the species. An international research team has documented humpback whales travelling more than 14,000 kilometres across open ocean, crossing between breeding populations in eastern Australia and Brazil. The findings, published in Royal Society Open Science, represent the longest confirmed movements ever recorded for the species. The breakthrough was made possible by comparing tens of thousands of photographs of whale flukes – the distinctive tail markings that act as a natural fingerprint for individual animals. Drawing on a dataset of 19,283 high-quality fluke images collected between 1984 and 2025 from eastern Australia and Latin America, the team used automated image-recognition software to identify potential matches before independently verifying each one by eye. The photographs were contributed by both professional scientists and citizen scientists via the global platform Happywhale. From nearly 20,000 individual whales spanning more than four decades of data, two animals emerged as having crossed between the two regions – a figure representing just 0.01% of identified individuals. The first whale was photographed in Hervey Bay, Queensland in 2007, resighted in the same area in 2013, and then recorded off the coast of São Paulo, Brazil in 2019. The straight-line ocean distance between those two breeding grounds is approximately 14,200 kilometres – roughly equivalent to the distance from Sydney to London. The second case involved a whale first photographed in 2003 at the Abrolhos Bank, Brazil’s primary humpback nursery off the coast of Bahia, within a boisterous group of nine adults. Some 22 years later – in September 2025 – the same animal was spotted alone in Hervey Bay, Australia, marking
May 26, 2026 · via oceanographicmagazine.com
Is Neuro-Symbolic AI (NSAI) more suitable for Indian education? Read here to understand its advantages for Indian Education. Neuro-Symbolic Artificial Intelligence (NSAI) is a hybrid AI framework that combines the strengths of neural networks (learning from data) and symbolic reasoning systems (rule-based logic). It aims to create AI systems that are not only intelligent but also explainable, reliable, and context-aware. Traditional AI models such as Large Language Models (LLMs) largely depend on statistical prediction, whereas NSAI integrates reasoning and knowledge structures with learning capabilities. Is Neuro-symbolic AI more suitable for the Indian education system? What is Neuro-Symbolic AI? NSAI merges two complementary AI approaches: - Neural Component (Learning/Perception) The neural network component handles: - Pattern recognition - Speech processing - Image recognition - Language understanding - Handling unstructured data Examples: - Understanding handwritten answers - Identifying speech in Hindi, Tamil, Bengali, or Odia - Recognising diagrams or visual inputs This acts as the “eyes and ears” of the system. - Symbolic Component (Reasoning) The symbolic system works using: - Explicit logical rules - Knowledge graphs - Ontologies - Human-readable reasoning pathways Examples: - Mathematical formulas - Grammar rules - Scientific principles - NCERT curriculum concepts This acts as the “brain” of the system. Working Mechanism Input: Neural network processes information – Converts into symbols – Symbolic engine applies rules – Generates fact-based output. Example: A student asks: “Why does an object fall to the ground?” Traditional LLM response: May generate an answer from statistical patterns and occasionally produce incorrect details. NSAI response: - Recognises the question - Maps it to the Newtonian mechanics knowledge graph - Applies symbolic laws of gravity - Produces a verified explanation Limitations of Traditional LLMs in Indian Education Infrastructure mismatch: Large AI models require: - Massive GPUs - Data centers - High electricity consumption -
May 26, 2026 · via clearias.com
