Mobile phone contracts can tie you in for a year or longer, but Smarty offers a much more flexible alternative if you want plenty of data without making a long-term commitment. Its £10 monthly SIM plan includes 40GB of 5G and 4G data alongside unlimited UK calls and texts.

You pay monthly in advance and can cancel or change your plan whenever you want, and Smarty promises no credit checks or annual price rises. You can choose between a physical SIM or eSIM, and 5G access is included at no extra cost with a compatible phone and coverage.

Today's best Smarty SIM deal

Why we recommend it

The combination of 40GB of data and a £10 monthly price should be enough for plenty of everyday browsing, social media, streaming, navigation, and other mobile use without paying for unlimited data you may never need.

There's no speed restriction on the plan, and you can use your entire UK data allowance for tethering or creating a mobile hotspot. That could be particularly useful for connecting a laptop or tablet when you're away from your usual Wi-Fi connection.

EU roaming is included, as is Wi-Fi calling which could come in handy if the mobile signal inside your home or workplace isn't particularly strong.

Price context & historical value

Smarty charges £10 per month for the plan, which gives you 40GB of 5G and 4G data plus unlimited UK calls and texts.

The important difference compared with many mobile deals is that the price isn't dependent on signing a lengthy contract. It's a one-month rolling plan with no annual price rises, and you can cancel or switch plans whenever you want.

Should you buy it?

✅ Buy Smarty's 40GB plan if...

You want plenty of mobile data without committing yourself to a lengthy contract. The £10 monthly price, 40GB allowance, unlimited calls and texts, and ability to cancel or change your plan each month make it a flexible option.

❌ Skip Smarty's 40GB plan if...

You regularly use considerably more than 40GB of mobile data each month or need a large roaming allowance. Heavy streamers may be better served by a larger data allowance. Browse all of Smarty's plans here.

The Catch: What to know before you buy

Although the plan includes EU roaming, you can't use the full 40GB allowance while travelling. EU data is subject to a 12GB monthly fair-use limit, while usage outside included European destinations requires an Out of Plan add-on.

Smarty may also suspend your service if it identifies that you've used it outside the UK continuously for 60 days or longer within a rolling 12-month period. It's intended primarily as a UK mobile service rather than a SIM for extended stays overseas.

• Shop the full Smarty range of SIM plans

The internet is littered with hundreds of parental control apps that claim to give you complete visibility into your child’s online activities. However, in doing so, many of these apps invade your children’s private space and blur the lines into surveillance.

This is where HeyPolo stands out. Launched by the team behind Surfshark VPN, HeyPolo is a separate product that takes a consent-based approach to location sharing. It allows you to see the approximate or real-time location of your loved ones at any point.

The best part is that users can control who they share their information with, what information they share, and for how long. HeyPolo also says it will never sell, monetize or exploit users' location data, with location data encrypted while in transit.

If you’re looking for a lightweight, easy-to-use, and inclusive location-tracking application, HeyPolo might just be the right pick. Read on as we explore its various features and pricing, and compare it with the best parental control apps so that you can make an informed decision.

HeyPolo review: Plans and pricing

HeyPolo offers one of the simplest parental control pricing plans we've seen. The monthly plan costs $5.99/month, while the annual one is just $1.99/month. The only difference between the two plans is the duration of the subscription. Everything else is the same, meaning both plans come with everything HeyPolo has to offer.

One good thing is that a single plan covers your entire family, with unlimited devices and no per-person pricing. Exactly what Surfshark VPN is known for, too. You also get a 30-day money-back guarantee, which means that if you don't like how HeyPolo works, you can get a refund.

Next, although HeyPolo’s website says that it doesn't offer any free trial, that's not entirely true. Sure, if you purchase through the website, you don't get a free trial. But if you download the app on your iOS or Android device and purchase a subscription through the Apple App Store or Google Play Store, you do get the option of a 3-day or 7-day free trial.

HeyPolo review: Features

First up, there’s real-time location sharing, where you can view your contacts’ location details, which are updated every five seconds. Users can choose whether to share their exact location or a general area, giving them better privacy control.

Location sharing can either be left on indefinitely or for a specific time period. Users can also set arrival and departure alerts for specific places, such as school, work, or home.

There’s also an SOS emergency alert, where any family member can send an instant SOS alert that notifies the recipient of their real-time location. This could come in handy for elderly people living alone, children travelling solo at night, a car breakdown, or any other emergency situation.

You can also set up low-battery alerts, alongside location and emergency alerts, so you can know when a family member's phone is running low on power.

Similarly, there’s group location sharing, which allows users to share their location with several people at once within specific groups or circles.

What stands out is that while most location-sharing apps only allow the person who created the group to control it, HeyPolo gives every member a certain degree of control over what they share. Each plan comes with unlimited groups, and everyone can join for free. One person can belong to multiple groups simultaneously, each with different sharing settings.

