Friday, May 22, 2026

Texas AG sues Meta over claims that WhatsApp doesn't provide end-to-end encryption


<p>The Texas Attorney General has sued Meta over allegations that the company’s WhatsApp messenger, used by more than 3 billion people, doesn’t provide the end-to-end encryption (E2EE) it has long claimed.</p> <p>Since at least 2016, Meta (then named Facebook) has said WhatsApp provides robust end-to-end encryption, meaning that messages are encrypted on a sender’s device with keys that are available only to the receiver's. By definition, E2EE means that no one else—including the platform itself—can read the plaintext messages.</p> <p>In sworn testimony before two US Senate committees in 2018, CEO Mark Zuckerberg <a href="https://www.congress.gov/event/115th-congress/senate-event/LC64510/text">said</a> Meta does “not see any of the content in WhatsApp; it is fully encrypted” and that “Facebook systems do not see the content of messages being transferred over WhatsApp.” The engine for this E2EE is the Signal protocol, an open source code base that multiple third-party experts have said lives up to its promises.</p><p><a href="https://arstechnica.com/security/2026/05/texas-ag-sues-meta-over-claims-that-whatsapp-doesnt-provide-end-to-end-encryption/">Read full article</a></p> <p><a href="https://arstechnica.com/security/2026/05/texas-ag-sues-meta-over-claims-that-whatsapp-doesnt-provide-end-to-end-encryption/#comments">Comments</a></p> Reference : https://ift.tt/ip0TYqc

