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Googles latest Pixel 10 phones, which were just announced today, dont come with many external physical changes. The most tangible hardware addition across the lineup, in fact, is completely invisible: a set of magnets beneath the phones back panels. With the new Pixelsnap system, Google is the first major Android manufacturer to finally catch up to Apples MagSafe. Apple launched its magnetic wireless charging system on the iPhone 12 range in 2020, and its quietly become one of the best things about using an iPhone. MagSafe has enabled a whole range of accessories and use cases that let you keep your phone powered up without having to mess around with cables, whether youre using a slimline portable magnetic battery or a charger plugged into your car. Its one of those things thats hard to go without once youre used to itand I feel it almost every day as someone who constantly bounces back and forth between iOS and Android. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/multicore_logo.jpg","headline":"Multicore","description":"Multicore is about technology hardware and design. It's written from Tokyo by Sam Byford. To learn more visit multicore.blog","substackDomain":"https:\/\/www.multicore.blog","colorTheme":"green","redirectUrl":""}} With Pixelsnap, Google is finally bringing Android up to speed. It works with the Qi2 standard, allowing for fast wireless charging at up to 25W on the Pixel 10 Pro XL, or up to 15W on the Pixel 10, 10 Pro and 10 Pro Fold. Google is selling a $39.99 Pixelsnap charging puck that looks similar to Apples MagSafe equivalent and can be slotted into a vertical charging stand. Theres also a Ring Stand attachment that doesnt provide any power but uses the same magnets to provide a handy kickstand that can prop your phone up in landscape or portrait mode. This is great news for Pixel fansor at least new Pixel buyerswholl now be able to see what the MagSafe hype was all about. Qi2 is backwards-compatible with MagSafe, in fact, since Apple itself contributed to the standard, so a huge range of accessories designed for iPhones will now work with Pixel phones as well. What took so long? That raises an obvious question, though: what exactly took so long, given that Qi2 launched in 2023 and is an open standard based on existing technology that anyone can use? Even before Qi2, it seemed inevitable that Android phone makers would rush to follow Apple. Chinese brand Realme was the first, announcing its own proprietary solution called MagDart in 2021. The technology did workthe company even sent me prototype chargers and a compatible phonebut it never launched on any commercial devices. More recently HMD, perhaps best known for taking on the Nokia brand, released a niche phone called the Skyline that appears to be the only true Qi2 magnet-equipped device on the market. I say true Qi2 because a lot of phones, for example Samsungs current flagship Galaxy S25, are certified as Qi2 Ready without actually having the magnets in place. What this really means is that itll work with Qi2 chargers if you buy a compatible case, which is also true of any Qi phonealbeit potentially at slower speeds. Im not a hardware engineer so I dont presume to understand the challenges here, but it doesnt seem like including Qi2 magnets necessarily requires making major compromises on industrial design. The Pixel 10 and 10 Pro are just 0.1mm thicker than their predecessors, while the 10 Pro XL has kept the same thickness. Each phone has gained a few grams in weight, but they also all have bigger batteries. Part of the issue might have been that no one was willing to jump in first. Most Android hardware innovation comes from Chinese manufacturers these days, but wireless charging has historically not been as important in their home market. High-end Chinese phones only started adopting Qi as a standard around 2021 or so, and companies like Oppo and Huawei remained more focused on pushing their ultra-fast wired charging solutions. While nowadays every Chinese flagship has fast wireless charging built in, they also all require proprietary accessories that dont support Qi2. But even if that really was a factor, I have no idea what Samsungs excuse is. The Qi2 Ready Galaxy S25 Ultra only supports 15W wireless charging, and Samsung hasnt invested in a proprietary system of its own. Its inexplicable that the most dominant brand in the US market hasnt kept up here. A return to best practices My hope is that Pixelsnap sees Google return to the role it once played in the Android ecosystem. Before the Pixel line, Googles Nexus devicesproduced in partnership with other OEMsserved as examples of best practices for manufacturers to adopt. They werent always the flashiest of products, but coupled with Googles understated yet definitive take on Android software, they tended to provide the most user-friendly experience. Magnetic wireless charging is all about the user experience. Its not something that necessarily excites power users by reading about it on a spec sheet, but it can help you fit your phone into your life in a more natural, less messy way. With any luck, Pixelsnap will be the catalyst for other Android phone makers to get on board. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/multicore_logo.jpg","headline":"Multicore","description":"Multicore is about technology hardware and design. It's written from Tokyo by Sam Byford. To learn more visit multicore.blog","substackDomain":"https:\/\/www.multicore.blog","colorTheme":"green","redirectUrl":""}}
