Abstract The human brain has long served as a blueprint for computation, guiding evolution from early symbolic systems to modern deep learning models. Despite these advances, traditional computing systems remain fundamentally limited in mirroring the remarkable flexibility, parallel processing and energy efficiency of the human brain. To address these limitations, neuromorphic computing was developed, which mimics the architecture and signaling behavior of biological neurons. Building on this foundation, a new frontier is now emerging—organoid intelligence (OI). OI uses lab-grown brain cellular structures, such as living neural organoids with electrical activity, synapse formation and primitive learning, as a substrate for computation. Here we trace the evolution of brain-inspired computing from symbolic logic systems to artificial neural networks, neuromorphic processors and finally biohybrid computers that incorporate living neural structures. We explore the transformative potential of OI along with the substantial technical, biological and ethical challenges it presents. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Subscribe to this journal Receive 12 digital issues and online access to articles $119.00 per year only $9.92 per issue Buy this article - Purchase on SpringerLink - Instant access to the full article PDF. USD 39.95 Prices may be subject to local taxes which are calculated during checkout Similar content being viewed by others References - Bermudez-Contreras, E., Clark, B. J. & Wilber, A. The neuroscience of spatial navigation and the relationship to artificial intelligence. Front. Comput. Neurosci. 14, 63 (2020). - Kriegeskorte, N. & Douglas, P. K. Cognitive computational neuroscience. Nat. Neurosci. 21, 1148–1160 (2018). - Hassabis, D., Kumaran, D., Summerfield, C. & Botvinick, M. Neuroscience-inspired artificial intelligence. Neuron 95, 245–258 (2017). - Brette, R. Brains as computers: metaphor,
Jul 3, 2026 · via nature.com
Smart education opens new possibilities for every student in Yinchuan A demonstration event is held in Yinchuan, northwest China's Ningxia Hui autonomous region to showcase achievements in AI-assisted teaching for primary schools, June 11. (Photo courtesy of the education bureau of Xixia district, Yinchuan) In Yinchuan, capital of northwest China's Ningxia Hui autonomous region, a group of seventh graders from Ningxia No. 15 Middle School have developed a smart bird-repelling system to protect goji berry fields. The system automatically detects birds approaching the fields and plays pre-recorded raptor calls to deter them. Powered by AI image recognition, it protects crops without harming wildlife. This is an example of the school's efforts to build a distinctive curriculum that integrates general education with AI. "Several companies have already contacted us about turning the students' idea into a real product," said Xie Wei, principal of the school. He summarized the school's goals in simple terms: "We want to lighten teachers' workloads and give our students more room to grow." The transformation brought by smart education can be felt throughout the campus. For Chinese teacher Bao Ling, lesson preparation used to be a time-consuming process. "I used to spend several evenings preparing audio and video materials for a single class," she recalled. Now, she routinely uses AI tools to turn textbook content into animated lessons. While teaching the essay Pear Blossoms Along the Post Road, she transformed the text into an immersive visual experience, with pear blossoms blooming across the screen and the story unfolding in vivid detail. "A single video can help students grasp the entire text," Bao said. "Students are more engaged and spend more time looking up and participating, while lesson preparation has become much more efficient." AI has also made literature feel more personal. Through AI-generated characters, students can "talk"
Jul 3, 2026 · via en.people.cn
The Vision AI Label Reader from collective mind GmbH (COMI) demonstrates how this complexity can be managed. The AI-based image processing system automates the capture and interpretation of item information in goods-in and logistics – regardless of layout, language or code type. Designed for industrial use, the solution improves process reliability, enhances data quality and streamlines workflows. A uEye CP industrial camera from IDS Imaging Development Systems GmbH provides the image data required for analysis. Fully automated capture instead of manual inspection The Vision AI Label Reader is designed for applications where a wide variety of items, labels and packaging are processed on a daily basis. This makes it particularly suitable for electronics manufacturing service providers as well as companies with complex logistics processes and extensive inventories. One concrete example is Rutronik Elektronische Bauelemente GmbH, a globally leading broad-line distributor of electronic components, where the system is already in successful operation. The goal is to automatically