Developers: Get Your Medical Mobile App Verified By IEEE


<img src="https://spectrum.ieee.org/media-library/conceptual-illustration-of-user-interface-layers-such-as-networking-information-assurance-and-design.jpg?id=66768355&width=1245&height=700&coordinates=0%2C62%2C0%2C63"/><br/><br/><p>Patients who use mobile applications to manage medical conditions including depression and chronic pain might assume the apps have been evaluated by regulatory agencies to be safe and effective. But that isn’t necessarily the case.</p><p>Most of the more than 55,000 medical apps that claim to diagnose or treat a condition—or ones that provide clinical decision support, known as “therapeutic” apps—have never been assessed by any trusted neutral bodies or regulatory agencies to evaluate them for technical soundness, ethical design, or clinical benefit. The apps often don’t comply with regional data security and privacy laws to protect people’s sensitive health information.</p><p>Medical apps differ from traditional wellness apps, which provide users with insights into becoming healthier by, for example, tracking fitness activities, monitoring blood pressure, and analyzing sleep patterns.</p><p>There is no reliable way to verify that therapeutic apps deliver the results they indicate. To help ensure such apps are credible, the <a href="https://standards.ieee.org/" rel="noopener noreferrer" target="_blank">IEEE Standards Association</a> (IEEE SA) recently launched the <a href="https://standards.ieee.org/products-programs/icap/mobile-health-app-registry/" rel="noopener noreferrer" target="_blank">IEEE Global Medical Mobile App Assessment and Registry</a>. The publicly searchable directory is designed to list apps that have been vetted by experts across several criteria including technical soundness, ethical design, compliance with data security and privacy regulations, and clinical efficacy, which is evidence of a clinical benefit for the patient.</p><p>“Patients, clinicians, payers, and health care systems often struggle to distinguish clinically meaningful therapeutic apps from those that are simply well-marketed,” says IEEE Senior Member <a href="https://research.bidmc.org/yuriquintana" rel="noopener noreferrer" target="_blank">Yuri Quintana</a>, chair of the assessment and registry program. He is chief of the <a href="https://bidmc.org/departments-divisions/medicine/clinical-informatics" rel="noopener noreferrer" target="_blank">clinical informatics division</a> at <a href="https://bidmc.org/" rel="noopener noreferrer" target="_blank">Beth Israel Deaconess Medical Center</a>, in Boston. “Our goal is to establish a standardized review method using criteria developed by experts.”</p><h2>Why regulation is lacking</h2><p>Because the apps are intended for medical use without being part of a medical implement, they fall under the designation of <a href="https://www.fda.gov/medical-devices/cdrh-international-affairs/international-medical-device-regulators-forum-imdrf" rel="noopener noreferrer" target="_blank">software as a medical device</a> (SaMD), according to the <a href="https://www.fda.gov/medical-devices/cdrh-international-affairs/international-medical-device-regulators-forum-imdrf" rel="noopener noreferrer" target="_blank">International Medical Device Regulators Forum</a>. SaMD is supposed to be regulated by public health agencies such as the U.S. <a href="https://www.fda.gov/" rel="noopener noreferrer" target="_blank">Food and Drug Administration</a>, but the apps have developed and grown in popularity so quickly that regulators haven’t been able to keep up, Quintana says. Some companies have received approval, but most have not, he says.</p><p>Many users are unaware of the regulatory gap, he says.</p><p>“Seeing an app from a well-known company often creates the impression that it has been meaningfully vetted for safety and efficacy, even when that is not the case,” he says.</p><p>Some companies are using deceptive advertising to sell their product, he adds. Marketing materials might claim that all of a company’s health apps are certified, even though only one app has been approved by a regulatory body to treat a particular condition. Or the verbiage might imply the company has clinical evidence proving its application works, even though the app has never been tested independently.</p><p>Another concern is that updated apps aren’t being vetted, says <a href="https://www.linkedin.com/in/mpalombini/" rel="noopener noreferrer" target="_blank">Maria Palombini</a>, IEEE SA’s director of health care and life sciences global practice lead.</p><p>“The original app might have received approval from a regulatory agency, but not the updated version,” Palombini says. “There could have been significant changes from the original.”</p><p>“Not every medical-related app triggers the same regulatory classification or review across jurisdictions,” Quintana adds. “That leaves a large gray zone of clinically relevant but lower-risk apps that haven’t undergone an independent assessment. The IEEE registry was created to help fill these gaps.</p><p>“IEEE is the best organization to address this problem because this is fundamentally a standards, trust, interoperability, and conformity assessment challenge,” he says. IEEE “is the world’s largest technical professional organization, with deep expertise in developing globally recognized standards including in <a href="https://spectrum.ieee.org/ieee-standard-biomedical-devices-data" target="_self">health care</a>, <a href="https://standards.ieee.org/initiatives/cybersecurity-standards-projects/" rel="noopener noreferrer" target="_blank">cybersecurity</a>, <a href="https://spectrum.ieee.org/two-new-ai-ethics-certifications" target="_self">AI ethics</a>, and <a href="https://standards.ieee.org/ieee/1547/5915/" rel="noopener noreferrer" target="_blank">interoperability</a>.”