Pros & Cons - - Slick interface - Useful face recognition tools - Capable auto-corrections - Supports plug-ins and raw files - AI object removal and search - - Available only for Apple devices - Nearly impossible to uninstall on macOS - Weak web interface Apple Photos Specs | Content-Aware Edits | | | Face Recognition | No software is immune to the AI craze, including Apple Photos. It's an indispensable photo editing app that syncs your photos between all your Apple devices and supports Live Photos, Portrait Mode, and the ProRaw format. It comes free with the purchase of any iPad, iPhone, or Mac and offers features you typically see in professional software, including HSL color editing, noise reduction, a vibrance tool, and tone curves. Generative AI remove and powerful search tools are new for the current version, and more AI features are coming later this year. Apple Photos is a fine option for photo hobbyists and a must-download for iPhone users, but the cross-platform Google Photos remains our Editors' Choice winner for entry-level photo editing software. Pricing: Free With the Purchase of an Apple Device The price of an Apple computer, phone, or tablet is all you pay to use Apple Photos, which comes preinstalled. In fact, you can't uninstall it from macOS without taking extreme measures that include command-line operations. Apple's iCloud Photos service, which dependably syncs your photos between iPads, iPhones, and Macs, gives you just 5GB of free storage. Fees range from 99 cents per month for 50GB to $59.99 for 12TB, but the sweet spot for most users is probably the $9.99-per-month 2TB plan. If you want to work on more operating systems, use Adobe Photoshop Elements, Google Photos, or Lightroom instead. For comparison, Google Photos is free for everyone and includes 15GB of
Jun 29, 2026 · via uk.pcmag.com
The Western Australian government is trialling Live Facial Recognition (LFR) technology across the state, with the Australian Retail Council (ARC) welcoming the news. This comes after Kmart and Bunnings were caught up in a review by the Privacy Commissioner over their use of facial recognition technology between 2020 and 2022 to help crack down on retail crime – particularly refund fraud. The ARC called the LFR trialling an encouraging step towards the responsible use of suspect matching technology, with the potential to help protect frontline retail workers and customers from known, high-harm repeat offenders. The WA government did not specify exactly where LFR will be deployed, only noting places like Perth CBD, Maitland and other jurisdictions. “All deployments are overt and will occur in public spaces where LFR has the greatest potential to assist the WA Police Force in fulfilling its operational duties,” the WA government shared. This comes as around 800,000 retail crime incidents were recorded across Australia in 2024, according to the ARC, with one in five of these events involving threats, aggression, intimidation, harassment or other serious behaviours. The peak body added that just 10 per cent of offenders are responsible for around 60 per cent of all retail crime incidents, with repeat offenders up to four times more likely to be violent. Independent national polling commissioned by the ARC also shows Australians strongly support the targeted use of suspect matching technology in situations involving genuine safety risks. Eight in ten (81 per cent) support its use to identify individuals who have previously threatened retail staff with a weapon, with 80 per cent supporting its use to identify people who have physically assaulted retail workers or customers. The ARC added that retailers are keen to see the practical lessons from the WA trial extended to responsible suspect
Jun 29, 2026 · via ragtrader.com.au
Physical AI: Bridging Digital and Real Worlds Physical AI is gaining traction by integrating intelligent agents into real-world environments, enhancing tasks through environmental interaction and motion control. Industry experts foresee significant commercialization potential in various sectors. Par Yu Sinan, People's Daily Artificial intelligence continues to evolve remarkably—from image recognition and text generation to video creation—demonstrating increasingly sophisticated capabilities. As these digital capabilities mature, the technology sector is shifting focus toward integrating AI into physical environments. This emerging concept, known as physical AI, is gaining significant traction within the industry. Physical AI represents intelligent agents capable of perceiving physical environments and performing human-like actions beyond digital interfaces. Ma Xiaojian, head of the joint laboratory between the Beijing Institute for General Artificial Intelligence and Delta Intelligence, noted that physical AI has three defining features: its capabilities are built on real-world physical interaction data, it incorporates an understanding of the physical world, and it can be deployed in real-world physical entities. Where generative AI excels in content creation and data analysis, physical AI specializes in environmental