Copilot‘s next trick is diagnosing your PC’s problems, but the catch is that the assistant doing the diagnosing is itself part of the problem. Windows Latest reports that Microsoft is testing a new Copilot feature called PC Insights, which will let you ask the AI assistant natural language questions about your computer’s hardware and storage instead of digging through the Task Manager or Settings. The feature will reportedly allow users to ask questions like, “Do I have enough space for a 100GB game?” and Copilot will check the available storage to offer a response. Users will also be able to ask about CPU usage, battery health, etc., to diagnose issues.
What Copilot will be able to see
According to a Microsoft support document spotted by Windows Latest, PC Insights is expected to read CPU, RAM, and GPU usage, calculate free storage space, and check folder sizes for places like your Downloads or Documents. It will also be able to see connected USB devices, external drives, printers, webcams, and the state of the computer’s Bluetooth and Wi-Fi connections.
Shikhar Mehrotra / Digital Trends
The feature will reportedly be opt-in and will ask users for permission each time they ask Copilot a hardware-related question, unless a user switches it to “Always allow.” Microsoft’s AI assistant won’t be able to open individual files, and for now, it appears limited to flagging problems rather than fixing them.
Copilot’s own resource use weakens the pitch
While the PC Insights feature may sound helpful, it has one big caveat. That is, the app promising to flag what’s slowing down your PC has been found to be a resource hog. In its testing, Windows Latest found that the current Copilot app uses up to 1GB of RAM at idle and takes up quite a bit of storage as it ships with its own private copy of Microsoft Edge.
PC Insights could be genuinely useful for less tech-savvy folks. But it’s hard to fully trust a tool for spotting resource problems when it’s contributing to them itself.
If any astute Hackaday reader saw [dongvua90]’s Newton’s cradle go on without human intervention all day long, they’d probably suspect the truth: there’s a battery and a magnet involved. But it is a nice desk piece, and you might be able to fool your less enlightened friends that you’ve discovered perpetual motion. Watch the resulting faux perpetual motion machine in action in the video below.
The trick is to sense the ball’s travel and inject a little electromagnetic pulse at just the right time. No problem for an ESP32 and a proximity sensor like the ones you find on some 3D printers. In fact, there’s very little custom circuitry. Everything is a module, and even the Newton’s cradle is cut out of a premade toy. A printed case and some software are really the heart of the design.
We can imagine this might be an interesting science demonstrator. Show the class the cradle with the electronics turned off, then subtly turn it on and ask the class what changed. You could even make the point by having students do it normally, while only you can get it to keep going forever, and challenge them to deduce what’s going on.
Tata Consultancy Services plans to build a team of up to 8,900 forward-deployed AI engineers and is looking for acquisition targets in AI and cybersecurity, chief executive K Krithivasan said.
The move is India’s largest IT firm answering the question that has hung over the sector since the arrival of agentic AI in enterprise stacks, which is whether the industry that sells engineering hours has anything left to sell.
Krithivasan said TCS aims to convert between 1% and 1.5% of its associate base into forward-deployed engineers. Against a headcount of 593,798 at the end of June, that works out at roughly 5,900 to 8,900 people.
The term is borrowed from the AI labs, where forward-deployed engineers sit inside the client’s business and make the model actually do something. Chief operating officer Aarthi Subramanian described them as specialists who are multi-skilled but deep in one particular area, which is a polite way of saying they are the people sent in when the pilot does not survive contact with production.
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Krithivasan has framed the programme as evidence that AI creates jobs rather than destroys them. He did not say whether the engineers will be hired externally or retrained from within, and on a base of nearly 600,000 people, that distinction is the whole story.
TCS added 9,279 employees in the June quarter, its second consecutive quarter of headcount growth after a stretch of contraction. Net profit rose about 5% year on year to ₹13,349 crore, on revenue up 14% to ₹72,275 crore, with an operating margin of 24%.
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“Q1 FY27 reflects continued growth momentum and the strength of our strategic positioning, despite geopolitical and macro-economic headwinds,” Krithivasan said alongside the results, which also carried a ₹12 interim dividend. Growth of 14% is not the profile of a company being hollowed out, though it is also not yet the quarter in which the theory gets tested.
