Waiting seven days or more to get a report of your recent CT scan? Welcome to today’s new normal. Until a couple of years ago, the digital transformation of radiology dramatically shortened turnaround times of report delivery. The last-century process of audio dictation, manual transcription, editing, and signing final reports was replaced by direct voice recognition software. Radiologists became the transcribers and editors. Turnaround of reports from study time shortened to minutes. Why in this day of AI have lag times in report delivery grown into the week levels even at the top academic centers? The answer lies in the first lesson of economics coined by the famed Stanford economist Thomas Sowell, namely, scarcity. “There is never enough of anything to satisfy all those who want it,” he wrote. The unbridled demand for imaging is rapidly outpacing the supply of radiologists. In a Journal of the American College of Radiology paper by Eric Christensen, the projected imaging utilization based on past trends will be approximately 20 percent higher by 2055. I suspect that is a gross underestimate, as continuation of recent per-person utilization trends dramatically broadens this range. The demand for imaging is influenced by a variety of factors. Population growth, particularly those over 65 where utilization of health care triples per capita, is a main one. Another is that imaging can expedite patient throughput for busy emergency room doctors, urgent care centers, and even primary docs who have 15 minutes to figure out patient disposition. Got a rattling cough or belly pain? Why auscultate when you can image. Part of that is the clinician’s fear of missing a serious condition and subsequent litigation exposure. Next, facilities like imaging centers and hospitals are incentivized by volume as reimbursement diminishes. The U.S. imaging services market is poised for significant growth, projected
Aug 14, 2026 · via kevinmd.com
Meta has filed a patent for its AI smartglasses that uses facial recognition to automatically detect who is in the frame, creates a video clip whenever one of those people does something — like picking an item up or walking around — and then generates a highlight reel of what just happened, according to a copy of the patent published Thursday. One example given is the system capturing highlights from a dinner party and then serving those up to the user. The patent gives new, granular insight into what Meta may be planning around its highly controversial push into facial recognition in combination with its AI glasses, which have already been widely lauded as “pervert glasses.” 💡 Do you work at Meta and know anything else about these glasses? I would love to hear from you. Using a non-work device, you can message me securely on Signal at joseph.404 or send me an email at joseph@404media.co. This post is for paid members only Become a paid member for unlimited ad-free access to articles, bonus podcast content, and more. Subscribe Sign up for free access to this post Free members get access to posts like this one along with an email round-up of our week's stories. Subscribe Already have an account? Sign in
Aug 14, 2026 · via 404media.co
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Aug 14, 2026 · via cureus.com
Artificial intelligence is not making the guest list in The Castro — for now. This week, two San Francisco gay bars, Badlands and Toad Hall, walked back their decision to implement an AI-powered facial recognition technology at the door following a vociferous outcry from the LGBTQ+ community. According to the San Francisco Chronicle, the tool in question, Patronscan, was used to “verify IDs and ages and flag problem patrons across all venues.” That said, the nature of the program’s database, which stores patron’s zip code, birth date, gender, ID expiration date, and photograph for 21 days (and longer in some cases), comes with some serious privacy concerns. Pack your bags, we’re going on an adventure Subscribe to our weekly newsletter for the best LGBTQ+ travel guides, stories, and more. As nationwide anti-surveillance groups like Club 1984 pointed out, there’s an especially sensitive nature to LGBTQ+ people’s data in this political climate. Plus, its very implementation goes against the longstanding tradition of LGBTQ+ safe spaces, where queer people could go and not “be photographed, named, and listed.” Currently, the group tracks nearly 40 LGBTQ+ venues in cities like New York and Los Angeles using similar technology, as well as bars and clubs that have vowed not to. Notably, patrons who visit venues using these systems cannot opt out of having their IDs scanned, and can only request “that their information be deleted” via a form on PatronScan’s website, per Metro Weekly. In a statement shared to Instagram on August 8, Badlands and Toad Hall’s management wrote that “effectively immediately,” they would pause use of PatronScan to “review [their] ID verification and security practices.” “The safety of our guests and staff remains a priority, as do privacy and trust,” they added. “We appreciate everyone who has shared their concerns and remain committed