interaction and motion control tasks. "While representing different AI dimensions, these domains demonstrate growing convergence," Ma noted. Generative AI's capabilities—including language interpretation, scenario modeling, and automated coding—enhance physical AI's task execution and environmental navigation. Over the past few years, the tech industry has advanced physical AI from core algorithms to ontology engineering through multiple approaches. Ma said that there are three main technical pathways currently used to implement physical AI. The first is the "pre-training and post-training" approach, in which models undergo large-scale pre-training on internet videos, first-person videos, and cross-robot manipulation data before being further refined through teleoperation data, reinforcement learning, or real-world fine-tuning. The second is the "real-simulation-real" approach, which reconstructs real-world geometry, materials, and dynamics into high-fidelity simulation environments, enabling robots to learn through
Jun 28, 2026 · via alwihdainfo.com
This story by Derechos Digitales originally appeared on Global Voices on June 27, 2026. In Latin America, surveillance is rarely presented as what it is. More often than not, it is set into motion on the premise of other promises: safety, efficiency, and order. It thus colonizes increasingly quotidian spaces until it no longer seems strange to us. Before, when a facial recognition camera seized our attention, we even questioned it. Today, it is part and parcel of public transport, mass events, and football stadiums. The advance of these technologies is not occurring as an exception or temporary measure. They are established silently and often without public debate, transparency, or people truly knowing what data is being recorded, who is storing it, or how it can be used later. At best, it is hidden behind individual consent. At worst, it is assumed to be what the people need. In May 2024, over 1.5 million people gathered on Rio de Janeiro’s Copacabana Beach for a free concert by Madonna. It was a night of celebration, but also one marked by large-scale surveillance, as thousands of agents, drones, and facial recognition cameras were deployed in the name of safety. Derechos Digitales documented the incident and included it in a report for the Inter-American Commission on Human Rights’ Special Rapporteur for Freedom of Expression. The concert surveillance was not limited solely to physical space. According to a media report from Brazil, the Rio de Janeiro Military Police also intensified its social media monitoring as part of its strategy for the event. The so-called “cyber patrol” was conducted without a clear legal framework that established any specific limits, controls, or supervision mechanisms. The crowd was not just observed by cameras at the beach; their online posts, comments, and other interactions were also tracked. This
Jun 28, 2026 · via newsgram.com
6ai — bringing thinking back applied intelligence. Think. Don’t Outsource There was an article the other day in The Telegraph titled “Accenture’s crash shows the consultancy racket is finished.” Although I agree with the article, this journalist’s revelation is a bit late. Anyone paying attention already knows this, and the “crash” has many maturation stages before the racket is gone for good. The consulting industry weakens our businesses, infantilizes our governments, and warps our economies, according to the author of The Big Con, Mariana Mazzucato. Big consulting serves neither citizens nor consumers, and it stunts innovation and obfuscates corporate and political accountability, she goes on to say. The consulting industry has pulled off a confidence trick, which, over the many decades, has hollowed out our thinking. The subtitle says: “Smart chatbots have exposed just how shallow much of the industry has become.” Again, I agree with the premise, but “chatbots” in themselves, as the argument for AI replacing much of consulting work goes, are just more hype to sell more AI stuff. There is always change when new automation technology enters the scene, and the consulting industry is facing the same fate as many other industries have before. But it is fair that this is a very powerful automation technology. The new hype is that companies like OpenAI/ChatGPT and Anthropic’s Claude are taking over from consulting. I don’t think so. These models don’t solve problems, make organizations think and get better. They just speed up information processing and generate outputs that are already programmed in the training data. These models tell us nothing new. Claude AI can provide research in seconds that a junior analyst might take hours or days to produce and package coherently in a slide deck. Then the senior partner comes along and charges $1500 per hour
Jun 28, 2026 · via perry-douglas.medium.com
From teen heartthrobs to swoon-worthy leading men, every decade has had its own class of ridiculously good-looking guys. Below you'll find 20 male celebs people couldn't stop crushing on over the years, and all you have to do is name each one. Good luck!