capture all relevant item information and make it available in a structured format. To achieve this, the system recognises all labels on an object, reads printed text as well as 1D and 2D codes, and then interprets the content using artificial intelligence. Handwritten entries can also be processed if required. Crucially, recognition does not rely on predefined label standards. New layouts, languages or code formats can be handled without retraining – a key factor for scalability and long-term viability. Camera and AI working together A central component of the solution is the industrial camera from the uEye CP family by IDS. It captures labels and packaging surfaces at high resolution and supplies the image data for AI analysis, reliably detecting fine details even under challenging conditions. In practice, reflective packaging such as dry packs, damaged codes or fluctuating lighting conditions place high demands on
Jul 3, 2026 · via ien.eu
On Wednesday, SwitchBot released its latest outdoor security camera. The smart home company bumped the resolution to 3K and now offers AI video descriptions, a feature that most security companies have added in the past year. SwitchBot's new outdoor pan/tilt camera, starting at $80, includes motion tracking and object recognition and offers you the choice between wired and wireless connections. It can also hold up to 512GB of local video clips or offer cloud storage as an option in its subscription plans. The real standout is the AI recognition technology, which allows the camera to describe the events it captures. "A man in a UPS uniform walks on a porch with a package," for example. The camera can also provide daily summaries of everything it's seen, saving you even more time. I've seen these features move into cameras from major brands including Ring, Nest, Blink and Arlo over the past year. They usually come with a hefty subscription fee around $20, but SwitchBot's is lower than usual, starting at $5 per month. The only AI identification features you can get for even less come from Eufy, which is planning to offer onboard AI descriptions for free sometime later this year. A representative from SwitchBot didn't immediately respond to a request for comment. SwitchBot has one trick, though, that really sets its camera apart from the pack: Its recognition features are specifically trained to identify wildlife, down to the species level. While most AI cams can tell the difference between dogs, cats and deer, this SwitchBot camera's abilities go a little deeper. That's useful if you want to get notifications like, "A coyote enters your yard," alerting you that it may not be safe for your outdoor cats or other pets. And its spotting the difference between a possum and a
Jul 3, 2026 · via cnet.com
Meta's Ray-Ban smart glasses are facing renewed scrutiny after a WIRED investigation revealed that the Meta AI companion app contains code for an unreleased facial recognition feature capable of identifying people captured through the device's camera. Researchers examining recent versions of the app uncovered references to an internal system known as "NameTag," which appears designed to recognise faces, convert them into biometric data, and alert users when familiar individuals are detected. The findings suggest Meta has been developing the technology for several months, raising fresh questions about privacy, biometric data collection, and the future of AI-powered wearables. How nametag works According to WIRED's analysis, the feature relies on three AI models. One detects a face in an image, another aligns and processes the image, while a third converts facial characteristics into biometric data that can be used for identification. Researchers also found evidence suggesting recognised facial data may be stored locally on user devices after facial "prints" are retrieved from Meta's servers. Although the feature is not currently available to consumers, its presence within the app indicates Meta has been actively exploring facial recognition capabilities for its smart glasses ecosystem. The discovery has reignited concerns about facial recognition in wearable devices. Unlike smartphones, smart glasses can capture images and video in a more discreet manner, raising questions about consent, surveillance, and the collection of biometric information in public spaces. Privacy advocates argue that real-time identification could make facial recognition more pervasive in everyday life, particularly if individuals are identified without their knowledge. The findings are likely to attract attention from regulators already examining how technology companies collect, store, and process sensitive biometric data. Meta says the feature remains under development and has not been released. "Nothing has shipped to consumers, and no final decision has been made on what to
Jul 3, 2026 · via eastleighvoice.co.ke