The findings set new records for the greatest distances ever confirmed between sightings of individual humpback whales anywhere in the world. “Discoveries like this are only possible because of investment into long-term multi-decadal research programs and international collaboration,” Griffith University Ph.D. Candidate and co-author Stephanie Stack said. “These whales were photographed decades apart, by different people, in opposite parts of the world, separated by two different oceans, and yet we can connect their journey.” By comparing tens of thousands of photographs of whale tails, also known as “flukes”, the team identified two individual whales that had been photographed in both eastern Australia and Brazil. One whale was first photographed in Hervey Bay, Queensland, in 2007, and was seen again in the same area in 2013 before turning up off the coast of São Paulo, Brazil, in 2019. These two breeding grounds are separated by a minimum straight-line ocean distance of about 14,200 km—roughly the distance from Sydney to London. Because only the start and end points of the whale’s journey were documented, the actual route taken, and therefore the true distance swum, remains unknown. The other whale was first photographed in 2003 at the Abrolhos Bank—Brazil’s main humpback whale nursery off the coast of Bahia—in a large, boisterous group of nine adults. Twenty-two years later, in September 2025, it was spotted alone in Hervey Bay, Australia, representing a travel distance of 15,100 km, making this the longest distance ever documented between sightings of the same individual humpback whale on record. The study drew on 19,283 high-quality fluke photographs collected between 1984 and 2025 from eastern Australia and Latin America, contributed by both scientists and citizen scientists through the global platform Happywhale. By running these photographs through an automated image-recognition algorithm and then independently verifying every potential match by eye, the
May 26, 2026 · via ecomagazine.com
Police deploy face tech in response to beach party - Published Adverts for an unofficial beach party on social media have prompted the police to deploy live facial recognition technology. "Significant numbers of young people" are expected to travel to Southend-on-Sea on Tuesday and gather by the seafront, Essex Police said. Flyers promoting the event online encouraged attendees to bring their own drinks and indicated that drugs could be available. A police spokesman said: "Anyone coming here intending to commit crime will be dealt with swiftly and robustly." It followed a busy Bank Holiday weekend when thousands of people visited the seaside city in Essex. The beach party has been advertised online as both the "Southend Takedown" and the "32C Southend Beach Step". Nitrous oxide and marijuana were also promoted as potentially available, although one flyer told people to create "no problems". Police are expected to have a highly visible presence at the city's railway stations, seafront and High Street throughout the day. They have imposed a dispersal order across the whole of the district until Thursday morning and been given extra stop and search powers. "We expect the vast majority of people to enjoy the seafront responsibly," the spokesman said. "However, those who do not should expect to be identified, stopped and, where appropriate, arrested." Ten people were sentenced in 2025 after a similar "beach rave" led to violence erupting between "two rival gangs" on the seafront the year before. The defendants, aged between 15 and 19, were given prison terms of up to eight years at Basildon Crown Court. Do you have a story suggestion for Essex? Contact us below. Get in touch Your Voice Follow Essex news on BBC Sounds, Facebook, external, Instagram, external and X, external. Related topics - Published16 July 2025 - Published2 August 2024
May 26, 2026 · via bbc.co.uk
Digital dragnet: When images online destroy lives Public wanted notices are increasingly used for trivial cases. Experts warn of disproportionate infringements of fundamental rights and call for reform. It sounds like an absurd joke from the digital world, but in November 2025 it was bitter reality on the website of the tabloid newspaper „Berliner Zeitung“. Under an official police wanted poster showing a young man in a drugstore, the headline proclaimed that a Pokémon card thief was being sought. Because the fan did not pay the nearly 10 euros for one of the coveted mini tin boxes in Brandenburg, the police resorted to a sharp sword of law enforcement: public wanted notices via the press. In a post for the Grundrechte-Report 2026 (Basic Rights Report 2026), which Netzpolitik.org published upon the release of the "alternative report on the protection of the constitution", aspiring legal scholar Athena Möller puts her finger on the wound. With such minor offenses, she explains, the suspicion arises "that we are dealing with a disproportionate interference with the right to informational self-determination." Publicly branded Similar reports have often been found