You can choose between three different levels of location sharing: Exact Location, which shows your live location; General Area, which shows the neighborhood you're in; and Private Mode, which turns off location sharing completely. You can also choose to share your location for a one-time period or during repeating periods, rather than having it constantly enabled.

So, you’ll get a notification every time your child reaches school or leaves it. The same goes for workplaces too. You can also share trips with people in your group. This shows where you travelled, when you travelled, your route on a map, and the length of the trip.

Lastly, HeyPolo saves detailed location history, allowing you to check where you or any member of your group has been, including past routes. However, this history is stored for only seven days, after which it is automatically deleted.

HeyPolo review: Interface and in-use

HeyPolo is very easy to install. Simply download the application from the Google Play Store or iOS App Store, and you’re good to go. You only need to set up a profile, purchase a subscription, and then invite the family members or friends whose locations you want to track.

People can be invited either by sharing a link or using the short code displayed on the screen. Note that only one person in the group needs an active subscription; everyone else can join for free.

An important caveat worth mentioning is that you won’t be able to move ahead with the app until you opt for a free trial or purchase a subscription, which means there is no demo mode offered by HeyPolo.

However, once you’re inside, you’ll see an interface with a live map showing everyone in your group as icons. Each icon is labelled with a status such as “Active”, “Arrived Home”, “In Private Mode”, or “Left Work”. People who are on the move will have a tag such as “On the Move (47 mph)”, showing their current speed.

We also like how the reviews for the HeyPolo apps have been overwhelmingly positive. The app is rated 4.35 stars on Google Play and a whopping 4.9 on the App Store. Most users describe the setup as uncomplicated, and the application itself is minimal and low-clutter, which is consistent with HeyPolo’s positioning as a lightweight, consent-first alternative to surveillance-heavy family trackers.

HeyPolo review: Support

HeyPolo has one of the fastest support services we've seen across the industry. There are two ways to reach customer support: email and live chat.

We tried out the live chat function by clicking on the small chat icon at the bottom right of the screen. To our surprise, it wasn’t an automated AI chatbot where you have to fight through several menus before getting an answer.

A live human agent was there to help us almost immediately, and resolving any queries was as easy as typing them out and asking whatever we needed. Overall, the chat was very swift, and we got straightforward, to-the-point answers to our questions.

Just keep in mind that live chat support is available from 9am to 5pm CDT. But there’s a good collection of FAQs, blogs, and articles on the website should you need help with common queries outside these hours.

HeyPolo review: The competition

HeyPolo is very good at what it does – tracking the real-time location of your family members. However, it's pretty limited in functionality and does not extend to other parental control features. If that’s what you’re looking for, here are a few alternatives you can consider.

mSpy is one of the best keyloggers in the industry, offering extensive insights into your child’s device and allowing you to see every word they type on their devices.

It also comes with robust location tracking, just like HeyPolo. You can monitor various social media platforms such as Instagram, Snapchat, WhatsApp, and even TikTok, and block certain apps on your child’s phone that you do not approve of. There’s also a screen-recording function that captures the child’s phone activity at set intervals.

That said, mSpy is a bit intrusive and does not follow the same consent philosophy as HeyPolo. Not to mention, it can also be pretty expensive, costing $11.19 per month on the annual plan.

Life360 is perhaps the closest substitute to HeyPolo, offering similar location-sharing features. However, it comes with better ancillary features than HeyPolo, such as 24/7 roadside assistance, crash detection, emergency dispatch, and free towing for up to 50 miles.

You also get $1 million in reimbursement for stolen funds, medical assistance, stolen phone protection, and more, depending on the plan you choose.

Life360 also offers a 7-day free trial, allowing you to check out the application and see if it suits your needs. That said, it's again a bit expensive, with its Silver plan priced at $9.99 per month.

HeyPolo review: Final verdict

HeyPolo is a straightforward, no-nonsense location-tracking application that helps you know the exact location of your loved ones at any moment.

It's ideal for families that believe in complete transparency. HeyPolo allows members to choose what data they share, with whom, and for how long, giving them greater control over their privacy. Users can see real-time locations updated every five seconds, as well as location history going back up to seven days.

You also get a 3-day or 7-day free trial when you purchase a subscription on the mobile apps. Along with this, the subscription is very affordable, at just $1.99/month.

That said, HeyPolo isn’t a full-fledged child monitoring app and is limited to location tracking. If you need other features like social media tracking or screen-time management, mSpy can be a good alternative.

• We've also featured the best parental control software

If you’re looking for a comprehensive online security suite for your family that also includes parental controls, Bitdefender is one of the best options right now. It's a well-known security provider offering an award-winning antivirus program, along with a password manager, VPN, and identity theft protection.