Abstract Bound states in the continuum (BIC) leverage symmetry-protected resonant modes for exceptional light confinement, yet their leaky modes are almost underutilized. Meanwhile, multiple quantum well (MQW) structures face limited optical absorption due to strict transition selection rules. We demonstrate the regulation of the leaky mode of quasi-BIC (QBIC) by analyzing MQW-vertical field coupling, revealing that increasing asymmetric parameters enhances the transverse leakage of wave vector and optical field nonlinearly. This drives a nonlinear photoresponse as increasing asymmetry parameter, while linear scenario with incident angle and external bias voltage. We then develop an optoelectrical fusion neuromorphic processor, implementing QBIC-MQWs into an artificial neural network for machine vision applications. Similar content being viewed by others Introduction Metasurfaces enable subwavelength-pixelated light manipulation of amplitude, phase, polarization, and propagation, emerging as a transformative platform for tailoring light-matter interactions. This capability facilitates in-situ electromagnetic wave engineering in integrated optoelectronic systems, unlocking monolithic designs for advanced photonic processors1,2,3,4. Bound states in the continuum (BIC) that exploit nonradiating modes to achieve theoretically infinite quality factors (Q) and their quasi-BIC (QBIC) counterparts that emerge via symmetry-broken perturbations to enable high-Q leaky resonances, accompanied with unprecedented light confinement in subwavelength volumes, have received significant attention in nanoscale lasing5,6,7,8,9,10,11, biomolecular sensing12,13,14, optical imaging15, and other meta-devices16,17,18,19,20,21,22,23,24,25,26,27,28. These works primarily focus on the resonance modes arising from electromagnetic interference within periodic meta-atom arrays. The exploration and application of the symmetry-broken leaky modes generated by engineered radiation channels of QBIC remain relatively limited. According to Bloch theorem, electromagnetic modes can be represented by a wave vector k|| = (kx, ky) that is parallel to the xy plane. For symmetry-protected BICs, the radiation direction is purely normal to the xy plane, yielding k||≈0. Nevertheless, once the symmetry is broken, a structural perturbation that breaks the symmetry can transform a BIC into a
Jul 3, 2026 · via nature.com
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Jul 3, 2026 · via youtube.com
A press conference being used by police to spruik new crime-busting cameras has been interrupted when the technology detected several wanted people. A woman who allegedly failed to appear in court was among three people picked up by the real-time facial recognition cameras at the Mirrabooka bus station in Perth’s north on Thursday afternoon, forcing officers into action. WATCH THE VIDEO ABOVE: Arrests made as new cameras spark police into action Know the news with the 7NEWS app: Download today “Been happening all week,” WA Police Commissioner Col Blanch said. “I’d love to say I planned that, but I think that’s exactly what the technology is. “People are being arrested because they are wanted.” More than 130,000 faces were scanned during the opening week of the Australia-first trial, starting June 22, and 18 arrests were made. Sixteen of those arrests related to outstanding warrants, and two were for breaching exclusion orders in entertainment precincts. “If we’ve got 4000 people in our community with arrest warrants, no one should be happy with that,” Blanch said. “If this can solve most of those problems, I think it’s a great deal.” The cameras also helped police speak to two people for welfare checks. The cameras are mounted on or near a marked WA Police van, and scan crowds to instantly detect faces and compare them against targets or people banned from certain areas. If the technology sounds the alarm, a human makes the final assessment on whether there is an actual match. The commissioner said “we have a human in the loop” to double-check false starts. Images of community members not on the alert list are automatically pixelated and deleted. “Speaking to the team who have been setting this up for the last week, the overwhelming positive feedback from our community has been
Jul 2, 2026 · via 7news.com.au
PHOENIX — Javier Lorenzano Nunez, who spent nearly a year in jail after being arrested for a 1998 Phoenix murder, has filed a federal lawsuit against the Phoenix Police Department and the Maricopa County Attorney's Office. The lawsuit alleges he was "arrested without probable cause" and that police and prosecutors "committed gross negligence, false arrest, false imprisonment, negligent infliction of emotional distress, and defamation." Phoenix police and the Maricopa County Attorney's Office declined to comment on the lawsuit. Lorenzano Nunez was arrested in 2024 after investigators used facial recognition technology to connect him to the decades-old killing of 28-year-old Sarah Carr. All charges were quietly dismissed less than a year later after forensic evidence, including DNA and fingerprints, excluded him, records show. Carr was shot and killed on July 9, 1998, just before