in the media over the past few months. The co-editor of the volume warns that this should not only alarm data protection advocates. The spectrum of people who could suddenly find themselves in the digital spotlight without their consent is broad. It ranges from witnesses and missing persons to suspects, among whom there are always wrongly accused individuals. For example, in February, the Magdeburg police searched for a man who had pocketed a lost wallet in a supermarket using press appeals. As it turned out, he was an honest finder: the wallet had long been back in the hands of its rightful owner by the time the search began. Nevertheless, the high-resolution photos of the wrongly
May 25, 2026 · via heise.de
Vadzo Imaging Explains V4L2 Driver Development for Embedded Linux MIPI CSI-2 Camera Integration V4L2 driver development for MIPI CSI-2 sensors demands accurate device tree configuration, sensor subdevice registration, and media controller pipeline setup before a single frame reaches the application. Vadzo Imaging's Bolt MIPI CSI-2 camera series - the BOLT 234CGS AR0234 Color Global Shutter MIPI Camera, BOLT 544CRS AR0544 HyperLux Color MIPI Camera, BOLT 900MGS IMX900 Monochrome Global Shutter MIPI Camera, and BOLT 1335CRS AR1335 Fixed Focus 4K MIPI Camera gives embedded engineers pre-validated hardware with Linux kernel driver support confirmed on Raspberry Pi, NVIDIA Jetson, and NXP i.MX platforms. FORT WORTH, Texas, May 25, 2026 (Newswire.com) - Vadzo Imaging, a provider of embedded vision cameras for OEMs and system integrators, today publishes a technical guide addressing V4L2 driver development for embedded Linux MIPI CSI-2 camera integration. The guide covers the full MIPI CSI-2 camera driver stack from kernel driver structure and device tree configuration through sensor subdevice registration in the Linux camera subsystem and the V4L2 MIPI camera integration sequence required across Raspberry Pi V4L2 driver, NVIDIA Jetson camera integration, and NXP i.MX camera integration platforms. Vadzo's Bolt MIPI CSI-2 camera series supports this workflow directly: every camera in the Bolt series ships with module-level Linux kernel driver packages verified on the platforms covered, giving embedded engineers a confirmed starting point for V4L2 driver development. V4L2 Driver Development for MIPI CSI-2 Cameras Requires More Than a Generic Kernel Driver MIPI CSI-2 camera integration in embedded Linux operates across three layers that must all be correct before the V4L2 camera driver delivers frames to the application: the sensor subdevice driver handling register initialization and mode switching through the V4L2 subdev API, the device tree configuration describing MIPI lane count, polarity, and link frequency for both the sensor node and
May 25, 2026 · via newswire.com
BuzzFeed GamesIf You Can Solve This Color Puzzle In Less Than 3 Minutes, You Have Perfect Color VisionHuedoku #29! New week, new puzzle, same zero mercy. 🎨💀Posted 6 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! Come back tomorrow for Huedoku #30 — and share your score to challenge a friend! 🌈 🌈 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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May 25, 2026 · via buzzfeed.com
AI slop is a real and present danger. As a writer and editor, I don't see myself using AI detection tools at every turn of the syllable. Instead, I am trying to train my eye to spot AI-generated content. It's still easy to spot deepfakes, but the written word is getting tougher to nail down. Wikipedia offers some help. Its volunteer editors, the army who obsessively fight for knowledge, have quietly built the most evidence-based AI guide on the internet. Wikipedia's Signs of AI Writing page isn't an app or a checklist. It's just a simple page, meant primarily for Wikipedia's own articles written in wikitext. But even outside the encyclopedia, it might help you eyeball the next piece of AI writing you come across. This AI App Will Help You Prove You Didn’t Use AI to Write Your Paper This app will help prove that you didn't cheat. Wikipedia built a handy AI detection field guide No app needed — just pattern recognition Wikipedia's Signs of AI Writing page started as an internal resource for volunteer editors. Since 2023, a group called WikiProject AI Cleanup has been reviewing new submissions for undisclosed AI-generated content. After combing through thousands of flagged articles, they cataloged the patterns they kept seeing in Wikipedia drafts and edits. The result is what Wikipedia says, that it's what the editors have observed, and it's more "signs" than "rules." The page is worth a bookmark and a deep read. Instead of depending on AI writing detectors, it will help you spot-check writing behaviors. Those are the telltale giveaways of AI writing. As we all know, LLMs are just machines, and they are built on statistical probability, not on real storytelling skills. When I first came across the page, I expected a basic checklist. What I found