But does its parental control offering, which is bundled with its Family plans and not available via a standalone subscription or even a dedicated app, compete against the best parental control apps?

Read on as we dissect the various parental control features it offers, what they cost, how easy the dashboard is to use every day, and what the top competitors offer.

Bitdefender parental control review: Plans and pricing

Bitdefender no longer offers its parental control features as a standalone subscription. You’d have to get one of its four family plans. But note that its entire suite of parental control features is available with each of these four plans.

The Total Security Family plan starts at $79.99 for the first year and covers up to 25 devices across five family members. At this price, the cost boils down to around $16 per member per year, which is more affordable than many other parental control applications. Not to forget that, for the price, you also get 24/7 real-time antivirus protection for up to 25 devices, as well as a password manager.

Next is the Premium Security Plan, which costs $99.99 for the first year and also comes with scam protection, AI-based scam protection, and a VPN with 4,000+ servers in 50+ countries. The Ultimate Security Family Plan and the Ultimate Security Plus Family Plan cost $119.99 and $199.99 for the first year, respectively.

The former comes with dark web monitoring and identity theft protection features such as an identity protection score and real-time breach notifications, while the latter also includes $2 million in identity theft insurance, three-bureau credit monitoring, and other bank, credit card, and investment alerts.

Bitdefender parental control review: Features

One of the standout Bitdefender parental control features is the ability to set screen-time schedules for your children, who would only be able to access their devices during the allowed time intervals.

Along with this, Bitdefender also offers several preset routines: Focus Time, Family Time, and Bedtime, which you can customize as per your child’s daily activity and schedule.

There’s also a pretty handy internet time management feature, which allows you to control how much time your child spends on the internet during a day. A nice addition is the ability to reward extra screen time for your children for responsible online use.

In addition to internet scheduling, parents can also choose to cut off internet access directly on their child’s device using Bitdefender’s Stop Internet feature.

Bitdefender also offers predefined age-appropriate filtering categories to help you filter out inappropriate content such as porn, betting, or online gaming for your children. As with screen time, you can also fine-tune these filters to better suit your child’s day-to-day use.

Apart from category-level filtering, parents can also allowlist or blocklist specific URLs individually, in case you want to go beyond the category selection.

Parents can set up to five child profiles, each with the child’s name, photo, and birth date. Bitdefender automatically applies age-appropriate filtering as soon as the profile is created, which parents can then edit as per their needs.

Along with this, there’s also location tracking, which helps you know where your child is on an interactive map at all times.

Lastly, there’s Safe Search, which lets you remove explicit and harmful results from search engines, as well as YouTube restrictions, which ensure your child only views age-appropriate videos on the platform.

However, note that content filtering and safe browsing require an active VPN connection to function, as per Bitdefender’s listing on the Google Play Store.

Bitdefender parental control review: Interface and in-use

Bitdefender parental control works across Android, Windows, iOS, and macOS. That said, Windows and Android get full, unrestricted enforcement of every feature, whereas macOS and iOS are noticeably more limited, largely due to Apple’s own platform restrictions.

For instance, iOS content filtering runs through Apple’s Screen Time and not Bitdefender’s own engine. Parents have to create a child account through Apple ID, then Bitdefender’s app hooks into Apple’s Screen Time restrictions rather than doing its own independent content filtering.

However, the setup is pretty simple. You just have to download the app on your child’s own device. Unlike other parental control applications, you can’t download the app on your child’s phone remotely – you’ll need physical access to the device to do so.

One thing worth noticing is that, after the 2025 overhaul, parental control is no longer configured within the Bitdefender Central mobile app, but from the Bitdefender Central web dashboard, which can still be accessed through the mobile application.

Once you’re on this dashboard, day-to-day use is genuinely easy. Bitdefender’s Activity Dashboard is filled with several graphs and charts, which allow you to check your child’s phone activity at just a glance.

For example, there’s a bar chart showing their daily internet time over the past few days, as well as a pie chart showing their current day’s internet usage along with their remaining time. The dashboard also gives parents visibility into what’s actually being blocked and when.

The Prevented Content Access panel is a running log of every link blocked on the child’s device over the past 7 or 30 days. This allows you to see whether your filtering settings are actually able to catch anything, or whether your child is repeatedly trying to search for restricted websites on their device.

Bitdefender parental control review: Support

Bitdefender offers one of the most extensive support options we’ve seen across the industry. For starters, there are hundreds of articles, blogs, and how-to explainers on its website, neatly categorized based on different products.

If that doesn’t solve your problem, you can contact Bitdefender support using 24/7 live chat, phone, or email. However, to do so, you’ll first have to go through a few selections, such as the exact help you need, the type of issue you’re facing, and the product you need help with.

The support section features various phone numbers for different regions. The email support requires you to enter your own email address along with the problem you’re facing and doesn’t hand out direct email addresses to the consumer.