Aug 13, 2026 · via gaycities.com
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Aug 13, 2026 · via youtube.com
Stop Blaming Facial Recognition for Workplace Surveillance Facial recognition has become the villain of choice in the workplace surveillance debate—the first technology critics name when they warn that America's factories and warehouses are turning into surveillance zones. That broader debate has reached Congress: Sens. Ed Markey (D-MA) and Brian Schatz (D-HI) reintroduced the Stop Spying Bosses Act and the No Robot Bosses Act in June 2026 to rein in employer surveillance of workers. States are pushing further: New York's Bossware and Oppressive Technology (BOT Act) would restrict electronic monitoring of employees, while a California bill that died in February would have banned workplace monitoring tools that use facial, gait, or emotion recognition—though its successor is already moving through the legislature. Rather than impose overly restrictive policies that limit facial recognition's utility in the workplace, policymakers should regulate what employers do with workplace data, not which device collects it. Part of the problem is vocabulary. As ITIF has explained, “facial recognition” is often used imprecisely as a catch-all term for a family of distinct technologies. Facial detection merely determines whether an image contains a face. Facial analysis estimates characteristics such as age or drowsiness without determining whose face it is. Facial recognition, by contrast, compares a face against stored templates, either to verify a claimed identity or to determine whether a person matches someone on a predefined list and, if so, retrieve information associated with that match. These uses involve different data and raise different privacy risks. They also rely on different technologies: cameras generally capture facial images, while some systems supplement them with infrared sensors. Other workplace devices collect different kinds of data altogether: a badge reader logs a credential, a handheld scanner logs task times, and a wearable logs motion. The same device can support very different data practices
Aug 13, 2026 · via itif.org
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Aug 13, 2026 · via youtube.com
A three-member bench headed by Chief Justice of India (CJI) Surya Kant tagged the plea with other pending petitions concerning the recent student protests organised by the Cockroach Janta Party. Appearing on behalf of the petitioner, senior advocate Dr Menaka Guruswamy contended that the plea was filed in the context of the Delhi Police using digital tools to surveil protesters at Jantar Mantar. She added the services of two private entities, Aditya Infotech Ltd and Dimension NXG Pvt Ltd, were being used, and that the data was processed and stored in violation of the Digital Personal Data Protection Act, 2023. She further submitted that the data had been collected without permission. "These private entities host the data in violation of the DPDP Act," she argued. The bench agreed to consider the plea. Rahim has approached the top court seeking a declaration that the use of indiscriminate biometric surveillance at peaceful public assemblies is unconstitutional and should be restrained until Parliament enacts a law specifically authorising and regulating such measures. The plea alleged that Delhi Police conducted biometric surveillance in a "complete legal vacuum". It said neither the Delhi Police Standing Orders governing protests nor the Criminal Procedure (Identification) Act, 2022, authorises biometric surveillance of persons participating in civilian assemblies. According to the plea, Delhi Police carried out automated extraction and matching of protesters' biometric identifiers and allegedly linked the data with permanent national criminal databases.