</p><p>“Through the <a href="https://standards.ieee.org/products-programs/icap/" rel="noopener noreferrer" target="_blank">IEEE Conformity Assessment Program</a>, we already run rigorous assessment and registry programs,” Palombini says. “Our neutral, consensus-driven, multidisciplinary approach—bringing together clinicians, regulators, developers, and ethicists without commercial bias—makes IEEE uniquely positioned to create trustworthy global guardrails that can scale across jurisdictions and support regulatory harmonization.”</p><h2>How the registry works</h2><p>The assessment framework was developed by a multidisciplinary group of 35 volunteer experts from 10 countries, Quintana says. The panel includes academics, AI experts, app developers, clinicians, ethicists, mental health experts, patient advocates, regulators, researchers, technologists, and those who assess safety in health care.</p><p>The registry is for any app used for clinical care or therapeutics that claims to demonstrate a medical benefit. That includes apps designed for cardiology, diabetes, mental health, neurology, oncology, rehabilitation, and respiratory diseases, Quintana says.</p><p>Initially, he says, the focus will be on apps that aim to treat mental health conditions, given the large number of offerings in that area and the registry committee’s expertise.</p><p>The submission of apps is voluntary. There is no government mandate that requires a company to use the IEEE registry.</p><p>The products will be evaluated against about 150 consensus-based criteria across three major areas: </p><ul><li><strong>Clinical efficacy</strong> including therapeutic effectiveness, any sustained benefits, risk management, comparison to standard care, user engagement, and real clinical value.</li><li><strong>Technical soundness</strong> including accessibility, privacy and security, error handling, interoperability, AI governance, usability, and operational quality.</li><li><strong>Ethical design</strong> including bias prevention, patient consent, data governance, conflict-of-interest transparency, responsible use of AI and large language models, and prioritization of public health benefits.</li></ul><p>IEEE charges a nonrefundable submission fee that covers the cost of the assessment plus the registry’s annual subscription for the first year.</p><p>Developers first must demonstrate they are a legally established entity before they can complete the <a href="https://forms.zohopublic.com/healthappregistryie1/form/AppPublisherRegistrationForm/formperma/vKV62XuzwMV6hoOZnUv3QiFo8BDLpUSFp2CZlOOIOyM" rel="noopener noreferrer" target="_blank">app publisher registration form</a> and then submit documentation and attestations about the product.</p><p>The IEEE review of an app is estimated to take six to eight weeks, Palombini says. The assessment results will be privately shared with the app publisher, she says, and to be listed in the registry, an app must achieve more than 85 percent compliance in each category.</p><p>Upgraded apps must be submitted and reassessed, Palombini says. Similar to how users are notified when an app on their smart devices has , the registry will be notified when listed apps have a new update available, she says.</p><p>Applicants who do not pass the assessment are to receive feedback explaining why. They will be given an opportunity to make changes or provide additional documentation, Palombini says.</p><p>“It’s a pretty methodological process, with checks and balances,” Quintana says. “We’re being very transparent about the process.”</p><p>Approved apps added to the registry receive an IEEE certification badge and submission identifier, which the company can display on its website, app store listings, and marketing materials.</p><p>“The badge serves as visible proof that the app has met the independent, consensus-based assessment for clinical value, technical robustness, and ethical design,” Quintana says.</p><p>The registry will be publicly available at no cost, he says.</p><p>Patients and families seeking safe, trustworthy apps—and payers and insurers evaluating reimbursement potential—will find the registry helpful, he says.</p><p>The <a href="https://forms.zohopublic.com/healthappregistryie1/form/AppPublisherRegistrationForm/formperma/vKV62XuzwMV6hoOZnUv3QiFo8BDLpUSFp2CZlOOIOyM" rel="noopener noreferrer" target="_blank">application website</a> is open. The public registry page does not yet list a specific count of approved apps because assessments are ongoing. Approved apps and their unique identifiers are to be published when the initial reviews are completed.</p><p>To learn more, you can watch a <a href="https://engagestandards.ieee.org/medical-app-registry-webinar.html?_gl=1*1bfk6ug*_gcl_au*MTcwMjc4NjczMy4xNzc2Mjc4MzQy*_ga*MTE2MjkxMjYxMC4xNzc2Mjc4MzQy*_ga_XDL2ME6570*czE3NzgwOTUwNTIkbzIzJGcxJHQxNzc4MDk1ODUzJGo2MCRsMCRoMA.." rel="noopener noreferrer" target="_blank">webinar</a> recorded in March.</p>The assessment framework that underpins the registry is supporting the formal recognition of <a href="https://standards.ieee.org/products-programs/icap/mobile-health-app-registry/" rel="noopener noreferrer" target="_blank">IEEE P3962 Standard for Criteria Assessment Framework f</a> Reference: https://ift.tt/qEG0YX2