May 25, 2026 · via makeuseof.com
IRS proposal could turn taxpayer facial verification into long-term fraud database The Internal Revenue Service (IRS) is considering a proposal that would authorize ID.me to retain taxpayers’ biometric data for years, a change that would deepen the role of facial recognition in federal tax administration and revive privacy concerns that forced the IRS to retreat from a similar controversy four years ago. Under the proposal, biometric scans collected during identity verification for IRS.gov accounts could be kept by ID.me for as long as an account remains active and then for up to 36 months after the account is deleted. The retained data could be accessed by government officials only as part of law enforcement or IRS inspector general investigations and through legal process. The proposal reflects a growing concern inside the federal government that identity fraud is becoming harder to detect as criminals use stolen personal information, synthetic, and AI-generated images to impersonate taxpayers. The proposed action has raised questions about how much biometric information Americans should be expected to give a private contractor to access government services online. ID.me says biometric retention depends on the customer agency and that some customers require biometric information to be purged within 24 hours after a successful verification, while others require longer retention. The company says it will not retain biometric information for more than 36 months unless there is a subpoena, warrant, or other legally compelling justification. The new IRS proposal would move the agency toward the longer end of that retention model. ID.me’s public privacy policy, updated May 7, says personal information provided in connection with a public sector agency verification may be retained for up to three years after account closure unless regulations require a shorter period. The policy also says ID.me may retain data tied to high-risk transactions, particularly
May 25, 2026 · via biometricupdate.com
Met police to share more bodycam footage online The Metropolitan Police says it is changing its policy on releasing more body-worn video from officers "where it can improve transparency and trust in policing". The force said the move would "back our own officers and help people understand the very challenging role they perform". Until now, body-worn video has only typically been published after the conclusion of any criminal proceedings, meaning the public was only seeing a "partial picture" from footage shared online by others. Civil liberties groups have long-standing concerns police can misuse body-worn cameras by switching them off during incidents or failing to disclose footage, raising questions regarding accountability. The Met said it released footage of the arrest of the suspect in the Golders Green knife attacks in April "in response to a narrative growing online which criticised the force used by officers, who were bravely apprehending an armed man". It added: "It was put into use again following the significant public order policing operation last Saturday, where we were able to provide an insight into the abuse officers faced from protesters and the challenges involved in intervening in dense crowds to make arrests." London's police force began an initial pilot of 500 body-worn cameras in May 2014, with a mass rollout to thousands of officers in October 2016. Human rights advocacy group Liberty has warned that UK police forces already use earlier versions of facial recognition technology, which combine footage recorded on body-worn cameras with software to provide retrospective facial recognition searches. A BBC investigation in 2023 also uncovered more than 150 reports of camera misuse by forces in England and Wales. In one case, siblings faced a two-year legal battle over footage showing officers' use of force against them during a Black Lives Matter rally in London.