The company reported an order book of $9.5bn for the quarter, including an AI-led transformation deal with the Swedish bearings maker SKF, and said its AI business is now running at a $2.6bn annualised revenue rate, per its own results statement. That last figure is the one investors will test, because it is the only line that distinguishes AI revenue from the rest.
The anxiety it is meant to answer is straightforward. India’s $315bn IT services industry sells effort, and clients who believe AI shortens projects will expect a share of the productivity gain to show up as a lower price.
Acquisitions are the second half of the answer. Krithivasan said TCS is scanning for targets in AI and cybersecurity, though the company named no candidates, gave no budget, and set no timeline.
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TCS is not alone in trying to sit closer to the model layer. Anthropic’s $100m Claude Partner Network pulled Accenture, Deloitte, Cognizant and Infosys into its enterprise ecosystem in March, which tells you where the integrators think the margin is going to sit.
India, meanwhile, is trying to move up the stack in hardware as well as services, with CG Semi beginning commercial chip production at its $870m Gujarat plant this month. The services giants and the fabs are, for once, chasing the same customer.
What TCS has not disclosed is how the forward-deployed engineers will be priced. Consulting firms have historically billed by the hour, and an engineer whose job is to make a model replace hours is an awkward thing to put on a rate card.
The company will report again in October. By then the useful number will not be 8,900, but whether the $2.6bn AI run rate has grown faster than the business it is supposed to be cannibalising.
What just happened? The long-running effort to introduce the click-to-cancel policy will end this October – for those living in New York City. Consumers will no longer be forced to jump through so many hoops when trying to cancel a subscription that they’re encouraged to give up, and the process will be carried out via the same method they used to sign up.
Mayor Zohran Mamdani and the Department of Consumer and Worker Protection (DCWP) announced that the city’s final Click-to-Cancel Rule will take effect on October 1. New York will become the first US city to impose this type of requirement at the municipal level.
“Whether it’s hidden fees that suddenly appear at checkout or subscriptions that take one click to sign up for and a dozen steps to cancel, the result is the same: working people pay more while corporations profit,” said Mayor Mamdani. “That ends now.”
The regulation covers automatic renewals and continuous-service subscriptions, including streaming platforms, gyms, subscription boxes, and free trials that turn into paid plans.
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Businesses must clearly disclose the price, billing frequency, renewal terms, cancellation deadline, and available cancellation methods before asking for payment details or consent.
Companies must allow customers to cancel at any time using a process as easy as the one used to subscribe and through the same medium – so no being forced to cancel over the phone. A business that accepts sign-ups through several channels must offer cancellation through all of them. Even subscriptions started in person must have an online cancellation option.
The rule also targets those all-too-familiar retention tactics. Companies can’t hang up on customers, hide or misrepresent cancellation instructions, lie about the consequences of leaving, or unreasonably delay a request. Consumers cannot be charged to return items supplied for free without their affirmative consent.
Subscriptions with terms of at least six months will require a reminder 15 to 45 days before the cancellation deadline. Businesses must also warn users before free trials lasting more than a month become paid-for and provide notice of material changes, including price increases.
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Violations can bring restitution and civil penalties starting at $525 and rising to $1,050 for a second offense and $3,500 for subsequent violations. The city estimates the rule could save residents between $21.5 million and $162.5 million annually.
We previously reported on the FTC approving a nationwide click-to-cancel rule in 2024, its decision to delay enforcement in May 2025, and an appeals court vacating it two months later because the agency skipped a required preliminary economic analysis. The FTC restarted the rulemaking process in March.
States have continued filling the federal gap. California’s expanded Automatic Renewal Law mandates simple online cancellation and renewal reminders, while Colorado, Connecticut, Massachusetts, Minnesota, and Utah have also strengthened their automatic-renewal rules, although the details differ.
The click-to-cancel measure is final, but New York City’s companion proposal requiring businesses to display all mandatory “junk fees” in the advertised price must still go through a public-comment period and a hearing.