Beyond all this, Bitdefender also has an active expert community where you can get answers and solutions from other users across the world. Overall, Bitdefender’s support infrastructure is pretty solid, and you’ll never be left wanting for answers.

Bitdefender parental control review: The competition

Bitdefender is billed as a complete security suite and not a standalone parental control app, which is why it does lack a few advanced, dedicated parental control features.

For instance, Parentaler offers social media monitoring, allowing you to view your child’s WhatsApp, Instagram, Telegram, Facebook, Snapchat, and TikTok accounts, and see what they’re posting or with whom they’re chatting.

There’s also text and call monitoring with Parentaler, allowing you to read your child’s incoming and outgoing texts, including deleted messages. We also like its keyword alert function, where you can get instant notifications if your child uses certain controversial words or slang in their conversations.

Another notable feature missing from Bitdefender is geofencing. While it allows you to check your child’s location, it doesn’t offer alerts based on allowed or restricted zones on a map.

If you’re looking for a more comprehensive all-in-one package, Aura is another strong option. It combines parental controls with identity protection, antivirus, VPN, and a password manager, making it more of a complete digital security solution than a standalone parental control app.

If you still need a standalone parental control app but need something more affordable, try Google Family Link, which is entirely free to use and offers comparable features such as screen-time management and content filtering.

Or, you could try FamilyTime, starting at just $2.41 per single device per month. In addition to screen-time scheduling and internet schedules, you can also block apps or games on a child’s device that you don’t approve of.

It also comes with an SOS panic button that your child can use during an emergency. It’s also a great choice for households with several children, thanks to its affordable family plans that can cover up to five devices.

Bitdefender parental control review: Final verdict

Bitdefender’s family packages are ideal for parents looking for all-round security protection for their children rather than a dedicated, comprehensive parental control app.

But there’s still lots to like. You get robust screen-time management and internet-time management features, along with predefined age-appropriate filtering categories and location tracking. That’s all in combination with an antivirus with real-time protection, a password manager, an unlimited VPN, and identity theft protection, depending on the plan you choose.

The pricing is pretty affordable too, with the monthly cost working out to around $1.33 per member on the entry-level plan. However, if you’re looking for more advanced features, such as social media monitoring, keyword alerts, or geofencing, options like Parentaler or mSpy are more suitable.

• We've also featured the best parental control software

Parental control applications help you keep tabs on and manage screen time for your children effectively. However, the market is flooded with thousands of applications, and picking the best parental control app for your specific needs can be quite a challenge.

This is why we’ve dug deep and conducted a comprehensive review of Parentaler – one of the most popular child monitoring applications today.

Along with extensive social media monitoring, the application allows parents to monitor their child’s texts across various platforms, track their location using GPS, and filter the kind of content they can view online.

But is Parentaler the right choice for your? Read on as we analyze its best features, pricing, and user experience, while also comparing it with the best in the industry.

Parentaler review: Plans and pricing

We’re not a fan of how Parentaler’s pricing isn’t prominently displayed on its website. You’ll have to answer a series of questions before you can find out how much it costs.

We’ve done some digging to find out that its monthly plan costs $42.69, whereas the quarterly plan comes at $24.40 per month. However, its most affordable plan is the annual package, costing $10.17 per month, billed annually at $121.99.

The good thing is that there aren’t any plans to choose from, other than the subscription length. All the three packages offer the same set of features, which is everything Parentaler has to offer. This is the kind of simplicity we also lauded in HeyPolo – Surfshark VPN’s own parental control app.

What we also didn’t quite like about Parentaler is that it doesn’t offer a free trial or even a demo, which means you’ll have to buy a plan to see how it works for you. That said, the company does provide a 14-day refund policy, so if the app doesn’t meet your expectations, you can claim a full refund.

Parentaler review: Features

Parentaler offers three main categories of functions with its child monitoring app: text and call monitoring, location monitoring, and content filtering. Let’s dive into each of them.

Parentaler allows you to monitor various platforms such as WhatsApp, Facebook, Instagram, Snapchat, Telegram, Viber, Kik, and TikTok. Parents can also view messages their child sends and receives, calls made, links shared, and any media they might have sent or received.

Besides this, Parentaler also lets you keep an eye on the kind of content your children are sharing on a particular social media platform, say Instagram or TikTok, and this includes keeping you aware of their posts, stories, and more.

Its SMS and text monitoring is also pretty robust and works with iMessage on iPhone, allowing you to see both incoming and outgoing texts, including deleted messages. Of course, you can also monitor call logs on both platforms, including a list of contacts.

Text monitoring also covers all major social media platforms. One caveat worth noting is that instant-message tracking, such as Facebook, WhatsApp, Viber, and Skype, along with Gmail and Wi-Fi network monitoring only works on Android if it’s rooted. That’s a bit of a bummer, in our opinion.