A hacker group is poisoning open source code at an unprecedented scale


<p>A so-called software <a href="https://www.wired.com/story/the-untold-story-of-solarwinds-the-boldest-supply-chain-hack-ever/">supply chain attack</a>, in which hackers corrupt a legitimate piece of software to hide their own malicious code, was once a relatively rare event but one that haunted the cybersecurity world with its insidious threat of turning any innocent application into a dangerous foothold in a victim’s network. Now <a href="https://www.wired.com/story/meta-pauses-work-with-mercor-after-data-breach-puts-ai-industry-secrets-at-risk/">one group of cybercriminals</a> has turned that occasional nightmare into a near-weekly episode, corrupting hundreds of open source tools, extorting victims for profit, and sowing a new level of distrust in an entire ecosystem used to create the world’s software.</p> <p>On Tuesday night, open source code platform GitHub announced that it had been breached by hackers in one such software supply chain attack: A GitHub developer had installed a “poisoned” extension for VSCode, a plug-in for a commonly used code editor that, like GitHub itself, is owned by Microsoft. As a result, the hackers behind the breach, an increasingly notorious group called TeamPCP, claim to have accessed around 4,000 of GitHub’s code repositories. GitHub’s statement confirmed that it had found at least 3,800 compromised repositories while noting that, based on its findings so far, they all contained GitHub’s own code, not that of customers.</p> <p>“We are here today to advertise GitHub’s source code and internal orgs for sale,” TeamPCP wrote on BreachForums, a forum and marketplace for cybercriminals. “Everything for the main platform is there and I very am happy to send samples to interested buyers to verify absolute authenticity.”</p><p><a href="https://arstechnica.com/information-technology/2026/05/a-hacker-group-is-poisoning-open-source-code-at-an-unprecedented-scale/">Read full article</a></p> <p><a href="https://arstechnica.com/information-technology/2026/05/a-hacker-group-is-poisoning-open-source-code-at-an-unprecedented-scale/#comments">Comments</a></p> Reference : https://ift.tt/AIiVDKc

Thursday, May 21, 2026

US government takes $2 billion equity stake in nine quantum computing firms


<p>The US government will take equity stakes worth a total of $2 billion in a slew of quantum computing companies, including a startup backed by a firm with links to the Trump family and one taken public by a Pentagon official.</p> <p>The announcement by the commerce department that it had signed letters of intent with nine companies—including GlobalFoundries and IBM—sent shares in quantum specialists soaring on Thursday.</p> <p>Both IBM, which is set to get $1 billion, and GlobalFoundries, which will receive $375 million, were up more than 6 percent in pre-market trading. D-Wave Quantum, an awardee that was taken public in 2022 by Emil Michael—now a top Pentagon official—was up more than 20 percent.</p><p><a href="https://arstechnica.com/gadgets/2026/05/us-government-takes-2-billion-equity-stake-in-nine-quantum-computing-firms/">Read full article</a></p> <p><a href="https://arstechnica.com/gadgets/2026/05/us-government-takes-2-billion-equity-stake-in-nine-quantum-computing-firms/#comments">Comments</a></p> Reference : https://ift.tt/zFUTfNL

SEM-Guided Low-kV FIB Finishing for Leading-Edge Semiconductor Failure Analysis


<img src="https://spectrum.ieee.org/media-library/zeiss-logo-above-the-slogan-seeing-beyond-on-a-dark-curved-rectangle.png?id=66728517&width=980"/><br/><br/><p>Discover how the ZEISS Crossbeam 750 FIBSEM sets a new benchmark for precise TEM lamella prep, tomography, and advanced nanofabrication. This delivers better resolution, better SNR, larger usable FOV, and shorter acquisition times. Learn how uninterrupted FIB milling will reduce damage and rework, accelerate time to TEM, and increase first pass success—so your FA, yield, and materials teams make faster, confident data driven decisions.</p><p><span>Join us to discover how the new ZEISS Crossbeam 750 with its see while you mill capability delivers precision and clarity—every time—for demanding FIB-SEM workflows. </span>Designed for extremely challenging TEM lamella preparation, tomography, advanced nanofabrication, and APT‑ready lift‑out, Crossbeam 750 combines a new Gemini 4 SEM objective lens, a double deflector, and a next‑generation scan generator to elevate both image quality and process confidence. You’ll learn how better resolution and better SNR translate into more image detail and shorter acquisition times, while the low‑kV FIB performance enables more precise lamella prep.</p><p>We’ll demonstrate High Dynamic Range (HDR) Mill + SEM—an interwoven SEM/FIB scanning mode that suppresses FIB‑generated background. This enables immediate, clean visual feedback, even during nudging the FIB pattern live while milling . The result: confident endpointing with uninterrupted FIB milling and pristine, metrology‑grade surfaces with the lowest possible sample damage. </p><p><span><span>This session is ideal for semiconductor failure analysists, yield teams and materials scientists seeking faster time‑to‑TEM, higher first‑pass success, and consistent outcomes at low kV. See how Crossbeam 750 empowers you to make earlier stop‑milling decisions, cut rework, and reliably plan turnaround time—so you can move from sample to insight with confidence.</span></span></p><p><span><span></span><a href="https://events.bizzabo.com/868497/home" target="_blank">Register now for this free webinar!</a></span></p> Reference: https://events.bizzabo.com/868497/home