Aug 13, 2026 · via economictimes.indiatimes.com
The results reaffirm the company's leadership in one of the industry's most demanding and operationally relevant biometric evaluations. COURBEVOIE, France, Aug. 13, 2026 /PRNewswire/ -- IDEMIA Public Security, the leading provider of secure and trusted biometric-based solutions, today announced that its facial recognition algorithm has achieved top performance in the latest National Institute of Standards and Technology (NIST)'s Face Recognition Technology Evaluation (FRTE) 1:N Identification benchmark, reaffirming the company's leadership in one of the industry's most demanding and operationally relevant biometric evaluations. The latest NIST FRTE 1:N Identification results place IDEMIA Public Security #1 in most of the tested scenarios, including the benchmark's two most operationally significant identification scenarios: - #1 in all Mugshot Identification types, including the largest evaluation conducted by NIST against a gallery of 12 million identities, demonstrating robustness and exceptional accuracy at a national scale. - #1 in Visa Border Identification, delivering a significant improvement in performance with identification errors reduced by more than 40% compared with IDEMIA Public Security's previous 2025 submission. - Top Tier in Fairness for False Positive Identification Rate, ensuring that users not only use the most accurate and efficient technology to date but can also be confident that they comply with the most demanding AI regulations in the world. The FRTE 1:N Identification benchmark evaluates how accurately facial recognition systems identify an individual by searching one face against millions of enrolled identities. Considered one of the world's leading benchmarks for facial recognition technology, it evaluates performance in real-world scenarios including mugshot identification, visa processing, border management, law enforcement investigations, and national identity programs. As governments and agencies process millions of travelers and identity transactions every day, achieving both exceptional accuracy and scalability have become essential. These latest NIST results demonstrate IDEMIA Public Security's ability to deliver highly accurate identification across some
Aug 13, 2026 · via prnewswire.com
Brazilians weigh the benefits of AI facial recognition against the costs Loading... | Rio de Janeiro In a downtown office building near Rio de Janeiro’s famous Sambadrome avenue, a dozen police officers sit behind desks staring up at a large bank of computer monitors. Mug shots, camera footage, and interactive maps blink from the screens. This is Rio’s Integrated Command and Control Center, or CICC, the state security forces’ technological nerve center. Facial recognition cameras operated by the military police are a key part of this infrastructure. Using artificial intelligence, smart cameras scan the biometric data of passersby against a database of outstanding arrest warrants. Officers at the CICC are alerted if there’s a match and send the closest patrol to conduct a stop. Why We Wrote This Who suffers when AI gets things wrong? In Brazil, where fighting crime is a top priority for citizens, facial-recognition technology is exploding, even though the legislature is still working on laying out clear rules. Fear of crime that for many outweighs concern for data privacy has made Brazil fertile ground for the mass adoption of these kinds of surveillance technologies. There are more than 560 projects using facial recognition technology across the country – more than double the number in use two years ago, according to civil society organization O Panóptico. The majority are run for public security purposes by local governments or police forces, but they’re also implemented in some private spaces, such as schools. While advocates say smart cameras can help bring down crime, the explosion of this technology without a clear legal framework raises questions about oversight, privacy, and who suffers the most when AI gets things wrong. It’s a public policy that has widespread support, says Thallita Lima, research coordinator at O Panóptico. “Public security is a problem,
Aug 13, 2026 · via csmonitor.com
Vadzo Imaging Introduces Bolt-2020BRS: 20MP AR2020 Raw Bayer MIPI Camera for AI Inspection, OCR, and Embedded Vision Vadzo's Bolt-2020BRS is a 20MP AR2020 Raw Bayer MIPI Camera built on the onsemi HyperLux LP AR2020 sensor, streaming unprocessed 8-bit Bayer data over 4-lane MIPI CSI-2 with sub-10ms latency for AI inspection, OCR, and embedded vision platforms needing direct sensor access for custom ISP pipelines on SoC accelerators, FPGAs, and edge AI platforms. As a board-level AR2020 Bayer MIPI Camera with 100dB HDR and NIR response at 850nm and 940nm, it gives OEM teams full control over image processing rather than a fixed onboard pipeline FORT WORTH, Texas, August 13, 2026 (Newswire.com) - Vadzo Imaging, a provider of embedded vision camera products, today announces the launch of the Bolt-2020BRS, a 20MP AR2020 MIPI Camera built for OEM teams who need direct access to unprocessed high-resolution sensor data rather than a fixed onboard image pipeline. As a 20MP Bayer MIPI Camera delivering 5120x3840 raw output at 1.4 µm pixel pitch over 4-lane MIPI CSI-2, it connects directly to the host SoC ISP, giving integrators the sensor data foundation for hardware-accelerated custom processing on Jetson, Raspberry Pi, and i.MX8M Plus platforms. Technical Problem Definition Many embedded AI inspection, OCR, and machine vision systems fail not because of insufficient resolution but because of processing decisions made before the frame reaches the inference pipeline. A camera module with a fixed onboard ISP applies demosaicing, noise reduction, and tone mapping tuned for general-purpose viewing rather than the feature set for an inspection or recognition model depending on. For AI Defect Inspection Camera Module deployments identifying sub-millimeter surface defects, or OCR MIPI Camera systems extracting character geometry from low-contrast labels, that early processing can discard detail the downstream algorithm needs, with no way to recover it once committed.