Next up is its GPS tracking technology, which allows you to check your child’s location right from the app’s dashboard on your device. You can even view detailed information such as the address, timestamps, and coordinates.

Parents can also mark allowed and restricted zones on a map directly from the Parentaler app and get instant alerts if their child enters or leaves these geofenced areas. You can also set screen-time limits with Parentaler, designating time limits for certain apps such as social media or games.

On the flip side, you can also schedule downtime, during which your child can only use certain apps. For instance, you can set up downtime during school hours where only learning apps might be accessible to your kids.

Along with this, there’s a dedicated Focus Mode on Android, which can pause distracting apps at preset times. You can also view detailed time reports to see where your child is spending most of their time.

Parentaler also offers handy content-filtering options, allowing you to block content relating to specific topics such as adult websites, social media, or any other objectionable content you don’t want your child to access.

The app allows you to view your child’s detailed browser history, helping you understand the kind of content they’re viewing online.

Additionally, parents can set up various keyword alerts, which might include commonly used slang or objectionable words. If your child ends up using them in their conversations, you’ll be able to view the alerts on the application’s dashboard.

Parentaler review: Interface and in-use

Parentaler works for Android, iPhone, and iPad, all of which come with a central dashboard accessible from any device or browser.

Parentaler’s compatibility policy page says that you don’t need physical access to the iPhone device to install the application if you already have the iCloud credentials and two-factor authentication hasn’t been activated.

However, if two-factor authentication is enabled or iCloud backup is disabled, you’ll need physical access to install the app on the target device. With Android, you’ll compulsorily need physical access for app installation.

Once the application is up and running, you’re greeted with an intuitive dashboard that lays out everything from call logs, social media monitoring, text messages, web history, and your child’s location on a single page. You can access various settings from the same dashboard and fine-tune them according to your requirements.

Overall, the platform is indeed very easy to use, with no major quirks or learning curve. That is, once you’ve successfully gotten past the installation hurdle.

Parentaler review: Support

Parentaler’s support options were honestly disappointing. We could only locate a “Contact Us” form on its website, where you need to enter your name, email, question, and message, and then wait for a response from Parentaler’s team.

Noticeably, the company’s marketing copy says that a 24/7 live chat option is available in various languages. However, we couldn’t locate any live chat button while navigating through its website.

It might be possible that you get a live chat option after you’ve purchased a plan, but the lack of proper support before committing to a purchase could be a major drawback for some parents. There’s no phone or dedicated email support either.

Parentaler review: The competition

While Parentaler is a solid parental monitoring and parental control app, there are a few features it lacks.

For instance, mSpy offers features like an anti-installation alert, where if your child uninstalls the parental monitoring app, you’ll get an instant notification. mSpy also offers remote camera and microphone access, allowing you to micromanage your child’s phone usage.

That means mSpy is great for anyone who needs a higher degree of control over what their child uses their devices for. It’s also one of the few parental control apps to offer extensive keylogging features, allowing you to see every word typed on your child’s device.

Another major shortcoming with Parentaler is that it doesn’t offer family plans. Even its annual plan, which costs around $121.99 per year, covers only a single device. This means that if you have more than one child to cover, you’ll have to buy separate subscriptions, which can quickly become expensive.

In comparison, Bitdefender offers value-for-money family plans, which start at just $79.99 for the first year, covering five accounts and 25 devices. Along with parental control features such as content filtering, internet time limits, GPS location tracking, and activity reports, you also get extra online protection tools, such as an award-winning antivirus, password manager, VPN, and decent identity protection features.

Parentaler review: Final verdict

Overall, we found Parentaler to be a decent parental control app for monitoring your children. It covers all the major bases when it comes to features, along with comprehensive text and call monitoring across various social media apps. You can also view extensive call logs and contact details on your child’s phone.

Its GPS tracking is also pretty well done, allowing you to set predefined geofencing limits. There are robust content-filtering options, so parents can keep a check on what their child views online.

That said, Parentaler doesn’t offer any family plans. While its annual plan is very reasonable at $121.99, this can quickly become expensive for households with multiple children.

It also misses out on certain features, such as remote camera or microphone access. Additionally, it doesn’t offer great support options, with only a Contact Us form available on its website. If you’re looking for more affordable or multi-device plans, Bitdefender and Mobicip can be good alternatives.

• We've also featured the best parental control software

• Huntress warns of phishing campaign abusing Adobe branding with browser‑in‑the‑browser trick
• Victims lured into fake update pages, unknowingly installing rogue ScreenConnect clients
• Attackers gain persistent remote access; defenders urged to restrict RMM installs and monitor IoCs

Security researchers Huntress have warned of an ongoing phishing campaign that abuses Adobe’s brand while deploying clever browser-in-the-browser (BitB) techniques to trick the victims.