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People rely on data from federal agencies every day often without realizing it. Rural residents use groundwater level data from the U.S. geological surveys National Water Information System to decide where to dig wells. High school coaches turn to weather apps supported by data from the National Weather Service to decide when to move practice inside to avoid life-threatening heat. Emergency managers use data from the Census Bureaus American Community Survey to ensure that residents without vehicles have seats on evacuation buses during local emergencies. On Jan. 31, 2025, websites and datasets from across the federal government began to disappear. As that happened, archivists and researchers from around the world sprang into action, grabbing what they could before it was gone. Trust in the federal statistical system took another hit when Bureau of Labor Statistics Commissioner Erika McEntarfer was fired on the heels of a dismal Aug. 1, 2025, employment report. And reduced data collection at the bureau was already causing concern before her dismissal. The bureau has ceased collection of critical inputs to the Consumer Price Index, likely reducing that inflation indicators accuracy, especially at the level of specific locations and products. As researchers of economics and epidemiology at the University of Michigan, we have spent years working with data, often from the federal government. When data and information began to disappear, we were spurred into action to preserve these important public goods. The Inter-university Consortium for Political and Social Research, where we work commonly known as ICPSR has been making data from governments and researchers available for more than 60 years. We are stewards of this data, preserving it and ensuring that it is accessible in a safe and responsible manner. Unfortunately, government data is now at risk of becoming less available or disappearing. But there are steps that researchers and the public can take to reduce that risk. Data at risk Some 8,000 pages were removed from federal websites within a few days of Jan. 31, 2025. Though many were soon restored following substantial outcry and some court orders, its still unclear how the restored webpages and datasets may have been changed. In one preliminary examination, researchers found that 49% of the 232 datasets they reviewed had been substantially altered, including the replacement of the word gender with sex. This alteration can obscure nonbinary gender identities. Only 13% of the changes the researchers found were documented by the government. U.S. government data has also become less accessible because of mass firings of federal workers and the dismantling of entire agencies. Important efforts like the Data Rescue Project and the Internet Archive have been able to preserve a great deal of knowledge and data, but they are mostly limited to publicly available data and information. No one left to vet data Many important government data resources contain sensitive or identifying information. This means officials must vet requests before they grant access to data rescue efforts. But many agencies have had their ability to conduct vetting and manage access severely curtailed and, in some cases, eliminated altogether. Take the Pregnancy Risk Assessment Monitoring System, which provides key data on maternal and child health from around the United States. The Centers for Disease Control and Prevention integrates data collected at state and local levels and adds population information to come up with estimates. While some of this data is publicly available, access to most data from 2016 and later requires a request to the CDC and a signed data use agreement. At the start of 2025, multiple researchers reported to our team at the Inter-university Consortium for Political and Social Research that the CDC had stopped processing these requests. In February, researchers discovered that the Pregnancy Risk Assessment Monitoring System would be discontinued. The CDC suggested that data collection would restart at some point. But on April 1, the entire Pregnancy Risk Assessment Monitoring System team was laid off. This made one of the most valuable sources of data on the health of mothers and babies largely inaccessible, and put plans for its future in limbo. Similar situations have played out at other agencies, including the dismantled U.S. Agency for International Development and the National Center for Education Statistics. Data collected, cleaned and harmonized using taxpayer dollars is now languishing on inaccessible servers. Inaccessible data The portal that researchers use to apply for access to restricted federal statistical data now includes a list of data that researchers can no longer access. Some organizations are leadig efforts to restore access to particular datasets. The Inter-university Consortium for Political and Social Research, for instance, has an agreement with USAID to preserve and provide access to USAIDs education data. Unfortunately, these efforts barely scratch the surface. With very few staff left, there isnt a clear estimate of which other USAID resources remain inaccessible. According to our count, 354 restricted