midnight at a house near 14th Street and McDowell Road following an argument. Witnesses identified a suspect named Gilbert Noel Sanchez Rosado, who fled and was never found. Two decades later, investigators ran Rosado's old Arizona MVD photo through facial recognition databases operated by the Arizona Department of Public Safety and the FBI. They received 250 possible matches and zeroed in on Lorenzano Nunez. Phoenix police made a big deal about the arrest, putting out a press release and producing a special video featuring the victim's son, Garrett Miller, who had become a police officer in Texas. Miller was flown in for the arrest, and Phoenix police used his handcuffs during the bust. He was also interviewed for the city's special video on the case. Facial recognition appears to be the key evidence used to arrest Lorenzano Nunez, according to the lawsuit and court records obtained by ABC15. "I represent an individual who never should have been arrested," said Danny Ortega, a civil rights attorney representing Lorenzano
Jul 2, 2026 · via abc15.com
What is neuro-symbolic AI? This powerful form of AI mixes awareness of sequences with logic Neuro-symbolic AI combines the pattern recognition capabilities of deep learning neural networks with the logical reasoning of symbolic AI. The result is a smarter system of artificial intelligence that can draw insights from data while applying rules, facts and reasoning to reach reliable decisions. As organizations search for AI systems that are more transparent, explainable and capable of complex decision-making, neuro-symbolic AI is emerging as one of the field’s most promising developments. Its impressive abilities could dramatically influence how businesses, researchers and governments use artificial intelligence in the years ahead. Ohad Elhelo, co-founder and CEO of AUI, spoke about the current state and future of neuro-symbolic AI during the University of Cincinnati’s Future of Commerce: AI+Robotics Summit 2026. The signature event, hosted at the UC 1819 Innovation Hub and Digital Futures complex, brought together national leaders on automation-related topics. Elhelo, a leading expert on neuro-symbolic AI, explained how this form of AI works, its top use cases and where the emerging technology is headed. How does neuro-symbolic AI work? Neuro-symbolic AI works by learning from data and applying logic to it to reach conclusions. The name “neuro-symbolic” refers to the two unique AI approaches the model combines: deep learning neural networks and symbolic AI. Put simply, “neuro” learns as it goes while “symbolic” deduces from what it knows. Deep learning neural networks are AI systems trained on massive amounts of data that identify relationships across it. These systems improve their performance by recognizing trends in large datasets rather than relying on predefined rules. Large language models (LLMs) such as ChatGPT, Claude and Google Gemini mainly run on pattern recognition through a neural system. “Neural approaches – deep learning – has driven all the great breakthroughs
Jul 2, 2026 · via uc.edu
HYBE has published its 2025 Sustainability Management Report, covering the K-pop giant behind BTS, SEVENTEEN, TOMORROW X TOGETHER, LE SSERAFIM, ENHYPEN, and its various sub-labels. The 121-page document sets out a number of disclosures, including anti-counterfeiting measures, the company’s use of generative AI, and its expansion into physical retail. Here are five things we learned⦠1. HYBE removed 92,208 counterfeit listings from Amazon over four months HYBE runs its response to intellectual property infringement through the IP Strategy Team within its Legal Affairs Department, and it has put figures to the work carried out in 2025. The report states: “When it comes to the infringement of our intellectual properties, we take a diverse approach to addressing such issues through the IP Strategy Team under the Legal Affairs Department. The progress and results are shared with management and relevant departments every month.” HYBE singles out a tie-up with Amazon. According to the report: “We have established a direct collaboration framework with Amazon to respond firmly to global artist IP infringement. Through a combination of AI-driven automated filtering and manual monitoring on the platform, enforcement against counterfeit goods has been intensified. As a result, over the four month period from September to December 2025, a total of 92,208 infringing listings were identified and removed on Amazon.” Across e-commerce more broadly, HYBE says it removed counterfeit product listings totaling 12,959 cases in Korea and 273,512 cases overseas during the year. “When it comes to the infringement of our intellectual properties, we take a diverse approach to addressing such issues through the IP Strategy Team under the Legal Affairs Department.” The company also reports that it confiscated and destroyed 19,356 counterfeit items through crackdowns on suppliers in Seoul’s Namdaemun market and vendors around a j-hope solo concert venue, working with Korean law enforcement. On