Microsoft and backup are two words often uttered together, usually in the form of “Microsoft Windows has crashed again, where’s my backup?” The question is: what would a backup look like for a digital sign in Derby?
Spotted by eagle-eyed Register reader “nategee”on a stroll in Derby, this sign appears to have spent much of the day pleading to be backed up.
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This poses an interesting question. What, exactly, would constitute a backup for a sign? Microsoft would obviously like somebody to log in with a Microsoft account so the data on the computer behind the scenes can be squirted into its cloud.
However, we’d contend that a more appropriate backup for a digital sign would involve glue, paper, and a person on a ladder, wielding a brush.
Although the words “if anything gets my back up” is often muttered by Windows users faced with yet another surprise update or unexpected screen of blue, the backup suggestion usually pops up when Windows restarts after an update. Microsoft has examined the user’s device and tightly clutched its pearls upon realizing that the PC isn’t backed up.
And now would be the perfect time to back it up by signing in with a Microsoft account, at least as far as the tech giant is concerned. The owners of the billboard might disagree.
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Sadly, there is nowhere obvious for a technically minded passer-by to attach a keyboard and mouse to let the sign continue the startup process, and the hard-pressed techie responsible, doubtless sitting behind a desk at the mothership, has yet to give a remote command to unbork the signage.
Digital signage might be flexible, but we doubt Microsoft is advertising backups here – or reminding everyone that Windows has a habit of nagging users into doing what Redmond thinks is best for them.
Perhaps it’s best to back up to something that doesn’t involve Microsoft’s OS, or maybe even save the power, dust off the poster poster and glue pot. No tech required. ®
South Korea will draw up record budget spending of more than 800 trillion won ($530.97bn) for fiscal 2027, supported by stronger tax revenues from the booming AI chip industry, the government said on Monday.
It is the clearest sign yet that Seoul intends to spend the semiconductor windfall rather than save it, an argument the country has been having since it floated a ‘future response fund’ built on chip tax receipts earlier this month.
Budget Minister Park Hong-keun, speaking at a national fiscal strategy meeting, said the plan would be financed through higher tax receipts and expenditure cuts. The proposal compares with this year’s 727.9 trillion won spending plan, excluding supplementary budgets.
Three “mega-projects”, covering chips, AI data centres and physical AI, will receive top fiscal priority. The government said it would secure the funding capacity through a major restructuring of existing programmes rather than relying solely on the extra tax revenue, which is a more disciplined framing than the numbers alone suggest.
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Park said the restructuring would target about 50 trillion won of spending, twice last year’s level, through a review of discretionary and mandatory expenditures and cuts to underperforming programmes. That is the part of the plan that will meet resistance, because every underperforming programme has a constituency.
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President Lee Jae Myung said the government would use all available means to keep corporate investment on schedule. “Additional tax revenue coming at this time is a precious resource to be used at a golden time when global AI dominance will be determined,” he said.
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The windfall is real and it is concentrated. Combined operating profits at Samsung Electronics and SK Hynix are projected to exceed 600 trillion won this year, up from roughly 90 trillion won a year earlier, and semiconductors now account for a rising share of national exports.
Seoul has already committed $880bn to chips, data centres and robots over the next decade under the same mega-project framing. The 2027 budget is the first annual instalment that has to be written against actual receipts rather than pledges.
It is also a visible upgrade on the government’s own plan. Under fiscal guidelines approved by the Cabinet in March, 2027 spending was pencilled in at 764.4 trillion won, with officials saying at the time that the figure could reach around 800 trillion won only if tax revenues improved and the expansionary stance held. Both conditions, it turns out, were met by the chip cycle.
The Future Response Fund now has a defined shape, at least on paper. It will operate as a strategic investment platform, setting aside tax revenue that exceeds long-term trends and directing it into four areas: youth, growth engines, regions and talent.
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What the government did not say is how large the fund will be, when it launches, or how “long-term trends” in tax revenue will be calculated. Those are the details that decide whether it is an endowment or an accounting line.
A budget written on cyclical profits is a bet that the cycle holds. Memory has crashed before, and the profits funding this plan come from two companies selling into a single wave of AI infrastructure spending.