datasets from the federal statistical systems Standard Application Portal have become unavailable due to firings, layoffs and funding cuts. Data is critical for people and the state and local governments that represent them to make good decisions. Federal data is also used for oversight, so that researchers can verify that the government is doing what its supposed to in accordance with its congressionally mandated missions. Government efficiency requires accountability. And accountability requires high-quality and timely data on operations. The mass firings of federal employees means that those tasked with ensuring this accountability are doing so while struggling to obtain necessary data. So where do we go from here? While the pace of intentional government data removal appears to have slowed, it hasnt stopped. New datasets under threat of disappearing are being rescued daily. Restructured federal agencies and related changes to or neglect of official websites can make data difficult or impossible to find. What you can do If you identify data that is at risk, perhaps because its collection has been discontinued or it covers a controversial topic, you can report your observations to the Data Rescue Project, a grassroots effort of archivists, librarians and other concerned people. The Data Rescue Project has been working for months to identify data and preserve government data, including in the Inter-university Consortium for Political and Social Researchs DataLumos open-access archive. Similarly, the Public Environmental Data Partners, a coalition of nonprofits, archivists and researchers, are preserving federal environmental data and have a nomination form. Efforts to identify restored data that has been altered are also gaining steam. Dataindex tracks Federal Register notices that describe proposed changes to 24 widely used datasets from across the federal government, including the American Community Survey from the Census Bureau, the National Crime Victimization Survey from the Bureau of Justice Statistics, and the National Health Interview Survey from the CDC. The website also facilitates comment on proposed alterations. You can help researchers understand the scale of data alterations that have been, and continue to be, made. If you notice changes in public datasets, you can share that information with the American Statistical Associations FedStatMonitoring project. The Inter-university Consortium for Political and Social Research is continuing our efforts to ensure the preservation of, and access to, existing data, including from the Bureau of Labor Statistics and the Consumer Financial Protection Bureau. At the same time, we and other groups are planning future efforts in data collection to avoid gaps in our knowledge. The federal statistical system is both large and complex, including hundreds of thousands of datasets that people depend on in many ways, from weather forecasts to local economic indicators. If the federal government continues to step back from its role as a provider of high-quality, trusted data, others including state and local governments, academia, nonprofits and companies may need to fill the gap by stepping up to collect it. Margaret Levenstein is a research professor at the Institute for Social Research at the University of Michigan. John Kubale is a research assistant professor at the Institute for Social Research at the University of Michigan. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Despite two centuries of evolution, the structure of a modern military staff would be recognizable to Napoleon. At the same time, military organizations have struggled to incorporate new technologies as they adapt to new domainsair, space and informationin modern war. The sizes of military headquarters have grown to accommodate the expanded information flows and decision points of these new facets of warfare. The result is diminishing marginal returns and a coordination nightmaretoo many cooks in the kitchenthat risks jeopardizing mission command. AI agentsautonomous, goal-oriented software powered by large language modelscan automate routine staff tasks, compress decision timelines and enable smaller, more resilient command posts. They can shrink the staff while also making it more effective. As an international relations scholar and reserve officer in the U.S. Army who studies military strategy, I see both the opportunity afforded by the technology and the acute need for change. That need stems from the reality that todays command structures still mirror Napoleons field headquarters in both form and functionindustrial-age architectures built for massed armies. Over time, these staffs have ballooned in size, making coordination cumbersome. They also result in sprawling command posts that modern precision artillery, missiles and drones can target effectively and electronic warfare can readily disrupt. Russias so-called Graveyard of Command Posts in Ukraine vividly illustrates how static headquarters where opponents can mass precision artillery, missiles and drones become liabilities on a modern battlefield. The role of AI agents Military planners now see a world in which AI agentsautonomous, goal-oriented software that can perceive, decide and act on their own initiativeare mature enough to deploy in command systems. These agents promise to automate the fusion of multiple sources of intelligence, threat-modeling, and