May 25, 2026 · via bbc.com
Liveness detection tender from Australian Tax Office updated with new info The Australia Taxation Office has updated its Request for Information (RFI) on a potential biometric liveness detection tool to support onboarding and identity verification for the myID App, which powers the country’s national digital ID. The update from the ATO, which manages myID within the Australian Governments Digital ID System (AGDIS), answers a host of questions regarding the tender, which closes this week, on May 28. The RFI seeks suppliers with identity verification expertise, particularly related to liveness detection and facial image capture, biometric matching and credential validation, as the ATO seeks to replace a contract signed with iProov in 2021. Regarding specific certification and the requirement for solutions to be tested by “a qualified third-party biometric testing entity experienced in ISO/IEC 30107,” the document says “the solution must have completed PAD testing using any ISO accredited biometric testing laboratory.” Individual labs are not favored. “Respondents should provide evidence of the testing body’s qualifications, accreditation scope, test methodology, version of the standard used, PAD assurance level assessed, and any limitations or exclusions in the test report.” The product must come as a SaaS solution, and support peak workloads of 10,000 verifications per hour with 95th percentile responses within one second. But, ATO says, the peak load requirement “should be treated as a combination of projected and observed load,” as applied to enrolments, reverifications and account recovery events. The ATO can’t rightly say what kind of numbers they’re looking at in the long term. “Forecasted growth of IP3 verifications” – the next security level ATO is pursuing – “and re-verification events cannot be provided at this stage. Respondents should provide a Software Capacity Plan and strategies for scaling that references peak load,” documenting assumptions, scalable architecture, and capacity headroom, while
May 25, 2026 · via biometricupdate.com
The National Transportation Safety Board (NTSB) has temporarily taken its public docket system offline after learning that publicly released accident materials may allow people to reconstruct approximations of cockpit voice recorder audio. The agency said advances in “image recognition and computational methods” have allowed individuals to recreate approximations of CVR audio from sound spectrum imagery released as part of NTSB investigations. The issue includes material released in the ongoing investigation into the crash of UPS Flight 2976 in Louisville, Kentucky, in November 2025. “The NTSB does not release cockpit audio recordings,” the agency said in a statement posted to its docket status page. “Federal law prohibits such public release due to the highly sensitive nature of verbal communications inside the cockpit. The NTSB takes these privacy restrictions seriously.” The NTSB said its docket system will remain temporarily unavailable while it examines the scope of the issue and evaluates possible solutions. The agency said it hopes to restore access “as soon as possible.” The issue does not appear to involve written cockpit voice recorder transcripts alone. A transcript provides the words, timing and some sound descriptions from a cockpit recording, but it does not contain the cockpit audio itself. The concern cited by the NTSB centers on sound spectrum imagery released in public investigation materials. Sound spectrum imagery is a visual representation of audio data. Investigators use it to help identify sounds and establish precise timing for events captured on a recording. Because that imagery is derived from the underlying CVR audio, modern image-recognition and AI computational tools may be able to use it to reconstruct an approximation of the protected cockpit audio. That creates a problem for the NTSB because federal law prohibits the public release of cockpit voice recordings, even though the agency may release written transcripts and factual
May 25, 2026 · via aerotime.aero
It's almost impossible to ignore AI. That doesn't mean it's always easy to understand. From agentic AI to UBI, tech CEOs, Wall Street, and politicians increasingly sound like they are speaking another language. The terms seem to change almost as quickly as AI models themselves advance. Even if you don't use AI, chances are your bank, your doctor, the streaming service you're using, and maybe even your car do. Here's a list of the people, companies, and terms you need to know to talk about AI, in alphabetical order. The AI terms you need to know Agentic: A type of artificial intelligence that can make proactive, autonomous decisions with limited human input and is capable of operating autonomously around the clock. Popularized by services like OpenClaw, the proliferation of these tools is viewed as the biggest moment in generative AI since the release of ChatGPT. AGI: "Artificial general intelligence," or the ability of artificial intelligence to perform complex cognitive tasks such as displaying self-awareness and critical thinking, the way humans do. Crossing this theoretical threshold is the mission of many in the industry. Alignment: A field of AI safety research that aims to ensure that the goals, decisions, and behaviors of AI systems are consistent with human values and intentions. Bias: Because AI models are trained on data created by humans, they can also adopt the same fallible human biases present in that data. There are a number of different types of bias that AI models can succumb to, including prejudice bias, measurement bias, cognitive bias, and exclusion bias — all of which can distort the results. Capability overhang: The term, credited to Microsoft Chief Technology Officer Kevin Scott, for the gap between what AI models are capable of and what real-world applications can currently utilize. ChatGPT: OpenAI's signature chatbot