Wednesday, May 20, 2026

Google publishes exploit code threatening millions of Chromium users


<p>Google on Wednesday published exploit code for an unfixed vulnerability in its Chromium browser codebase that threatens millions of people using Chrome, Microsoft Edge, and virtually all other Chromium-based browsers.</p> <p>The proof-of-concept code exploits the Browser Fetch programming interface, a standard that allows long videos and other large files to be downloaded in the background. An attacker can use the exploit to create a connection for monitoring some aspects of a user’s browser usage and as a proxy for viewing sites and launching denial-of-service attacks. Depending on the browser, the connections either reopen or remain open even after it or the device running it has rebooted.</p> <h2>Unfixed for 29 months (and counting)</h2> <p>The unfixed vulnerability can be exploited by any website a user visits. In effect, a compromise amounts to a limited backdoor that makes a device part of a limited botnet. The capabilities are limited to the same things a browser can do, such as visit malicious sites, provide anonymous proxy browsing by others, enable proxied DDoS attacks, and monitor user activity. Nonetheless, the exploit could allow an attacker to wrangle thousands, possibly millions, of devices into a network. Once a separate vulnerability becomes available, the attacker could use it to then compromise all those devices.</p><p><a href="https://arstechnica.com/security/2026/05/google-publishes-exploit-code-threatening-millions-of-chromium-users/">Read full article</a></p> <p><a href="https://arstechnica.com/security/2026/05/google-publishes-exploit-code-threatening-millions-of-chromium-users/#comments">Comments</a></p> Reference : https://ift.tt/Pj3Nyid

Will Robotics Have a ChatGPT Moment?