The goal is to deliver rogue ScreenConnect clients which would grant the attackers persistent access to target devices.

In its report, Huntress says it could not find the lure itself and thus could not report what the scam looks like. However, it saw the victims clicking on a link in the email and then being redirected to a typosquatted domain https[://]adoube[.]vu that spoofs an Adobe landing page.

We heard you like browsers…

This is where we get to the scam’s unique twist. Usually, phishing lures would simply redirect victims to a malicious website which could be identified simply by looking at the address bar. If the domain differs from the legitimate one, the scam falls apart. To work around that problem, scammers came with a solution called “browser in the browser”.

Using either HTML, CSS, or JavaScript, the crooks would create an entire fake browser window, including the address bar, URL, padlock icon, and more, inside the actual webpage content itself. Therefore, if the victim isn’t all too careful, they might look at the fake address bar, see a legitimate URL, and believe they are visiting the correct website.

In this fake browser window, the fraudsters display a blurred .PDF document. Overlaid is a message saying the documents are “secured” and created with “the latest version of Adobe.” The only way to read them, the message continues, is to “update or download Adobe PDF Reader.” Expectedly, there is a big “View Files” button just under the notification, leading to a different, equally fake BitB page, showing the download progress. In the background, something gets downloaded.

Victims might think they’re getting a PDF reader, while in reality they’re getting a rogue version of ScreenConnect.

Poisoned ScreenConnect instances

On its own, ScreenConnect is not malware, or dangerous in any other way. It is a legitimate remote access and support software, similar to TeamViewer, AnyDesk, or Remote Desktop, allowing IT professionals remotely connect to and control computers and other devices. These variants, however, are tainted to enable threat actors to obtain persistent remote access to their targets’ endpoints, Huntress explained.

“The first initial remote client installed was the rogue ScreenConnect Client configured to communicate with instance-uxh86b-relay[.]screenconnect[.]com. The attacker used a legitimate ScreenConnect Trial Relay domain to further avoid detection,” the researchers said. “This initial malicious ScreenConnect Client used the native Windows command shell and curl to retrieve and install a second malicious ScreenConnect Client configured to communicate with attacker-controlled IP. Both clients established service-based persistence for continued remote access.”

After installation, the attackers used the second ScreenConnect session to run HideCursor.exe, an executable, as the name suggests, that helps the attackers hide their mouse activity.

Huntress’ researchers don’t know what the endgame is, since the threat actors were spotted and shut down in this stage of the attack. The researchers also did not share the details about the target, such as the size of the organization, or the industry it operates in. Therefore, it is impossible to even speculate on the nature of the attack and if the threat actors aimed to install ransomware.

Still, the researchers stressed the importance of training employees to “treat unexpected software update prompts and file-viewing pages with caution”, and to make sure they know how to verify downloads through trusted channels. IT teams should also restrict who can install remote-management tools, maintain an approved inventory of RMM software, and alert on new or unapproved ScreenConnect clients, unusual relay connections, and executables launched from the user Downloads folders.

Finally, businesses should monitor for Indicators of Compromise (IoC) listed on this page.

Whether it’s helping your kids improve their cyber hygiene, restricting internet access for discipline or productivity purposes, or simply keeping a watchful eye on their internet activities, a parental control app has become a much-needed defense against today’s worsening digital threat landscape.

FamilyTime is one such popular child monitoring application that gives you a granular view of the applications and websites your child visits and allows you to manage their screen time with active limits.

In this review, we’ve taken a deep dive into FamilyTime Premium’s best features, plans, user experience, and customer support to help you decide if it’s the right choice for you. Read till the end because we also compare it with some of the best in the business.

FamilyTime review: Plans and pricing

FamilyTime Premium offers a pretty straightforward pricing structure. There are three plans for you to choose from: My Family, My Family 3, and My Family 5. While the first plan covers only one device, the other two cover three and five devices, respectively.

The single-device plan costs $2.41 per month, billed at $29 annually. My Family 3 costs $4.08 per month, billed at $49 annually, while My Family 5 costs $5.75 per month, billed at $69 annually.

The good news is that there are no feature differences between the three plans – the only difference is the number of devices they cover. This means you get everything FamilyTime Premium has to offer, even with the basic $2.41 plan.

Before you commit to a paid plan, you can try FamilyTime Premium’s 3-day free trial, where you can test various features to see how they work.

However, note that the free trial isn’t particularly extensive and lacks certain features, especially social media monitoring on platforms such as WhatsApp, Instagram, TikTok, Twitch, and Signal. Similarly, you can’t read your child’s text messages or view their calls during the free trial.

That said, it’s still one of the most comprehensive free trials we’ve seen, even if it’s for a very limited time. That makes it worth trying if you’re considering FamilyTime and want to explore its features to understand whether it’s right for you.