May 25, 2026 · via businessinsider.com
Plantalk Unveils Plantiemoji, the AI-Powered Emotional Plant Interface, Now Live on Kickstarter The World's First Plant Fitness Tracker Combines Real-Time Emoji Status, AI Diagnostics, and 4-in-1 Sensing to Give Plants a Voice HOUSTON, TX / ACCESS Newswire / May 25, 2026 / Plantalk today announced the launch of Plantiemoji, an AI-powered plant care device that gives your plant a 'voice' through expressive emojis. Debuting today on Kickstarter, the device aims to transform plant care from a guessing game into an interactive conversation. Plantiemoji is an AI-driven emotional interface that turns complex environmental data into intuitive visual feedback. By translating metrics like soil moisture, light, temperature, and humidity into emojis displayed on a detachable screen, it makes plant care simple, intuitive, and engaging. For those interested in securing the upcoming Kickstarter launch offer, a limited early reservation option is now available ahead of launch: https://www.kickstarter.com/projects/plantalk/plantiemoji-your-plants-first-fitness-tracker Redefining Human-Plant Interaction: From Data to Emotion In a world of ubiquitous smart devices, plant care remains stubbornly reliant on guesswork. For many, knowing exactly when a plant needs water, more light, or a change of environment is a constant challenge. Plantiemoji solves this by transforming complex environmental data into expressive, emoji-like visual cues. These real-time signals allow users to instantly understand their plant's condition and know precisely when to step in. By introducing emotional feedback, Plantiemoji reimagines plant care as an interactive dialogue-where plants are no longer silent decor, but expressive companions. An AI-Driven Plant Care System Plantiemoji integrates environmental sensing with artificial intelligence to deliver a comprehensive plant care solution. Inserted into the soil, the device continuously monitors key parameters including temperature, humidity, light, and soil moisture. Through a connected mobile app, users can identify plant species using image recognition. Once the plant is identified, the system builds a specific profile and activates its
May 25, 2026 · via bignewsnetwork.com
Worse than a facial recognition system? - Researchers have demonstrated that routers can identify individuals using wireless signals. - A person can be identified even without a device or with their phone turned off. - A router could become a covert monitoring tool, making this surveillance method both invisible and difficult to detect. - Such a method raises urgent questions about privacy regulations similar to those now being debated around facial recognition. Using wireless signals and artificial intelligence could turn a router into a monitoring system, researchers at the Karlsruhe Institute of Technology (KIT) have found. The study also revealed that a person can still be identified even if their smartphone is shut down or they don’t carry it with them at all. It’s enough that they’re surrounded by other people whose devices are communicating with each other. “By observing the propagation of radio waves, we can create an image of the surroundings and of persons who are present,” explained Professor Thorsten Strufe from KIT’s Institute of Information Security and Dependability. The expert compared it to a camera, but the difference is that “radio waves instead of light waves are used for the recognition.” The research reveals that it’s possible to turn any router into a surveillance device, raising serious privacy concerns. “If you regularly pass by a café that operates a WiFi network, you could be identified there without noticing it and be recognized later, for example, by public authorities or companies,” shared Julian Todt, a PhD researcher at KIT. How does surveillance through WiFi work? While there are different types of surveillance technologies available for quick identification, what makes wireless network surveillance stand out is that it’s almost everywhere and doesn’t raise suspicion because you can’t really see it. This surveillance method also doesn’t require any extra hardware,
May 25, 2026 · via cybernews.com