<img src="https://spectrum.ieee.org/media-library/a-collection-of-5-robots-against-colored-backgrounds.jpg?id=66734221&width=1245&height=700&coordinates=0%2C88%2C0%2C88"/><br/><br/><p>Over the next few decades, billions of autonomous, AI-powered robots will work alongside people in factories, perform tedious tasks in warehouses, care for the elderly, <a href="https://spectrum.ieee.org/collections/darpa-subterranean-challenge/" target="_blank">assist in unsafe disaster areas</a>, deliver packages and food to our doorsteps, and eventually, help out in our homes. Some will look like us, and many won’t. What is certain is that regardless of form factor, robots will all rely heavily on AI in order to deliver real-world value.</p><div class="rm-embed embed-media"><iframe height="110px" id="noa-web-audio-player" src="https://embed-player.newsoveraudio.com/v4?key=q5m19e&id=https://spectrum.ieee.org/robotics-ai-breakthrough?draft=1&bgColor=F5F5F5&color=1b1b1c&playColor=1b1b1c&progressBgColor=F5F5F5&progressBorderColor=bdbbbb&titleColor=1b1b1c&timeColor=1b1b1c&speedColor=1b1b1c&noaLinkColor=556B7D&noaLinkHighlightColor=FF4B00&feedbackButton=true" style="border: none" width="100%"></iframe></div><p><span>In 2025, total investments in robotics companies reached </span><a href="https://www.cbinsights.com/research/report/venture-trends-2025/" target="_blank">a record $40.7 billion, accounting for 9 percent of all venture funding</a><span>. The multibillion dollar question therefore is this: What will it take for AI-powered robots to begin to have a serious economic impact? Many of today’s robotics and AI companies are making bold claims, such as that humanoid robots will </span><a href="https://www.1x.tech/" target="_blank">soon be coming into our homes</a><span>, but there’s still a big gap between promise and reality.</span></p><p><span></span><span>The promise of robots that live and work alongside us has been the stuff of science fiction for a very long time. And while many programmers have tried to make that promise a reality, the physical world is just too complicated for traditional computer programs to handle the endless complexity it presents. Thanks to AI, robots are no longer being programmed—instead, they learn to operate in the real world. With enough practice, they can learn to perceive and understand the world around them, reason about that world, and use that reason and understanding to perform tasks that are useful, reliable, and safe.</span></p><p>The two of us have worked at the forefront of AI and robotics for the last decade, as a <a href="https://engineering.oregonstate.edu/people/jonathan-hurst" target="_blank">Professor in Robotics at Oregon State University</a> and <a href="https://www.agilityrobotics.com/about/leadership" rel="noopener noreferrer" target="_blank">Co-Founder of Agility Robotics</a>, and as <a href="https://www.linkedin.com/in/hanspeter/" rel="noopener noreferrer" target="_blank">former CEO</a> of the <a href="https://everydayrobots.ai/" rel="noopener noreferrer" target="_blank">Everyday Robots moonshot at Google X</a>. Our experience deploying AI-powered robots in real-world settings has given us a perspective on where AI can be used to great benefit in complex robotic systems in the near term, and where we are still on the frontier of science fiction. We believe AI will enable an inflection point in robotics advances, but that it will be through the well-engineered application of coordinated systems of different AI tools rather than a single ChatGPT-style breakthrough.</p><p>As the excitement around AI is matched only by the uncertainty of what will be possible, here are five hard truths that will define AI in robotics.</p><h2>1. The YouTube-to-Reality Gap Is Real</h2><p>For years we have been seeing videos on YouTube with humanoid robots performing amazing moves on everything from a dance floor to an obstacle course. The inside knowledge in robotics is to “never trust a YouTube robot video.” The gap between real robots that can perform real work in unstructured human environments and carefully scripted and edited robot performances remains significant. The latest performance to get a lot of attention was a <a href="https://www.youtube.com/watch?v=mUmlv814aJo" rel="noopener noreferrer" target="_blank">martial arts show</a> featuring Unitree humanoid robots performing with children at the Chinese 2026 Spring Festival Gala. While impressive, this falls into a long lineage of tightly scripted robotic performances, where everything has been carefully choreographed and planned in advance. The low-level controls, synchronization, and choreography were stunning, yet the Spring Gala robot performance showed a level of autonomy and intelligence much closer to industrial robots building cars in a factory than something that will show up in your living room any time soon. </p><p class="shortcode-media shortcode-media-youtube"> <span class="rm-shortcode" data-rm-shortcode-id="d5c524bfa673932ad736d1599aad9c93" style="display:block;position:relative;padding-top:56.25%;"><iframe frameborder="0" height="auto" lazy-loadable="true" scrolling="no" src="https://www.youtube.com/embed/mUmlv814aJo?rel=0" style="position:absolute;top:0;left:0;width:100%;height:100%;" width="100%"></iframe></span> </p><p><span>Seeing these kinds of demos nevertheless raises questions about where robotics really is. If robots can perform kung fu moves and do backflips and dance, why aren’t they also showing up on factory floors yet? And why can’t they do the dishes in my home after dinner? The simple answer is this: Making AI-powered robots capable of performing general tasks in varied human environments is still </span><em><em>really</em></em><span> hard. While impressive technological feats like those at the Spring Festival may make it look like we could be very close, the use of AI in these demos is only for low-level motor control (to keep the robots from falling over) and therefore is only a small part of the solution for robots to be general purpose in the real, unstructured spaces where we humans live and work.