Aug 13, 2026 · via newswire.com
British Transport Police is extending its live facial recognition (LFR) trial to the London Underground, despite ongoing privacy and accuracy concerns, according to The Register. The deployment will initially focus on Victoria Underground station before rotating to other stations. The LFR technology, utilizing the NEC NeoFace M40 algorithm, scans faces against a police watchlist, alerting officers to potential matches for review. This expansion follows a pilot at London Bridge railway station and similar deployments by the Metropolitan Police. Critics, including civil liberties group Big Brother Watch, have labeled the technology "dystopian" and "intrusive," citing instances of innocent individuals, particularly from ethnic minorities, being misidentified. Concerns also extend to the routine use of such pervasive surveillance in a democracy and the storage of facial images. A recent survey indicated public apprehension regarding errors and data handling. British Transport Police maintains that images of non-matches are deleted immediately and emphasizes its commitment to lawful, proportionate, and transparent use of the technology to protect the public and combat crime. Kelley Damore is Chief Content Officer at CyberRisk Alliance, where she leads content strategy across the company’s digital brands, research, communities and live events serving CISOs and security practitioners. At CyberRisk Alliance, she is focused on delivering 365-day engagement, trusted journalism and actionable insights to help security leaders navigate an increasingly complex threat landscape. Kelley Damore is Chief Content Officer at CyberRisk Alliance, where she leads content strategy across the company’s digital brands, research, communities and live events serving CISOs and security practitioners. At CyberRisk Alliance, she is focused on delivering 365-day engagement, trusted journalism and actionable insights to help security leaders navigate an increasingly complex threat landscape. Registering with SC Media is 100% free. Join tens of thousands of cybersecurity leaders today and gain access to the latest analysis shaping the global infosec
Aug 13, 2026 · via insight.scmagazineuk.com
Honor's Robot Phone has launched in China with a 4-DoF gimbal camera and the first ARRI color science pipeline built into a smartphone. Here's what's inside, and what it costs. To be totally honest, we were rather skeptical of the Honor Robot Phone when it was first announced. But, following a rollout path that has taken in everything from MWC 2026, Cannes, and the 28th Shanghai International Film Festival, it launched yesterday in China. And above and beyond what we still can’t help thinking of as a bit of a gimmick in the shape of its 4-DoF integrated gimbal camera, it is the first smartphone to feature ARRI color science in its image processing pipeline. ARRI's first smartphone So, let’s start there. The main camera supports 10-bit ARRI LogC3 recording in a dedicated ARRI Cinema mode, combined with ARRI Wide Gamut 3 and built-in, real-time-previewable ARRI Looks. Honor says footage can go straight into the likes of DaVinci Resolve with ARRI LUTs applied as part of a "complete mobile capture-to-post-production workflow." Harald Brendel, ARRI's Director of Image Science, has said that the two companies have calibrated the phone so that it can use the same LUTs as an ALEXA and thus produce “very similar” images. There is a lot more to an imaging pipeline than just that though, and as yet we don’t know the details of bitrate or measured dynamic range (Honor claims 14 stops). Perhaps more importantly, Honor has confirmed the ARRI technology will extend into the upcoming Honor Magic9 Series, which is a far more straightforward, conventional smartphone and is liable to be the one that really introduces ARRI color science into the mass smartphone space. Camera and gimbal details The Honor Robot Phone has three cameras: a dual 200 MP system featuring a 200 MP, 1/1.28-inch,
Aug 13, 2026 · via redsharknews.com
Youverse highlights population-scale facial recognition accuracy in NIST evaluation Youverse says its first submission to the NIST’s ongoing Face Recognition Technology Evaluation 1:N Identification track validates the accuracy of its software as suitable for population-scale fraud detection. The company’s youverse_001 facial recognition algorithm recorded a false-negative identification rate of 0.43 percent at a threshold limiting the False Positive Identification Rate (FPIR) to approximately 0.3 percent when matching frontal mugshot probes against a gallery of 1.6 million mugshots. Youverse expresses this as a 99.57 percent true identification rate. “Independent evaluation by NIST is a major milestone for Youverse and a powerful validation of what we have built,” says Miguel Lourenço, the company’s CPO. “Achieving a 99.57 percent true positive identification rate against a gallery of 1.6 million faces demonstrates that our technology delivers the scale and accuracy demanded by the world’s most critical identity systems,” Lourenço adds. One-to-many identification compares one probe image against an entire gallery to find a possible matching identity. Organizations often use 1:N identification to search large databases for duplicate enrollments or people registered under different identities. When searching a