MNPD launching drone first responder trial program in Madison Metro Nashville Police are preparing to launch a new Drone as First Responder trial program in Madison aimed at helping officers respond to emergencies faster. The limited trial program begins Tuesday, May 26, and will operate out of the Madison Precinct. Three drones stationed on the roof of the precinct will be able to respond within a two-mile radius to emergency calls, active criminal investigations, missing person cases, and major traffic crashes. Police say the drones can often arrive at scenes within one to two minutes, giving officers critical real-time information before they arrive. “The major benefit is the time it takes to arrive on scene, it's like a minute to 2 minutes, they don't have to deal with traffic they can get to a scene and give you all the information that you need quickly,” Chief John Drake said. The drones will be operated remotely by four FAA-certified officers from the department’s Community Safety Center who received specialized drone training. MNPD says departments across the country — including Las Vegas, Oklahoma City, and Charlotte — already use similar programs. MNPD emphasizes program is NOT surveillance Police say the drones are not intended for random neighborhood patrols or general surveillance. Officials stressed the drones will only be used in response to specific calls for service where aerial views could improve safety and decision-making during emergencies. MNPD also says: - The drones do not use facial recognition software - The drones cannot be weaponized under state law and department policy - Flights will be publicly logged online - Non-evidence video footage will be permanently deleted after seven days Police say access to drone footage will be limited to trained personnel and investigators handling cases connected to the footage. The trial program is
May 25, 2026 · via fox17.com
Capitalizing on a 37.8% CAGR : Why the Deep Learning Market is a USD 406 Billion Megatrend by 2032 WILMINGTON, NEW CASTLE, DE, UNITED STATES, May 25, 2026 /EINPresswire.com/ -- According to a new report published by Allied Market Research, titled, âDeep Learning Market Size, Share, Competitive Landscape and Trend Analysis Report, by Component (Hardware, Software, Service), by Application (Image recognition, Signal recognition, Data mining, Others), by Industry Vertical (Security, Marketing, Automotive, Retail and E-Commerce, Healthcare, Manufacturing, Law, Others): Global Opportunity Analysis and Industry Forecast, 2022 - 2032." Market Size : The global deep learning market size was valued at USD 16.9 billion in 2022, and is projected to reach USD 406 billion by 2032, growing at a CAGR of 37.8% from 2023 to 2032. Download Sample Report (Get Full Insights in PDF - 350 Pages) at: https://www.alliedmarketresearch.com/request-sample/5815 Deep learning is a technology that directs computers to process data according to the human perspective. The models of deep learning can analyze complex patterns, texts, sounds, and other data to produce accurate insights and predictions. In addition, it is a subset of machine learning and artificial intelligence, that focuses on modeling and stimulating the behavior of human brain neural networks. In deep learning, large datasets are used to train artificial neural networks to carry out tasks without explicit programming. Furthermore, the technology is used in computer vision, speech recognition, natural language processing (NLP), and others. Moreover, various trends are associated with deep learning technology such as transfer learning (pre-trained models), generative adversarial networks (GANs), self-supervised learning and others. Using pre-trained models that have been optimized for tasks performed on the base of huge datasets is called transfer learning. With a smaller dataset, this strategy enhances performance while accelerating training. In addition, the self-supervised model of deep learning helps in generating own
May 25, 2026 · via einpresswire.com
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May 25, 2026 · via telecompaper.com
Breaking News Metropolitan Police is accelerating the use of live facial recognition technology across London, arguing the system has become a “groundbreaking” policing tool, even as civil liberties groups warn it risks normalising mass biometric surveillance in public spaces. The debate has intensified following a recent High Court ruling that cleared the way for wider deployment of the technology after a legal challenge brought by campaign group Big Brother Watch failed last month. During a recent deployment in Victoria, central London, police used temporary facial recognition cameras to scan passers-by against a watchlist of roughly 17,000 individuals compiled primarily from custody images. Within a short period, officers stopped multiple individuals after the system generated alerts, including one man later taken into custody. The Metropolitan Police says live facial recognition, or LFR, has helped officers arrest around 2,500 wanted individuals since the start of 2024, including suspects linked to violent and sexual offences. Lindsey Chiswick, who leads the force’s live facial recognition programme, described the technology as transformative for policing in the capital. Speaking during the Victoria operation, she cited cases involving robbery, rape, strangulation and convicted sex offenders identified through the system. The technology works by converting faces captured through live video feeds into biometric templates and comparing them in real time against police watchlists. According to the Met, non-matching facial data is deleted immediately after processing. Police say the system has demonstrated high levels of accuracy. Chiswick said that among more than 3 million faces scanned in the 12 months through last September, the technology generated only 10 false alerts, none of which resulted in arrests. But critics argue the core issue extends beyond technical accuracy to broader questions around civil liberties, privacy, and state surveillance. Campaigners say live facial recognition effectively treats every member of the public as
May 25, 2026 · via varindia.com