</span></p><h2>2. Data Is An Unsolved Challenge</h2><p>Large Language Models like OpenAI’s ChatGPT and Anthropic’s Claude were initially trained on an internet-scale database of text. The world woke up one day in late 2022 to ChatGPT demonstrating that AI computers could suddenly “speak” to us in prose or verse and about seemingly any topic. LLMs have turned out to generalize well and are now able to take multimodal input (text, images, video) and produce multimodal output. Importantly, the corpus of training data was both enormous and human-generated, which are characteristics that form the gold standard for AI training.</p><p class="shortcode-media shortcode-media-rebelmouse-image rm-float-left rm-resized-container rm-resized-container-25" data-rm-resized-container="25%" style="float: left;"> <img alt="A series of four images, including robots working in a contained factory space, in an open indoor factory, outdoors in the real world delivering a package, and working with a human to move a couch in an apartment." class="rm-shortcode" data-rm-shortcode-id="f8dd8681a93fee0b55cfebeab420789a" data-rm-shortcode-name="rebelmouse-image" id="a0903" loading="lazy" src="https://spectrum.ieee.org/media-library/a-series-of-four-images-including-robots-working-in-a-contained-factory-space-in-an-open-indoor-factory-outdoors-in-the-real.jpg?id=66734272&width=980"/> <small class="image-media media-caption" placeholder="Add Photo Caption...">The fastest path to robots as part of everyday life may emerge through a range of robot forms performing increasingly sophisticated applications and employing a range of AI tools.</small><small class="image-media media-photo-credit" placeholder="Add Photo Credit...">Agility Robotics</small></p><p>Giving AI a body (in the form of a robot) so that it can engage with people in the physical world continues to be a very difficult and broadly unsolved problem. AI models for general-purpose robotics must simultaneously satisfy multiple, often conflicting, physical, geometric, and temporal limitations while operating in unstructured, dynamic environments. In order to generalize, robot models need to be trained on data gathered in a high-dimensional configuration space, where “dimensions” represent text, lighting conditions, degrees of freedom, joint limits, velocities, force, and safety boundaries, just to mention a few. Importantly, this must be <em><em>good</em></em> data—it must contain many examples from what amounts to an infinite number of possible configurations in the physical world.</p><p>Since there are very few existing sources of data like this, approaches like teleoperation, video analysis, motion capture of humans, and self-exploration in simulation and in the real world are all seen as important ways to collect data. It’s a Herculean task. For example, at Everyday Robots at Google X, we ran 240 million robot instances in our simulator over the course of 2022 to collect training data, mostly to train a trash-sorting model. Similar amounts of data will be needed for every skill, to get to a similar level of capability, which is not yet human level.</p><h2>3. There Will Be No Single Robot AI</h2><p>We are far away from a moment where a single AI model might allow general-purpose robots to live and work alongside us. </p><p>General-purpose robots can have wheels or legs. They can have one, two, three, or more arms. Some have propellers and can fly, while others may be designed to operate under water. Some will drive on busy roads. The physical world is infinitely varied and complex. And then there are all the people and other animals that will be surrounding the robots. How do you train a model to operate a robot safely and reliably in all of these settings? The simple answer is, You don’t. At least not for quite some time.</p><p>We believe the winning AI architecture leading to the next big breakthroughs in general-purpose robotics will be “agentic AI” for robots, which are high-level coordinating models that can reason, plan, use tools, and learn from outcomes to execute complex tasks with limited supervision. Agentic, high-level models running on robots will invoke a system of specialized ones for different types of tasks. We will likely soon see multiple robots collaborating and coordinating with each other through their on-board agentic AI models.</p><p>AI tools are unlocking new and powerful capabilities in robotics, which in turn will enable new solutions and new markets. It’s encouraging to see these new models being made broadly available, some even as open-source solutions. This availability is akin to what happened with the internet: Real progress occurred when it became ubiquitous. We anticipate an inevitable democratization of complex behaviors in robotics with wide access to these AI tools and technologies.