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Jun 28, 2026 · via buzzfeed.com
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Jun 28, 2026 · via instagram.com
Every time you search, browse, or interact with an app, you generate data. That data is worth billions to AI companies. But the platforms that collect it keep almost all the value. A new generation of decentralized AI data marketplaces wants to flip that arrangement — using crypto to pay contributors directly whenever their data trains a machine learning model. The mechanics go deeper than a simple "own your data" slogan. There are verification layers, staking systems, privacy constraints, and token economics — and together they decide whether a contributor gets paid fairly or not at all. This piece explains how those systems work, from the ground up. TL;DR - Decentralized AI data marketplaces connect people who own raw data with AI developers who need labeled, verified training sets, and use crypto tokens to handle payments trustlessly. - Contributors submit data, which is verified on-chain or via decentralized oracle networks before a payment is released, removing the middleman platform from the revenue split. - Privacy-preserving techniques like federated learning and zero-knowledge proofs let data be monetized without the raw underlying information ever leaving the contributor's device. - Token economics, including staking, slashing, and reputation scoring, align incentives so contributors submit accurate data rather than junk. - Projects like Kled AI on Solana represent the current frontier, but the model spans multiple chains and several competing architectures. Why AI Companies Need So Much Data And Who Pays For It Today Large language models and image-recognition systems are data-hungry in a way that's hard to overstate. A single training run for a frontier model can consume hundreds of billions of text tokens, millions of labeled images, or years' worth of recorded human behavior signals. That data has to come from somewhere. Today, most of it comes from a handful of routes. Web
Jun 28, 2026 · via yellow.com
The European Space Agency’s (ESA) Euclid space telescope has captured the largest and most detailed visible-light image ever obtained of the Milky Way's galactic bulge, the central region of our galaxy. The image is a mosaic containing more than 60 million stars, as well as nebulae and star clusters. It will allow scientists to confirm the possible presence of exoplanets using a microlensing technique and measure their masses with greater precision. The Power of Euclid Although Euclid was designed to observe billions of distant galaxies, its visible-light camera is sensitive enough to resolve individual stars at the center of the Milky Way—a region that is both extremely bright and densely populated—without being overwhelmed by the intense light. On March 23, 2025, Euclid turned its gaze toward the galactic bulge, capturing this enormous image in just 26 hours of observations. The result was remarkable: a mosaic composed of nine separate “pointings” (exposures) by its visible-light camera, each covering an area of sky larger than the full moon. While the quality of Euclid's visible-light images is comparable to that of the Hubble Space Telescope, there is one major difference: Each pointing that Euclid captures in just a few hours covers an area 270 times larger than Hubble's field of view. It is also much faster. To put this into perspective, the Keck Observatory would require roughly 2,000 hours to observe the same mosaic. The Image of the Milky Way The new Euclid image captures more than 60 million stars, along with nebulae and star clusters, in one of the Milky Way's most crowded regions—a location ideally suited for searching for exoplanets through gravitational microlensing. “To catch microlensing, you need to observe parts of the sky that are crowded with stars, such as close to the centre of our galaxy,” said Jean-Philippe Beaulieu,
Jun 28, 2026 · via wired.com
Mouse brain activity was used to recreate 10-second videos, offering a new way to study how vision is represented in the brain. Scientists led by University College London (UCL) have reconstructed videos using only brain activity recorded from mice, allowing them to recreate what the animals were seeing. The findings, published in eLife, could help researchers better understand how the brain handles visual information and may offer new ways to study how different species experience the world around them. In recent years, scientists have become increasingly interested in how the human brain makes sense of signals from the eyes. Researchers have shown images and movies to people in fMRI scanners and have tried to decode visual information in the brain down to the pixel level. The new work follows that same broad goal, but it uses single-cell recordings in mice instead. This approach can provide a more detailed view of how the brain represents visual scenes. Using activity from the visual cortex alone, the team was able to produce high-quality reconstructions of videos the mice had watched. Lead author Dr. Joel Bauer (Sainsbury Wellcome Centre at UCL) said: “We wanted to have a better way of investigating how the brain interprets what we see. The current methods of understanding what specific groups of neurons are representing are not very generalizable to situations that haven’t been specifically tested for. And so, we wanted to develop a method that can capture what is being represented in the brain and compare that to reality.” Neurons recreate visual scenes The method could help scientists examine the gaps between what is actually shown and how the brain represents it. Those differences may reveal how particular visual cues influence neural representations. Dr Bauer and colleagues used a dynamic neural encoding model that had been developed by