even limited decision cycles in support of a commanders goals. There is still a human in the loop, but the humans will be able to issue commands faster and receive more timely and contextual updates from the battlefield. These AI agents can parse doctrinal manuals, draft operational plans and generate courses of action, which helps accelerate the tempo of military operations. Experimentsincluding efforts I ran at Marine Corps Universityhave demonstrated how even basic large language models can accelerate staff estimates and inject creative, data-driven options into the planning process. These efforts point to the end of traditional staff roles. There will still be peoplewar is a human endeavorand ethics will still factor into streams of algorithms making decisions. But the people who remain deployed are likely to gain the ability to navigate mass volumes of information with the help of AI agents. These teams are likely to be smaller than modern staffs. AI agents will allow teams to manage multiple planning groups simultaneously. For example, they will be able to use more dynamic red teaming techniquesrole-playing the oppositionand vary key assumptions to create a wider menu of options than traditional plans. The time saved not having to build PowerPoint slides and updating staff estimates will be shifted to contingency analysis asking what if questionsand building operational assessment frameworksconceptual maps of how a plan is likely to play out in a particular situationthat provide more flexibility to commanders. Designing the next military staff To explore the optimal design of this AI agent-augmented staff, I led a team of researchers at the bipartisan think tank Center for Strategic & International Studies Futures Lab to explore alternatives. The team developed three baseline scenarios reflecting what most military analysts are seeing as the key operational problems in modern great power competition: joint blockades, firepower strikes and joint island campaigns. Joint refers to an action coordinated among multiple branches of a military. In the example of China and Taiwan, joint blockades describe how China could isolate the island nation and either starve it or set conditions for an invasion. Firepower strikes describe how Beijing could fire salvos of missilessimilar to what Russia is doing in Ukraineto destroy key military centers and even critical infrastructure. Last, in Chinese doctrine, a Joint Island Landing Campaign describes the cross-strait invasion their military has spent decades refining. Any AI agent-augmented staff should be able to manage warfighting functions across these three operational scenarios. The research team found that the best model kept humans in the loop and focused on feedback loops. This approachcalled the Adaptive Staff Model and based on pioneering work by sociologist Andrew Abbottembeds AI agents within continuous human-machine feedback loops, drawing on doctrine, history and real-time data to evolve plans on the fly. In this model, military planning is ongoing and never complete, and focused more on generating a menu of options for the commander to consider, refine and enact. The research team tested the approach with multiple AI models and found that it outperformed alternatives in each case. AI agents are not without risk. First, they can be overly generalized, if not biased. Foundation modelsAI models trained on extremely large datasets and adaptable to a wide range of tasksknow more about pop culture than war and require refinement. This makes it important to benchmark agents to understand their strengths and limitations. Second, absent training in AI fundamentals and advanced analytical reasoning, many users tend to use mdels as a substitute for critical thinking. No smart model can make up for a dumb, or worse, lazy user. Seizing the agentic moment To take advantage of AI agents, the U.S. military will need to institutionalize building and adapting agents, include adaptive agents in war games, and overhaul doctrine and training to account for human-machine teams. This will require a number of changes. First, the military will need to invest in additional computational power to build the infrastructure required to run AI agents across military formations. Second, they will need to develop additional cybersecurity measures and conduct stress tests to ensure the agent-augmented staff isnt vulnerable when attacked across multiple domains, including cyberspace and the electromagnetic spectrum. Third, and most important, the military will need to dramatically change how it educates its officers. Officers will have to learn how AI agents work, including how to build them, and start using the classroom as a lab to develop new approaches to the age-old art of military command and decision-making. This could include revamping some military schools to focus on AI, a concept floated in the White Houses AI Action Plan released on July 23, 2025. Absent these reforms, the military is likely to remain stuck in the Napoleonic staff trap: adding more people to solve ever more complex problems. Benjamin Jensen is a professor of strategic studies at the Marine Corps University School of Advanced Warfighting and a scholar-in-residence at American University School of International Service. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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