NIST mugshot gallery with 12 million identities, the algorithm recorded a 98.97 percent identification rate. Youverse says this large-scale search capability could support identity deduplication, fraudulent enrollment detection, access control, KYC, and anti-money laundering (AML) processes. The company’s best result by ranking among the main FRTE metrics was matching probe images captured by biometric kiosks against a gallery of 1.6 million visa images. Youverse delivers the facial matching algorithm with liveness detection and says its platform permits one-to-many searches only with explicit user consent. The latest NIST FRTE 1:N results showed that performance continues to converge in controlled comparisons such as frontal mugshot identification. Important performance differences remain when algorithms face more difficult images, including webcam captures,
Aug 13, 2026 · via biometricupdate.com
DHS surveillance spending tops $2.9B as domestic enforcement architecture expands The Department of Homeland Security (DHS) has recorded more than $2.9 billion in contract obligations since January 2021 for technologies capable of watching, identifying, locating and compiling detailed profiles of people inside the United States, according to a new Brennan Center for Justice analysis. An analysis of the Brennan Center’s underlying contract spreadsheet by Biometric Update shows the spending is accelerating. Approximately $1.36 billion in obligations have been recorded since President Donald Trump returned to office, including about $805 million through July 26, 2026—already more than the total identified for any full year from 2021 through 2025. The spending spans facial recognition and other biometrics, drones, commercial data purchases, cellphone extraction and location tools, and AI-driven analytical platforms that combine information from government and private databases. Rather than documenting a single surveillance technology, the report maps an increasingly integrated enforcement architecture in which multiple systems work together to identify, locate and profile people. Biometrics account for the largest share Biometric programs account for approximately $1.1 billion of the obligations identified by the Center, more than any of its other five categories. Much of that amount supports the expansion and maintenance of DHS’s central biometric infrastructure, including its legacy Automated Biometric Identification System (IDENT) and the Homeland Advanced Recognition Technology program intended to succeed it. General Dynamics, Peraton and Science Applications International Corporation are among the principal contractors. Another large portion went to Amentum and Pluribus Digital for collecting biometric and biographical information from applicants seeking immigration related benefits. The category also includes mobile identification systems that bring biometric searches out of controlled enrollment centers and into field operations. Among them is Mobile Fortify, the NEC-developed facial recognition application used by Customs and Border Protection (CBP) and Immigration and Customs Enforcement
Aug 13, 2026 · via biometricupdate.com
Back to Journals » Journal of Multidisciplinary Healthcare » Volume 19 NeuroMimicNet: A Multimodal Neuromorphic Framework for Early Screening and Cognitive Pattern Recognition in Children with Autism Received 24 February 2026 Accepted for publication 7 May 2026 Published 14 August 2026 Volume 2026:19 605039 DOI https://doi.org/10.2147/JMDH.S605039 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 2 Editor who approved publication: Dr David C. Mohr Poornima S, Elakya R School of Computer Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, Tamil Nadu, 600127, India Correspondence: Elakya R, Email [email protected] Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition which is composed of social, behavioral, and communication challenges that generally require early detection. Purpose: This research proposes NeuroMimicNet, a brain-like event-driven neuromorphic computing framework designed for early screening and cognitive pattern recognition in children with autism. The framework integrates audio signal and facial expression images as multimodal inputs to capture both neural and behavioral patterns. Methods: The audio modality involves pre-processing steps including noise elimination and normalization, while the neuromorphic processing of audio features is done with Spike-Timing-Dependent Plasticity (STDP), Hebbian learning and a Loihi-inspired spiking neural processing model to capture temporal auditory patterns efficiently. The facial expression images are pre-processed through face alignment, resizing and normalization, and high-level visual features are extracted using a pretrained ResNet50 convolutional neural network. The extracted audio and image features are fused at the feature level to form a unified multimodal representation. The fused features are then classified into four ASD severity level such as Typical, Mild, Moderate, and Severe using a supervised classification model. Results: Performance is evaluated using accuracy, F1-score, precision, recall, and computational efficiency across benchmark EEG-autism datasets. Experimental results demonstrate that NeuroMimicNet achieves higher accuracy and faster response compared to conventional deep learning models.