FamilyTime review: Features

FamilyTime Premium offers a slew of features to help you manage your child’s screen time and phone usage. One of the best is its Balance feature, which gives parents a great degree of control over how much time their child spends on their device.

For starters, parents can define daily usage limits along with individual app limits. There’s also Screen Schedule, which lets you schedule limited screen time for your child during different parts of the day.

Next, the Scheduled Internet feature offers a finer level of control, letting you block internet access on your child’s device for a specific period. They’ll still be able to use non-internet apps.

What we liked the most, though, is its Time Bank function, which allows a child to carry forward their unused daily allowance. For instance, if you’ve allowed five hours of screen time during weekdays and your child uses their phone for only three hours on a particular day, they can carry the remaining two hours forward for later use.

Lastly, there’s Family Pause, which can immediately lock your child’s device in case of an emergency. In addition to extensive screen-time controls, FamilyTime also offers several safety features. For example, you can outright block apps or games that you don’t approve of on your child’s device, or block inappropriate and age-sensitive websites.

On the flip side, you can choose to allow your child to access only approved applications and games and enable search filters to block explicit websites, videos, and images.

There’s also a handy SOS Panic Button that your child can use during an emergency. When they activate it, parents receive an immediate SOS alert notifying them that their child needs help.

FamilyTime also offers a pretty nifty PickMeUp Request feature, which sends real-time reminders and lets you plan your child’s pickup on a day-to-day basis.

On top of this, FamilyTime offers several visibility features, giving you granular insights into your child’s phone activity. For instance, you can view all the contacts on your child’s device, read their text messages, and access their call logs.

Moreover, you can check the list of installed apps, view your child’s web history, and even monitor their social media activity on platforms such as WhatsApp, Instagram, TikTok, Twitch, and Signal.

Lastly, there are location-tracking features as well, which can help you locate all your family members on a live map at a glance. You can also define specific areas on the map and receive instant alerts whenever your child enters or leaves a designated zone.

FamilyTime review: Interface and in-use

FamilyTime works on both Android and iOS. Unlike some other apps that claim they can be installed remotely using iCloud credentials, FamilyTime Premium makes no such claim.

Parents will need physical access to their child’s device to download the FamilyTime Junior app, while installing the FamilyTime Dashboard app on their own device. Once that’s done, the two applications are linked by scanning a QR code.

On Android, parents will need to grant several permissions, such as overlay access and device administrator rights, and allow installations from unknown sources for all the application’s features to work.

Parents will also need to set a four-digit PIN during installation to prevent the child from removing or disabling the FamilyTime Junior app.

A good thing about the platform is that it gives children greater visibility into their own limits, allowing them to check their remaining screen time, send SOS alerts, review their Time Bank balance, and see which applications are blocked.

The dashboard itself is very intuitive and easy to use. The layout is clean and simple, and parents can quickly navigate through the various features with just a few clicks. You’ll also appreciate that the setup tutorial is very detailed. That said, the installation process won’t take more than a few minutes.

As with any child monitoring application, users might encounter occasional inconsistencies in FamilyTime’s performance, especially on iOS devices, which operate within a more closed ecosystem. That said, both applications generally work well and don’t come with a steep learning curve.

FamilyTime review: Support

FamilyTime Premium has done well when it comes to customer support. For starters, you can access 24/7 live chat through the website even before making a purchase. That lets you iron out any concerns or queries you might have. This was, in fact, one of our gripes with Parentaler, which didn’t offer live chat, at least not before purchasing a plan.

Once you’ve subscribed to a FamilyTime plan, you also get access to 24/7 Premium in-app live chat as well as 24/7 email support, which should be more than enough for most queries or issues you might have.

There’s also a rich collection of how-to articles and FAQs that provide answers to commonly asked questions. We also like that there’s a detailed collection of step-by-step installation guides and walkthrough articles covering various core functionalities of the platform.

FamilyTime review: The competition

mSpy offers more advanced features, such as keylogging, which helps you view every keystroke your child types on their device, including deleted messages and typed URLs. There’s also a keyword alerts function that can notify you whenever specific keywords are typed, which isn’t typically possible with a standard keylogger.

Furthermore, mSpy offers broader monitoring coverage across several social media platforms, including Snapchat, Tinder, Facebook Messenger, and Viber. There’s also AI chatbot monitoring, which lets you see what your child types into chatbots such as Gemini or ChatGPT.

That said, mSpy is pretty costly, starting at $11.67 per month per device on the annual plan. This can become very expensive very fast if you have a household with multiple children.

Qustodio is another strong alternative, particularly if you want a more traditional parental control app with extensive monitoring and filtering tools. It offers screen-time limits, app and website blocking, location tracking, and social media monitoring, while also supporting a wide range of platforms including Windows, Mac, Android, iOS, Chromebook, and Kindle.