Jun 28, 2026 · via scitechdaily.com
Understanding Agentic AI: Why sci-fi apocalypse films have been warning us Agentic AI, a new tech buzzword, involves AI systems making more autonomous decisions, raising concerns reminiscent of sci-fi apocalypse films. Picture: Google Gemini Image: Google Gemini The new buzzword in tech is definitely Agentic AI, but what exactly is it, and should we be worried? Firstly, Agentic AI means handing over more control to an increasingly powerful AI application. It will be able to make more decisions on its own and, as a result, do more for the end user. For example, if you want to book tickets to an event, Agentic AI will be able to handle almost everything. That means you can issue a prompt like: “Book me tickets to the Beyoncé concert next month.” It will then find out exactly when the concert is, check with the user about seating preferences, and then confirm payment, either through biometrics or facial recognition software. Apple’s Siri AI to Enter the Agentic AI Market in September Apple’s Siri AI will be one of the latest entries into the Agentic AI market when it officially launches in September. It will join other leading Agentic AI platforms such as ChatGPT Operator, Claude (Anthropic), and Microsoft Copilot Studio. To be clear, this shift in the way AI works could gradually change the way we use technology altogether. As someone who grew up watching Terminator, which dealt with computers becoming self-aware and swiftly moving to wage war on, and essentially exterminate, humankind, this shift does not sit comfortably with me. Of course, we are probably still at least a couple of decades away from AI being capable of building its own self-aware robots designed for nefarious purposes. But the fact that we are on a path that could eventually lead there is, at
Jun 28, 2026 · via iol.co.za
G7 Data Protection Summit: Call for rules on age verification and smart homes The G7 supervisory authorities demand strict protection of fundamental rights in online age verification and are targeting connected children's rooms. The digitalization of everyday life increasingly poses challenges to privacy protection, not least for minors. At their annual meeting, which concluded on Friday in Paris under the chairmanship of the French supervisory authority CNIL, the G7 data protection authorities therefore focused on the digital security of children and adolescents. The summit resulted in groundbreaking decisions on the contentious issue of age verification online and security in smart homes. In the Declaration for privacy-friendly age verification, which is controversially debated in Germany as well as a social media ban, the G7 data protectionists do not fundamentally oppose reliable exclusion criteria for children and adolescents in parts of the internet. According to them, age controls could be an important tool to protect young people from content harmful to minors, such as pornography, or to enforce legal age limits in social networks. However, the experts warn against the unthinking, widespread use of such systems: a surveillance mania harbors considerable risks for the fundamental rights and freedoms of all users, for example through the restriction of freedom of opinion and information. They demand that age safeguards must always be proportionate and strictly aligned with the specific context and the actual risk. Before states resort to such far-reaching technical controls, parental supervision and digital media literacy should be strengthened as a priority. Strict conditions for online age verification If online age verification is unavoidable, data protection must be built directly into the technology (Privacy by Design), the paper states. The G7 data protectionists emphasize that the data collected must be used exclusively for age verification and must not be misused for user
Jun 28, 2026 · via heise.de
A third-year medical student told me last month she was not going to apply to radiology. She had been interested all through second year, had done a sub-internship she liked, and had the grades to match anywhere. Then she changed her mind. The reason, almost verbatim: “My advisor said I should not go into a field that AI is going to replace.” She is not the only one. I have heard this from at least five students in the last year, from family medicine attendings warning their best students off radiology, and from internal medicine residents asking me, half-jokingly, whether I am worried about my career. The fear is real, widespread, and wrong. It is also doing damage to a field that is in shortage and that will be leading AI deployment to the rest of medicine for the next two decades. Here is the data the fear is built on. A recent analysis I co-authored of every AI/ML-enabled medical device the FDA has authorized over the past three decades, 1,430 devices, found that 76.5 percent were reviewed by the FDA’s Radiology panel. Cardiovascular came in second at 9.5 percent, neurology third at 4.5 percent. The remaining 19 review panels combined accounted for less than 10 percent. Pathology had nine. Microbiology had six. The psychiatry panel had zero. If you only saw the radiology number, the conclusion writes itself: AI is coming for radiology first and hardest. That is the version of the story that has reached advisors and students. It is also the wrong reading. That 76.5 percent represents where the data is, not where AI is replacing physicians. Radiology runs on DICOM, a universal imaging standard that makes a chest CT in Boston and a chest CT in Bakersfield the same file, labelable by the same workflow. There