Jul 2, 2026 · via musicbusinessworldwide.com
Quick Hits - The CAI found that Metro Inc.’s facial recognition pilot meets the necessity standard of the Act respecting the protection of personal information in the private sector (the Privacy Act). - Although it called facial recognition more intrusive than traditional video surveillance and the biometric data “sensitive,” the CAI held that the biometric bank does not “otherwise” infringe privacy under Article 45 of the Act to establish a legal framework for information technology (LCCJTI). - Necessity turns on a structured test: the objectives must be important, legitimate, and real, and the collection must be proportionate, rationally connected, minimized, and more beneficial than harmful. Notably, the CAI reached that result after a demanding and often critical review of the technology’s privacy risks, concluding that the project’s benefits outweigh the intrusion, subject to a two-year reporting obligation and to its separate, still-contested February 18, 2025, decision on consent. This 2026 decision is the second chapter of the same investigation. In its February 18, 2025, decision, the CAI held that Metro’s facial recognition amounts to identity verification requiring express consent under Article 44 LCCJTI, and prohibited the bank on that basis. That ruling, which we examined in our earlier article on Québec’s restrictive approach to biometric data, remains under appeal before the Court of Québec. The 2026 decision expressly leaves it untouched. The necessity “green light” is therefore conditional: the consent prohibition still stands unless and until it is overturned. Metro proposed a pilot in up to ten grocery and pharmacy stores that would convert surveillance images of suspected repeat offenders into biometric templates, store them in a database, and flag matches in real time. The CAI was openly skeptical: it found the accuracy evidence thin, flagged real risks of false positives and demographic bias, and warned that relying on a
Jul 2, 2026 · via ogletree.com
Police will be using Live Facial Recognition vans in Clacton this weekend to help identify people suspected of serious offences.
The technology will be deployed on Saturday, July 4, and will be used to locate people suspected of offences including drug-related crime, violence, sexual offences, and theft.
Police have made more than 170 arrests using live facial recognition technology to date, including in cases involving violent and sexual offences.
Officers say the cameras can identify individuals even if their faces are partially covered by masks or other coverings.
Members of the public who are not on the police watchlist will have their images discarded in a fraction of a second.
Essex Police said people are welcome to speak to officers in the town to learn more about how the technology works.
Jul 2, 2026 · via essexcountystandard.co.uk
Why We Need a 'Truth Campaign' for the AI Era Gaurav Laroia, Charlotte Slaiman / Jul 2, 2026Gaurav Laroia and Charlotte Slaiman both previously served at the Federal Trade Commission. They recently published a memo, “Settlement Wins Against Big Tech Should Underwrite Digital Resilience Funds,” at the Federation of American Scientists. As former attorney-advisors to Federal Trade Commission leadership, we worked hard to turn the page on the era when Big Tech could write off fines for alleged lawbreaking as just the “cost of doing business.” We fought to impose real, substantive limits on corporate data collection and to change the extractive business models fueling digital platforms. But our time in the trenches also taught us a hard truth: while strong injunctive relief and market reforms are vital, enforcement alone isn’t enough. To truly protect the public, legal and regulatory action should be paired with a massive, proactive public education campaign. Today, as the honeymoon phase for generative AI ends and state attorneys general launch mounting lawsuits against chatbot developers, we have the momentary opportunity to do just that: fund a “Truth Campaign” for the AI era. The scale of these compounding digital harms resembles an environmental disaster rather than a series of unconnected consumer injuries. Pew polling shows that half of Americans are more concerned than excited about AI, and most doubt their ability to tell whether words or images came from a machine. Gen Z seems to be increasingly anxious about this technology’s impact on their lives. A recent Gallup poll shows their levels of optimism plummeting about how helpful the technology can be in education and especially as deployed in the workforce. During the social media era, tech companies used algorithmic feeds to hijack our attention and our outrage. Generative AI, with its ability to mimic human
Jul 2, 2026 · via techpolicy.press