The boom is also already distorting things closer to home, with the chip rally pressuring Korea’s bond market and record chip bonuses flagged as an inflation risk by economists. An expansionary budget on top of that is a choice, not a neutral act.
The government will publish the full 2027 budget bill later this year, when the restructuring targets stop being a headline figure and start naming programmes. That is when the 50 trillion won will get tested.
You know that one friend who always takes great photos but isn’t the best at sharing them? At my last Fourth of July party, I watched him snap a great picture of my fiancée and me, but instead of asking him to share when he had time, I pulled out Liene’s N200 Pro portable photo printer from my bag. I asked to print that photo on the spot and offered to print anything else he wanted.
Within minutes, it felt like half the party had their phones out, ready to print a photo. By the end of the night, nearly everyone went home with a physical memory of that party.
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Like many children of the ’90s, I’ve seen no shortage of trends from my youth try to return with the assistance of modern technology. Capturing a moment that you can physically hold will always be more interesting to me than an Instagram shot, and over the last two years, we’ve seen photo printers get smaller, more capable and considerably less expensive.
The team at Liene, makers of photo and sticker printers with a reputation for being easy to use, created something so portable that it weighs less than a pound and is just 1.2 inches thick, making it an easy travel companion.
It doesn’t get much easier to use than this N200 printer. It charges via USB-C, which is convenient. On more than one occasion, while testing this printer, I’ve just connected it to the car charger on the way to a gathering, and that has been enough for 25 prints over more than an hour. Photo paper and ink cartridges are both easy to install and leave very little mess behind, aside from the small edge you tear off each photo as it exits the printer. As long as you have a phone, you can use this printer.
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Swapping out the ink catridge doesn’t get much easier than this.
Russell Holly / CNET
Liene printers use thermal dye sublimation to create images, which means every print is done in layers. You’ll see the photo paper move in and out of the machine a couple of times with each print as it applies yellow, magenta and blue ink to create the image before it gets a final lamination and exits the printer. This whole process takes just under 90 seconds, and the image quality is surprisingly good for a 3×2 printed image. And because the sheets Liene sells for this printer are also stickers, you can easily peel off the backing and stick the picture to whatever you want.
If you want to quickly go from your camera roll to printing, Liene’s app makes that pretty effortless. But if you want to have some fun, you’ll find loads of personalization options. If you want to take photos through the app using old-school camera filters, it’s right on the home screen. Want a border around the photo? Too easy, there are dozens of options that update constantly to reflect current holidays and sporting events.
The only part of the app I didn’t use too often was the collage function, but only because a 3×2 image is already pretty small and making it smaller wasn’t usually what friends around me would ask for.
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The photo paper slot is well hidden, but no less easy to access.
Russell Holly / CNET
The $100 version of this printer includes 50 sheets of sticker paper and five ink cartridges. There’s an $89 version that comes with 10 sheets of sticker paper and one ink cartridge, but you’re immediately spending more the moment you need more paper or ink because a new box of paper and ink is $25. This also means that each print comes out to about 50 cents, which is slightly less than the 65 cents per print average from competitors like Fujifilm and Canon.
What Liene created with this printer is a fun conversation starter at a party. Tiny sticker photos aren’t the most practical thing ever, but they’re undeniably fun to make and share at a cost that will work for just about everyone.
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If you’re the kind of person who enjoys a good physical picture, and you have friends to share something like this with, there’s a lot to like about this printer.
IBM’s launch of its AI coding assistant “Bob” points to a much bigger shift in enterprise modernization. Across the industry, AI tools are being positioned as a way to make legacy systems easier to understand, assess and eventually modernize. And there is real value there.
Some of these tools can read thousands of lines of legacy code, identify deprecated APIs, summarize business logic and surface technical debt in minutes. For organizations carrying decades of operational history, that kind of visibility is a big step forward – but let’s not confuse visibility with modernization.
Jim Piazza
Chief AI Officer at Ensono.
Understanding how a system works is necessary. It is not sufficient. I have seen teams produce clean dependency maps, detailed code summaries and impressive technical assessments, only to realize the hardest part starts after the AI has finished scanning the code.