Aug 13, 2026 · via dovepress.com
| Study shows that quantitative CT analysis of orbital structures offers a potential, objective method for assessing TED activity, enabling clinicians to identify high-risk patients who may require prompt therapeutic intervention. Photo: Bobby Saenz, OD. Click image to enlarge. | In a recent study, researchers aimed to identify a relationship between orbital CT parameters (volume and density) and inflammatory activity in patients with thyroid eye disease (TED). The team found five predictors of active TED, including larger extraocular muscle (EOM) volume and higher intraorbital fat density, suggesting that quantitative CT analysis may be useful for assessing TED activity. The findings were reported in PLoS One. This retrospective study analyzed CT images and clinical records of 85 TED patients and 15 controls. Orbital segmentation was performed using commercially available software. The volumes and densities of the EOMs, intraorbital fat and lacrimal gland were measured. CT parameters were compared among the control, active TED and inactive TED groups. Patients were further classified into two subgroups based on disease severity: mild TED and moderate-to-severe TED. Patients with active TED (defined by a clinical activity score ≥3) demonstrated significantly larger EOM volumes and higher intraorbital fat densities compared to those with inactive TED. Five robust, independent predictors of active TED were found: - shorter disease duration - higher serum thyroid-stimulating immunoglobulin levels - larger EOM volume - higher EOM density - higher intraorbital fat density Combining clinical, serological and quantitative CT metrics resulted in exceptional diagnostic performance, indicated by an area under the ROC curve (AUC) of 0.938. Stratified analysis confirmed that EOM volume and intraorbital fat density remained significantly different between active and inactive TED groups across both mild and moderate-to-severe disease categories. In the moderate-to-severe subgroup, all four extraocular rectus muscles were larger in active TED patients. In the mild subgroup, only
Aug 13, 2026 · via reviewofoptometry.com
The company behind 300,000 Eftpos terminals across Australia is hoping shoppers will want to make payments by simply glancing at a screen, as biometric technology pushes further into retailing. Verifone is selling the innovation as “pay for your coffee with a smile”, promising faster checkouts for people who opt in to having their face or palm-vein – the veins in people’s hands – biometrics used for Eftpos transactions in Australia. It may take a long time before the technology is widely available, however, with cafes, restaurants and retailers required to upgrade their existing equipment. The head of product for Asia Pacific at Verifone, Ben Hughes, said the biometric payments will ease the “friction” of slow transactions. “If you go to a grocery store and you have to tap a loyalty card, plus tap a payment card, that’s the kind of thing that now we’d be able to speed up,” he said. He said the company was expecting retailers to deploy the Verifone Victa devices, which launched last month, incrementally as their current terminals reached their end of life. Hughes said the technology will need buy-in from banks and other organisations that want to allow their customers to pay using biometrics. Biometrics are converted into tokens on the device, he said, meaning images are not stored by Verifone, but biometric profiles are managed by merchants, banks or digital wallet providers. Customers will be able to continue to use contactless payments on their card or phone. Hughes said the company had measures in place to avoid users “spoofing” other people’s hands or faces, as has been seen in the rollout of facial verification technology, similar to that used in age assurance technology for Australia’s social media ban. The company is expecting some pushback on the shift to biometrics, but compared it to
Aug 13, 2026 · via theguardian.com