Greenville getting Flock cameras to help track crime GREENVILLE, N.C. (WITN) - Big brother may be watching you even closer as Greenville will soon deploy Flock cameras around the city. Police say 10 cameras will be put at strategic locations to help solve crimes, locate missing people, and enhance public safety. The city already has a network of cameras that police use to help with their crime-solving efforts. Flock cameras are maintained by a private company that records license plates and vehicle locations, which are made available to law enforcement. WITN asked about 15 people in downtown Greenville if they were in favor of police adding the 10 new cameras. Nine of them, including Greenville resident Karen Mills, do not want them. “You know, you want to catch the bad guys, but at the same time, privacy is becoming a privilege instead of a right,” said Mills. However, six of the fifteen support the new Flock cameras. “I would think the pros definitely outweigh the cons since everything is computerized nowadays,” said Rhonda McIntosh, who was visiting family in Greenville Thursday. “We carry a phone that tracks us,” she explained. In April, Pitt County Schools okayed the installation of two Flock cameras on two of their campuses, Wellcome Middle School and Chicod School, after a request from the Pitt County Sheriff’s Office. While the cameras have drawn criticism from some over privacy concerns, Greenville police say the technology has already helped solve crimes in the region. We asked Police Chief Richard Tyndall if he believes the cameras are at least tiptoeing the line of too much surveillance. “No, I don’t think so,” Tyndall said. “As an example, we have access to over 1,000 cameras in the city right now. We, as a department, have used this technology in the past.
Jul 2, 2026 · via witn.com
Medical Care Technologies Inc. (OTC Pink:MDCE) Advances Beyond Original AI Vision Patent - Technology Has Evolved Faster Than Expected Rapid Internal Innovation Renders U.S. Provisional Patent Application No. 63/854,935 Obsolete, Highlighting Exceptional Velocity in AI Development MESA, Ariz., July 2, 2026 (Newswire.com) - Medical Care Technologies Inc. (OTC PINK:MDCE) today announced that it has elected not to proceed with its U.S. Provisional Patent Application No. 63/854,935, originally filed in July 2025 for its AI Vision Technology. This decision reflects the Company's accelerated pace of innovation, as its current proprietary AI vision systems and software have advanced significantly beyond the original application. Since filing the provisional patent in July 2025, MDCE's engineering teams have achieved substantial breakthroughs in computer vision algorithms, real-time image processing, model efficiency, and practical deployment across multiple platforms. These advancements have made the 2025 provisional application outdated, as the Company's live and beta technologies now deliver superior performance and capabilities. "Our AI vision technology and software development has progressed at a speed that surpassed even our own expectations," said Marshall Perkins, CEO of Medical Care Technologies. "Instead of pursuing an application that no longer reflects our current state-of-the-art systems, we are fully focused on deploying and protecting our next-generation solutions that are already powering real-world products and delivering strong results. This demonstrates our agility and commitment to staying far ahead of the curve." Key current implementations of MDCE's evolved AI Vision technology include: - Vision API Services now available through the corporate website for enterprise clients - MDCE Melanoma Scan Beta platform, showing promising internal testing results - Advanced image recognition features integrated into Snapshot Recipes and RealGameUsed.com authentication workflows This strategic decision underscores MDCE's dynamic development culture and focus on rapid commercialization of cutting-edge solutions rather than legacy filings. The Company continues to evaluate new intellectual
Jul 2, 2026 · via newswire.com
Dublin, July 02, 2026 (GLOBE NEWSWIRE) -- The "Maritime AI - Global Strategic Business Report" has been added to ResearchAndMarkets.com's offering. The global market for Maritime AI was estimated at US$5.9 Billion in 2025 and is projected to reach US$64.7 Billion by 2032, growing at a CAGR of 40.8% from 2025 to 2032. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions. What Forces Are Driving Adoption Across The Maritime Ecosystem? The growth in the maritime artificial intelligence market is driven by several factors including sustained fuel efficiency pressure that requires continuous speed and route optimization based on predicted weather resistance and ocean currents, increasing vessel traffic density in major shipping lanes demanding automated collision avoidance and navigational risk scoring, variability in port waiting times requiring predictive arrival scheduling and berth allocation coordination, tightening emission monitoring regulations that necessitate automated fuel consumption and exhaust pattern analysis, expansion of semi-autonomous and remotely supervised vessel operations requiring perception, obstacle detection, and decision support algorithms, aging