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Legacy estates rarely sit neatly off to the side. They are woven into the operating model of the business. They reflect years of process decisions, integration choices, compliance requirements, customer-specific exceptions and institutional knowledge that is often scattered, tribal or barely documented. Lovely little treasure hunt, except the treasure is risk
An AI model may identify an ageing integration point or highlight an application that supports a critical business process. That is helpful. But the real challenge begins when teams realize how many other systems, workflows and operational teams are connected to what looked like a straightforward change.
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In many large organizations, legacy systems are still in place for a very simple reason: they work. They continue to perform reliably under demanding conditions, even if parts of the surrounding environment have evolved, degraded or become harder to support over time.
That is why modernization is not just a technology exercise. It is a sequencing exercise. It is a risk exercise. And, done properly, it is a business decision.
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The multi-layer challenge
Every technical decision inside a legacy estate has consequences somewhere else. A change to one application can affect recovery procedures, audit requirements, licensing agreements, batch schedules, integration layers or support processes that have been stable for years.
This is where many modernization programs stall. Teams underestimate how interconnected these environments have become. AI can accelerate the technical assessment, but its real value comes when those insights are connected to the operational and commercial context around the system.
That distinction matters. Enterprises are moving away from broad “replace everything” strategies and becoming more selective. Not every legacy platform needs to be ripped out. Some systems need restructuring. Some need better interfaces. Some need to be moved. And some, frankly, should be left exactly where they are because they are doing their job reliably at scale.
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Workload placement has become much more nuanced. Moving a service to public cloud may improve scalability and speed up software delivery, but it can also introduce data sovereignty concerns, latency issues, cost variability or new support dependencies.
At the same time, keeping workloads on modernized IBM Z or Power environments may provide more predictable performance for applications that already run effectively at scale.
The real question is not, “How do we get everything off legacy platforms?” The better questions are, “Which systems genuinely benefit from relocation, which need to be modernized in place, and which can be extended through modern interfaces?”
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Without that context, organizations can spend a lot of money moving systems around without actually fixing the underlying problem. Congratulations, you now have the same complexity in a newer location.
We are already seeing this play out in enterprise environments where legacy platforms still sit at the center of high-volume operations. In one recent assessment, AI coding assistants were used to analyze more than six million lines of RPG code running on IBM Power systems, processing roughly 30 million requests a day.
The work surfaced technical debt and concentrated areas of complexity in weeks, giving the organization a clearer basis for deciding what to modernize, where to start and how to sequence change without disrupting core operations.
That is the practical value of AI in modernization: not magic, but better visibility, faster assessment and smarter prioritization.
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Why enterprise AI deployments are becoming more specific
This broader shift is also showing up in how hyperscalers talk about enterprise AI adoption. Microsoft CEO Satya Nadella has described the market as moving from “discovery” into “widespread diffusion.” In plain English, the challenge is no longer just building impressive models.
It is embedding AI into real workflows, real operations and real business systems at scale. That is much closer to how modernization actually works inside large enterprises.
The same shift is happening with AI models themselves. The industry still loves to talk about scale, but most enterprise teams are not sitting around hoping for a trillion-parameter model to save them. They need tools that help engineers solve very specific problems inside environments that are already complicated enough.
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In many cases, smaller, specialized models are proving more useful because they can be deployed in controlled ways, focused on specific tasks, and governed more tightly.
That governance point matters. Bringing AI into infrastructure operations raises very practical questions: What data can the model access? What systems can it touch? Can it recommend changes? Can it execute them? Who approves movement toward production?
That is another reason task-specific models are gaining traction. Teams can define exactly what the model is allowed to do, where human approval is required and how changes move through existing controls. In enterprise environments, that kind of control is not bureaucracy. It is how you avoid turning a productivity tool into tomorrow morning’s outage bridge.
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Where AI is delivering practical value today
The organizations getting real value from AI are usually not the ones making the loudest claims about it. They are applying AI to engineering and infrastructure work that already consumes huge amounts of time: investigating incidents, mapping dependencies, validating changes, supporting regression testing and understanding how complex systems actually behave.
A lot of that work comes down to giving engineers better visibility and helping them get to root cause faster.