Jun 27, 2026 · via kevinmd.com
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Jun 27, 2026 · via sfgate.com
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Jun 27, 2026 · via iopscience.iop.org
Biometrics market signals strong as providers expand reach The expansion of the global biometrics market, fast and steady, can sometime be obscured by the controversies that come along with powerful new technology and a competitive business environment. Headlines from the past week serve as a reminder of the momentum behind biometrics providers and digital identity projects around the world, and reveal some interesting clues about the direction those projects will take going forward. M&A and investments ROC’s acquisition of ZTC is targeted at expanding its video intelligence platform end-to-end, building its face biometrics core capability into an overall digital forensics investigation platform. The deal continues the post-IPO clarification of vision for ROC serving a customer base beyond its federal government core. Incode is building a network for sharing fraud signals while doubling down on its privacy-first, decentralized vision through the acquisition of Identiq. A key market expansion operating here is the threat of agentic AI, which can be mitigated by pooling data. Incode CEO Ricardo Amper has also shared insights into the deal with Biometric Update for an interview article coming next week. Investors remain bullish on IDfy, and by extension the Indian KYC market, as seen in the $23 million the company has picked up to expand its risk detection tools. IDfy is marching towards an IPO with a self-declared timeline of 5 years. Intellicheck’s growth has landed it on the Russell 3000 index as one of America’s largest publicly traded companies, which helps positions its stock with institutional investors. Familiar faces, new tech NEC is supplying live facial recognition to Western Australia Police for trial deployment in public spaces, in one of the first deployments of LFR in a democratic country other than the UK. If the UK’s example holds, a single van in a single state could
Jun 27, 2026 · via biometricupdate.com
What "Familiar Faces" Does Amazon Ring's AI facial recognition feature, launched December 2025, uses computer vision to identify repeat visitors to a home and label them by name in doorbell notifications. The feature is optional for Ring owners, but the core dispute is that the millions of neighbors, delivery workers, and passersby who walk past a Ring-equipped front door are enrolled in biometric scanning without their knowledge or consent. Amazon states that face data is encrypted and that unidentified faces are automatically purged after 30 days. Legal Challenge Virginia resident Charles Sigwalt filed a class action lawsuit in Seattle federal court in June 2026, seeking at least $5 million in damages on behalf of a proposed class. The complaint, reported by TechCrunch and Reuters, claims Ring cameras at friends' and family members' homes collected and stored his facial recognition data without consent. The suit follows earlier public criticism from the Electronic Frontier Foundation and Senator Ed Markey (D-MA), who demanded Amazon abandon the feature before its December launch. Amazon did not publicly respond to the lawsuit at the time of filing. Regulatory Map The feature is unavailable in Illinois and Texas - both states with strong biometric privacy statutes - and in Portland, Oregon, which has enacted private-sector facial recognition restrictions. That geographic carve-out signals Amazon acknowledges elevated legal risk where robust biometric law exists, making the lawsuit in states without those protections the active legal frontier. Pattern of Privacy Concerns Ring's record with law enforcement and user data amplifies public unease. The company paid a $5.8 million FTC settlement in 2023 after employees improperly accessed private customer video. Ring previously granted police the ability to request footage without a warrant before reversing that policy. A February 2026 Super Bowl ad for Ring's AI-powered lost-pet tool "Search Party" triggered a
Jun 27, 2026 · via letsdatascience.com