Dublin, Aug. 12, 2026 (GLOBE NEWSWIRE) -- The "Artificial Intelligence AI" has been added to ResearchAndMarkets.com's offering. Artificial Intelligence Patent Landscape Report 2010-2024: Global Market, Technology and Competitive Analysis The Artificial Intelligence Patent Landscape Report delivers a comprehensive analysis of 244,202 AI patents filed across major jurisdictions between 2010 and 2024. Drawing on international patent filings, the report examines innovation across healthcare, finance, entertainment, agriculture, energy, logistics, industrial automation, retail, manufacturing, transportation, consumer electronics and enterprise software. The analysis combines quantitative patent data, descriptive statistics, artificial intelligence, natural language processing, topic modeling, patent clustering and International Patent Classification-based technology segmentation. It provides actionable intelligence on patent activity, competitive positioning, geographic coverage and emerging innovation opportunities in machine learning, neural networks, natural language processing, computer vision, image and video recognition, pattern recognition, robotics, predictive analytics and intelligent automation. Organized into Landscape Overview, Market and Competitor Analysis, Technology Analysis and Key Players' Patent Profiles, the report supports strategic decision-making in research and development, product innovation, investment, licensing, partnerships, mergers and acquisitions and market entry. Artificial Intelligence Patent Landscape Overview The landscape overview tracks global AI patent trends from 2010 through 2024. The dataset includes 106,684 active patents, 94,075 pending patents and 42,952 inactive, discontinued or expired patents. Filing activity reached its highest level in 2023, when more than 45,000 new patents were recorded. Approximately 95% of the identified patents have been registered since 2019, underscoring the rapid acceleration of artificial intelligence research and commercialization. China leads the global artificial intelligence patent landscape with 115,768 registrations, followed by the United States with 58,671 patents. South Korea, Europe and other jurisdictions account for smaller shares. These results highlight China's dominant filing position and the United States' substantial contribution to global AI innovation. Artificial Intelligence Market and Competitor Analysis The market analysis evaluates global AI
Aug 13, 2026 · via globenewswire.com
Facial detection technologies have gone from commonplace to near-ubiquitous in major cities, prompting some privacy researchers to look for ways to thwart them. Hacker and former CISO Bill Swearingen's noRecognition project can now generate patterns that hide a wearer from cameras, making them useful for t-shirts, face coverings, hats, and other garments to help maintain your privacy. People have been using makeup and specific clothing patterns to trick smart cameras for years, but with improvements in AI and image recognition, this has grown increasingly difficult. The noRecognition project wants to both enhance these apparel countermeasures and make them more readily available, hence the crowdfunding campaign. "Privacy is a fundamental right," Swearingen told TechCrunch, saying he wanted people to be able to opt out of being tracked with something as simple as a choice of clothing. My grandparent's sofa probably would have been invisible to modern facial recognition systems.Credit: noRecognition These patterns will be sold in two different tiers: Standard and One of One. The former will include the mainstream patterns the project generates, giving you broad-spectrum coverage against detection by security and surveillance systems. However, it's possible that AI developers will one day buy these prints and train their models to track them, making them less useful as protective measures. One of One, however, will only be sold in extremely limited numbers: 50 of each pattern across the various clothing options. Once those 50 are sold, that pattern will never be sold again, in theory, making it almost impossible for an AI model developer to use it for training, as its supply and use would be too limited. Swearingen is also releasing his team's numbers to keep the campaign honest. You can see which vision systems the patterns were tested against, how well they work when worn by different people
Aug 12, 2026 · via tech.yahoo.com