AI models can help connect runtime anomalies to recent code changes. They can reduce the time teams spend manually tracing incidents across hybrid environments. They can support regression testing around older applications and surface integration dependencies that were previously difficult to visualize across multiple infrastructure layers.
That becomes especially important in environments where cloud-native services sit alongside long-established mainframe and midrange systems. In many organizations, the hardest problems show up in the seams between those environments, particularly when different teams manage different parts of the estate with different tools, different metrics and different operating rhythms.
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That is why the most useful AI deployments tend to focus on practical engineering work, not grand attempts to automate everything at once.
Organizations are seeing value in areas that are repetitive, complex and difficult to scale manually. Automated test generation can reduce regression risk around legacy applications. AI-supported observability correlation can shorten incident investigation cycles. Dependency analysis can help teams prioritize infrastructure work that removes bottlenecks affecting service delivery.
In most cases, AI is not replacing engineering judgment. It is improving the work engineering and infrastructure teams already understand well. And that is where the expectations need to be clear.
AI can absolutely speed up discovery. Work that once took weeks of manual assessment can now happen much faster. But that is usually the point where the real work starts.
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A model can tell you how systems connect. It cannot tell you how much disruption the business is prepared to absorb. It cannot decide which customer commitments matter most. It cannot magically unwind 25 years of operational dependency while everyone politely keeps breathing.
Technology leaders should view AI coding assistants as decision-support tools for broader infrastructure and modernization strategies, not as stand-alone solutions to legacy complexity.
IBM’s Bob announcement shows how quickly these capabilities are advancing, especially when it comes to understanding legacy code and helping teams work through large, complex estates. But visibility only matters if organizations can turn it into practical change without creating instability elsewhere.
AI can help you read the legacy estate. It can help you understand the risk. It can help you move faster. But modernization still requires judgment, sequencing and operational discipline.
This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit
The good news is that Sergeants Zach Allbee and Nik Yakel from Luke Air Force Base have helped to design a chute for the F-35A’s gun system that can at least reduce the chances of Class A engine mishaps. Among other criteria, a Class A mishap is defined as one where the damage costs more than $2.5 million. According to a video posted on the Luke AFB Facebook page, the system clips onto the jet’s existing adapter without any modifications and channels spent casings directly into an ammo can.
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This isn’t a fix that addresses known issues like complex maintenance or software issues. Rather, it’s a mechanical solution that helps to reduce the F-35’s chances of damaging $20 million Pratt & Whitney F135 engines due to foreign object debris hazards (FOD). FOD hazards are essentially small loose objects that lie undetected on runways and can be sucked into a jet engine’s intake. According to Luke AFB, the Project Z.A.C.H (Zero-point Ammunition Cartridge Holder) device costs about $98 and means airmen no longer have to manually catch shells being downloaded from the fighter, a process during which about 20% of shell casings are missed. These missed shells can scatter across the flightline, creating potential FOD hazards.
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The problem with spent ammo casings
The problem the Sergeants set out to solve is down to the way the F-35’s internal gun system is unloaded. Rather than unloading the ammunition by hand, the usual procedure is to use a mobile loader that loads the new shells while ejecting the spent shells. While this undoubtedly sounds like a whole “barrel” load of fun for the crews, the procedure can cause some headaches.
According to Luke AFB, the ammo can sits about six feet under the existing adapter, and during downloads, the spent casings fall freely toward it. This is the point when the “20% miss rate” comes into play. This is bad enough in ideal situations, but at night or when crews are under pressure, it can be all too easy to miss even one. And this could be enough — there will only be one winner if a brass shell casing meets a turbine spinning at thousands of RPM. Even the incredible F135 engine that powers the F-35 would suffer serious damage from such an impact.
The Project Z.A.C.H device addresses this directly. The chute clips straight onto the existing adapter without any modifications and funnels the casings straight into the ammo can, eliminating the one-in-five miss rate entirely.