</p><h2>4. Hardware Is Still Very Hard</h2><p>Robots are complex systems with many parts that all need to work together with great precision. For a robot to be useful and safe, every part of it must be coordinated, from its perception systems, to the computer controlling it, all the way down to its individual actuators.</p><p>Actuators—that is, the motors and gears—are a good example of an important part of the robot where what got us here won’t get us there. The actuators used at scale by most industrial robots will not work for robots that will operate in human environments. If these robots accidentally collide with an obstacle, the resulting impacts are harsh, forces are high, and things break. Humans don’t move in this way. We are far more compliant in how we interact with the world, and we’re constantly making contact with our environment and using that contact to help us accomplish things. </p><p>Consider the challenge of inserting a key in a lock: Humans typically don’t do this by aligning the key perfectly with the keyhole. Instead, we just feel for the edge of the keyhole and jiggle the key in. Robots need to be able to operate in novel ways to achieve comparable capabilities by using a new class of actuators that are sensitive to force and able to have a compliant interaction with the environment. While these kinds of actuators do exist, they are not yet generally available at scale for robot systems designed to operate around people.</p><h2>5. Real Value Comes From “Easy” Tasks</h2><p>There’s a big difference between tasks that look impressive and real-world tasks that provide value. Robotics is a perfect example of <a href="https://en.wikipedia.org/wiki/Moravec%27s_paradox" target="_blank">Moravec’s paradox</a>, which states that tasks that are hard for humans are easy for computers (like multiplying two big numbers), and tasks easy for humans (like a toddler’s movements) are extremely difficult for computers and robots.</p><p>Serving customers is an unforgiving reality check, because customers only care about solving the real problems they have. If we are to deploy AI-based robot solutions, they must outperform the way things are currently done, while demonstrating reliable performance metrics and safety. Agility Robotics’ early work to deploy our humanoid robot Digit in customer locations led to the realization that our first obstacle was safety: Robots that balance and manipulate objects in human spaces bring new types of risk to the workplace. In the first <a href="https://www.youtube.com/watch?v=AJpTpUqjgrY" target="_blank">humanoid deployments</a>, physical barriers were necessary, and Agility kicked off a multi-year engineering effort to solve the safety challenge, touching nearly every aspect of robot design and relying heavily on new AI-based approaches to human detection and behavior control.</p><p class="shortcode-media shortcode-media-youtube"> <span class="rm-shortcode" data-rm-shortcode-id="2e10035a69200933f1594941bc6121ce" style="display:block;position:relative;padding-top:56.25%;"><iframe frameborder="0" height="auto" lazy-loadable="true" scrolling="no" src="https://www.youtube.com/embed/E2g1APtSuUM?rel=0" style="position:absolute;top:0;left:0;width:100%;height:100%;" width="100%"></iframe></span> </p><p><a href="https://everydayrobots.ai/vision" target="_blank">Everyday Robots</a> at Google deployed robots in 2019 that worked autonomously in office buildings doing chores like cleaning cafe tables and sorting trash. We quickly learned how “messy” and difficult the real world is for a robot. This experience informed the architecture and deployment of our AI systems while also gathering real-world data that could be combined with simulation data for training and improving models.</p><p>This focus on creating a product to meet specific customer needs and deploying robots in real-world settings is the only way to inform the structure of the AI tools and infrastructure for near-term utility on a path towards long-term broader capability and generality. There will be no “aha” moment, no silver bullet algorithm, and no volume of data sufficient to produce a general-purpose robot without extensive real-world experience. </p><h2>AI Robots Are Coming, One Step at a Time</h2>As we look to the future, there is no doubt that the world is bringing AI into the physical world through robots. We are at the beginning of a “<a href="https://spectrum.ieee.org/is-a-cambrian-explosion-coming-for-robotics" target="_self">Cambrian explosion</a>“ of useful, intelligent machines. We believe AI is not one tool, but a huge frontier of technical approaches that is unlocking new capabilities so powerful, they will define our economy moving forward. This will happen not in one single definitive moment, but as an ongoing set of small and large breakthroughs, where AI-driven robots begin to provide real value in a few tasks, and then a few more, with impacts unfolding across numerous $100 billion-plus markets that will dramatically improve the quality of our lives. Reference: https://ift.tt/vrcMzAg

Texas AG sues Meta over claims that WhatsApp doesn't provide end-to-end encryption

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