Agentic AI, a new tech buzzword, involves AI systems making more autonomous decisions, raising concerns reminiscent of sci-fi apocalypse films. Picture: Google Gemini Image: Google Gemini The new buzzword in tech is definitely Agentic AI, but what exactly is it, and should we be worried? Firstly, Agentic AI means handing over more control to an increasingly powerful AI application. It will be able to make more decisions on its own and, as a result, do more for the end user. For example, if you want to book tickets to an event, Agentic AI will be able to handle almost everything. That means you can issue a prompt like: “Book me tickets to the Beyoncé concert next month.” It will then find out exactly when the concert is, check with the user about seating preferences, and then confirm payment, either through biometrics or facial recognition software. Apple’s Siri AI will be one of the latest entries into the Agentic AI market when it officially launches in September. It will join other leading Agentic AI platforms such as ChatGPT Operator, Claude (Anthropic), and Microsoft Copilot Studio. To be clear, this shift in the way AI works could gradually change the way we use technology altogether. As someone who grew up watching Terminator, which dealt with computers becoming self-aware and swiftly moving to wage war on, and essentially exterminate, humankind, this shift does not sit comfortably with me. Of course, we are probably still at least a couple of decades away from AI being capable of building its own self-aware robots designed for nefarious purposes. But the fact that we are on a path that could eventually lead there is, at the very least, cause for concern. Related Topics:
Jun 27, 2026 · via capeargus.co.za
Abstract Medical image registration plays a crucial role in tumor growth monitoring, radiotherapy planning, and disease diagnosis. Recently, Transformer-based networks have been widely adopted in unsupervised image registration, achieving improved registration accuracy. However, the use of attention mechanisms significantly increases model complexity with substantial computational and memory costs, failing to meet the real-time requirements of medical image registration. To address these challenges, this paper proposes a Hierarchical Pyramid Network with Lipschitz Continuity Constraint and Spatial Recurrent Encoding Module for Medical Image Registration (LHPS-Net). The model employs a hierarchical pyramid architecture that enhances registration performance through Lipschitz continuity constraints and spatial recurrent encoding. Specifically, unlike traditional deep learning-based approaches, LHPS-Net independently extracts features from fixed and moving images and progressively generates deformation fields through hierarchical decoders, which facilitates large-deformation image registration. The spatial recurrent encoding module replaces conventional convolutional blocks, utilizing SLK (Spatial Locally-connected Kernel) to capture contextual information with lower computational cost while effectively focusing on multi-scale features. The LC-Def block incorporates Lipschitz continuity constraints to help achieve diffeomorphic deformation. To validate the performance of our proposed network, we conducted comprehensive comparisons with existing methods on public datasets including IXI, LPBA, and OASIS. Experimental results demonstrate that LHPS-Net achieves superior registration performance under common evaluation metrics. Similar content being viewed by others Data availability The datasets used and/or analysed during the current study are publicly available from third-party repositories, including the IXI dataset (https://brain-development.org/ixi-dataset/), the LPBA40 dataset (https://www.loni.usc.edu/research/atlas_downloads), and the OASIS dataset (https://sites.wustl.edu/oasisbrains/). The processed data, experimental settings, and additional materials supporting the findings of this study are available from the corresponding author upon reasonable request. References - Li T, Staring M, Qiao Y (2025) Efficient large-deformation medical image registration via recurrent dynamic correlation[J]. IEEE Transactions on Medical Imaging - Velesaca HO, Bastidas G, Rouhani M et al (2024) Multimodal
Jun 27, 2026 · via link.springer.com
Agentic AI, a new tech buzzword, involves AI systems making more autonomous decisions, raising concerns reminiscent of sci-fi apocalypse films. Picture: Google Gemini Image: Google Gemini The new buzzword in tech is definitely Agentic AI, but what exactly is it, and should we be worried? Firstly, Agentic AI means handing over more control to an increasingly powerful AI application. It will be able to make more decisions on its own and, as a result, do more for the end user. For example, if you want to book tickets to an event, Agentic AI will be able to handle almost everything. That means you can issue a prompt like: “Book me tickets to the Beyoncé concert next month.” It will then find out exactly when the concert is, check with the user about seating preferences, and then confirm payment, either through biometrics or facial recognition software. Apple’s Siri AI will be one of the latest entries into the Agentic AI market when it officially launches in September. It will join other leading Agentic AI platforms such as ChatGPT Operator, Claude (Anthropic), and Microsoft Copilot Studio. To be clear, this shift in the way AI works could gradually change the way we use technology altogether. As someone who grew up watching Terminator, which dealt with computers becoming self-aware and swiftly moving to wage war on, and essentially exterminate, humankind, this shift does not sit comfortably with me. Of course, we are probably still at least a couple of decades away from AI being capable of building its own self-aware robots designed for nefarious purposes. But the fact that we are on a path that could eventually lead there is, at the very least, cause for concern. Related Topics:
Jun 27, 2026 · via thestar.co.za