fleet infrastructure that depends on predictive maintenance for engines, hull stress, and auxiliary machinery reliability, digitization of port terminals generating operational data that must be analyzed for crane scheduling and yard capacity planning, growth of maritime security surveillance for territorial monitoring and illegal activity detection using movement pattern recognition, and rising demand for accurate estimated time of arrival predictions by shippers and logistics partners to synchronize downstream transportation and inventory planning. Report Scope The report analyzes the Maritime AI market, presented in terms of market value (US$). The analysis covers the key segments and geographic regions outlined below: - Segments: Component (Hardware Component, Software Component, Services Component); Technology (Natural Language Processing Technology, Machine Learning Technology, Computer Vision Technology, Robotics & Autonomous Systems Technology); Application (Navigation & Route
Jul 2, 2026 · via globenewswire.com
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Jul 2, 2026 · via youtube.com
Argonne’s Adam Szymanski applies modeling and simulation tools to strengthen the nation and get its resources ready to move Szymanski helps develop modeling and simulation tools used in military logistics, transportation analysis and mission planning Adam Szymanski believes there is something powerful about building a model that captures the complexity of physical systems. “These models make it possible to explore scenarios that would be impractical to test in the real world,” he said. Szymanski leads the modeling and analytics group at the U.S. Department of Energy’s (DOE) Argonne National Laboratory. This group develops advanced modeling and simulation software, including critical tools for military logistics and transportation analysis and electronic warfare models for mission planning. The models developed by his group are used by the U.S. Department of War and Department of Homeland Security, as well as the DOE. “Being able to analyze ‘what if’ questions and help inform better decisions feels a bit like getting a glimpse into the future — and getting to influence it for the better.” — Adam Szymanski, modeling and analytics group lead at Argonne National Laboratory “These tools help policymakers evaluate potential scenarios and make informed decisions,” Szymanski explained. “The result is enhanced national readiness, optimized resource movement and improved responses to conflicts and humanitarian operations.” His role in accomplishing this mission, as he sees it, is to provide his team with two things: technical support and leadership. Turning complex systems into actionable models On the technical side, Szymanski is a core software developer responsible for the design, implementation and integration of large-scale features and capabilities that are central to how the team’s programs function. For example, over the past several years on the Analysis of Mobility Platform program, he led development efforts in enhancing sealift modeling capabilities to allow for modeling of Joint Logistics
Jul 2, 2026 · via anl.gov
Officials from the Riley County Police Department appeared at Tuesday’s city commission meeting to address common questions about their automated license plate readers, but were met with security concerns from commissioners and the public. These plate readers (ALPRs) are high-speed, computer-controlled camera systems mounted on squad cars, poles or overpasses, and include Flock cameras. RCPD credits the use of ALPRs for more than 150 “positive outcomes” in recent cases. RCPD deputy director Erin Freidline said the system takes still images of license plates on the rear of vehicles. “That door to data is stored for approximately 30 days in our systems,” she said. “You know, this has been a technology that’s been in use for decades. It kind of ebbs and flows on how people want to view it, but it is newer to our community, just in the last couple years.” There are 11 Flock cameras installed in and around the edges of Manhattan. “There is no facial recognition in a license plate reader that is taking a picture of a license plate tag, and there’s no demographic,” Freidline said. “If you were to try and get occupants of the vehicle, if that picture is taken, there isn’t the technology to do demographics across those ALPRs as well.” Sgt. Michael Dunn with the criminal intelligence unit said he is the administrator for most of the ALPR systems. “This analytical software allows us to connect data across cases, identify patterns and provide patrol and detectives with actionable intelligence much earlier in the investigative process,” Dunn said. “These tools are producing real outcomes, for example, faster case resolutions and improved ability to identify and intercept suspects before crimes escalate.” Dunn said Flock automatically creates an audit trail when searches are conducted, and RCPD’s policy requires an audit of all ALPR systems
Jul 1, 2026 · via themercury.com