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A little ingenuity goes a long way
While this might seem like a minor issue, Luke AFB notes that even a single stray shell casing can create an FOD with the potential to cause a Class A mishap. For a fleet already known for long-standing maintenance issues and delays, anything that reduces the risk of further accidents has to be a welcome improvement. Speaking to ABC15, Sergeant Albee said that after one instance when he was watching shell casings “go everywhere,” he thought that there had to be a better way. And so Project Z.A.C.H was born.
It began as a quick “proof of concept” design, with the prototype built from whatever materials were available — and a little help from a 3D printer. The concept worked, and with assistance from the base’s Detachment Nine engineering team, the design was refined into a more durable three-piece bracket and flexible funnel that eliminates the chance of missing shell casings. The final version still costs less than $100; for some context, this is less than the $131 cost of each shell fired by the F-35.
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While reducing the chances of expensive mishaps is one of the obvious benefits of the device, the other big saving is time. According to the Luke AFB video, the device has reduced the time taken to perform the task by about half — a job that used to take 30 to 40 minutes can now be achieved in 15 to 18 minutes.
The Samsung Fold 8 series is just around the corner, and with Apple finally entering the competition this year, it’s more important than ever for the Korean smartphone maker to deliver real upgrades. In a new editorial, Samsung CEO TM Roh said the company will continue to make its foldable phones thinner, lighter, stronger, and more immersive, while placing an even greater focus on personalized AI experiences. The comments come ahead of Samsung’s Unpacked launch, where the company is expected to unveil the Galaxy Z Fold 8, Galaxy Z Flip 8, and a brand-new Z Fold 8 Wide.
Samsung Wants Foldables to Become the Perfect AI Devices
According to Roh, the next evolution of AI isn’t about simply answering questions anymore. Instead, Samsung believes AI is entering what it calls the “agentic era,” where AI assistants can take action on a user’s behalf while leaving the final decision in the user’s hands. That, however, requires AI to understand the person using it.
Roh argued that foldable phones are particularly well-suited for this future because they combine a compact form factor with a large display that expands whenever users need more screen space.
“As AI helps us with more at once, a screen that flexes and folds expands what is possible. This is what makes foldables special,” Roh said.
Image: Amanz
Samsung says it has spent years refining its foldable lineup by making devices slimmer, lighter, and more durable, and that trend will continue with future Galaxy foldables.
Beyond hardware, Roh also highlighted Samsung’s broader AI strategy. Rather than treating smartphones as standalone devices, Samsung wants AI to work seamlessly across its ecosystem of Galaxy phones, tablets, smartwatches, TVs, and smart home appliances. The idea is for AI to quietly connect these devices in the background, making everyday tasks feel more natural instead of forcing users to switch between separate apps and services.
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Beyond that, Roh pointed to Samsung Knox as the foundation of the company’s AI strategy, explaining that the security platform now protects not only individual Galaxy devices but also the information shared between them. According to Samsung, sensitive personal data will remain on the device whenever possible, allowing users to better understand how Galaxy AI works while maintaining control over their information.
A reliable mobile carrier is essential to our day-to-day life. We need access to calls, texts and the internet for pretty much everything. You likely have an opinion about your cellphone plan, and we want to hear about it.
This month, we’re asking which mobile carrier you rely on. You can take our two-minute survey to share your experience on your plan’s reliability, speed, value and customer service. The top picks will make it to our roundup, so be sure to check back in a few weeks to see if your favorite made the list.
Why we want to hear from you
Advertised speeds and coverage maps don’t tell the whole story. What matters is how your signal holds up in crowded spaces, on a road trip or even at home, and we want to know about your experience.
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“It’s easy to get overwhelmed with specs, especially when you’re comparing phone plan features, but the real test is whether your service is working as you expect or getting in your way,” said Jeff Carlson, CNET senior writer. “With so many variables — your phone model, the cell towers in your area, even obstructions like buildings and trees — each person’s experience is going to be different.”
Whether you’re on a national network or a budget mobile virtual network operator, you can help other CNET readers find a reliable carrier by sharing your thoughts.
How to make your voice heard
This survey is open through the end of July and takes only a few minutes to complete. After we gather enough information, we’ll crunch the numbers and publish the winners.
Need a refresher on mobile carriers? Check out our list of the best cellphone plans to see what CNET editors think.
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