If you'd like alternatives that, like FamilyTime, take a more inclusive approach, you can check out applications like Bark or HeyPolo.

Bark, for example, explicitly addresses children during setup to explain that the goal is safety, not spying. It also uses an AI alert system to flag genuine risks such as predators, cyberbullying, or self-harm, rather than handing parents a full transcript of everyday conversations for them to go through.

FamilyTime review: Final verdict

We’d recommend FamilyTime Premium for several very good reasons. For starters, it’s one of the most inexpensive parental control applications out there, with plans starting as low as $2.41 per month for a single device. Even its multi-device plans are pretty affordable, starting at just $4.08 per month.

Next, the platform offers a relatively transparent Junior app for your child’s device, where they can view their own screen time, check blocked apps, and send SOS alerts when needed. This is in stark contrast to the closed monitoring environment offered by apps such as mSpy.

You also get 30-day activity reports, location tracking and geofencing, social media monitoring, and a free trial with nearly all the available features. However, if you need even more features, such as keylogging, keyword alerts, or remote camera access, consider splurging on mSpy.

• We've also featured the best parental control software

• Bitdefender finds Google Play Early Access platform could give malicious apps an easy breeding ground
• User reviews and ratings are not publicly displayed, removing the ability for users to evaluate if an app is legitimate
• Games, casinos, and utility apps are being loaded with malicious packages and downloaded thousands of times

Google has unveiled an Early Access program for the Play Store, allowing developers to list early-access apps for testing and feedback.

While great for smaller apps looking to weed out any wrinkles in their apps, Early Access also offers a lucrative way for malicious actors to lure users into downloading apps that look legitimate, but can hide malicious packages inside.

However, new research from Bitdefender notes the fact that the Early Access program hides public reviews and ratings could lead to an app ecosystem filled with scams, fake casinos, and malware-laden packages masquerading as legitimate software.

Early Access is filled with dangerous apps

When looking for apps on the normal Play Store, one of the first things users are greeted with is an app’s rating. For fake or malicious apps, users can quickly evaluate whether or not to download the app thanks to the star rating and user reviews. While there is the potential for nefarious developers to fake reviews and ratings there is at least some ability to check if an app is legitimate.

But the Early Access system does away with public user ratings and reviews entirely. There is effectively no way for users who fall victim to a fake app to publicly warn other users not to download the app.

Add to this equation that ability for developers to show off their apps through sponsored Facebook and TikTok videos, offering outrageous rewards or using deepfakes of celebrities to entice users to install their apps.

This is especially true for fake gambling apps. Bitdefender has spotted numerous adverts for casino apps using deepfakes of well known celebrities such as Cristiano Ronaldo, Jason Statham, and Andrew Tate. These apps actively push users into the Google Play Early Access store, or direct to the apps website.

Other listings mimic well-known apps, adding financial incentives for downloading such as doubling the money you invest every time you complete a task or overcome an obstacle. Other apps take advantage of the hype for upcoming game releases, such as Grand Theft Auto V and VI. These apps often use screenshots from the actual games in order to appear legitimate.

When detected as illegitimate, these scam apps will often be deleted before being replaced by exact copies that perform the same malicious functions. Some illegitimate apps have been downloaded thousands of times, Bitdefender said, but many remain available on the Google Play Early Access store.

But the scam apps aren’t limited to games and casino apps. Bitdefender also saw numerous apps offering utility functions such as QR code scanners or PDF readers. In some circumstances, the exact same apps were listed multiple times by different developers - likely to expand the reach and maximize the number of downloads.

Bitdefender notes that Google Play’s reputation relies on users being able to trust the apps they are downloading, but the Early Access program removes almost every way users can detect a malicious app before installing.

• Matt Mullenweg accuses Automattic board of conspiring against him
• Former CEO is now in a period of paid leave
• His role at WordPress.org is currently unaffected

Automattic CEO and founder Matt Mullenweg has been placed on a paid leave of absence by the company's board, but while this is currently being seen as a temporary measure, Automattic has not publicly stated how long the leave will last.

The reason for the board's decision remains unclear, but TechCrunch reports that some employees were "ecstatic" or "relieved" at the decision.

However, Mullenweg is clearly unhappy with the decision, alleging that the board gave him 50 minutes' notice before the meeting and insufficient time to seek legal counsel.

Automattic CEO Matt Mullenweg on paid absence

Mullenweg remains a member of Automattic's board, but claimed in a company-wide Slack message seen by TechCrunch that CFO Mark Davies had "conspired" with board members Ann Dunwoody, Toni Schneider and Sue Decker to remove him temporarily. Mullenweg, a board member, voted against the change but was, of course, outvoted. Davies has been appointed interim CEO in the meantime.

"I won’t be able to make the [meeting] tomorrow. @Mark Davies has conspired with @Ann Dunwoody, @Toni, and @Sue Decker behind my back and they voted to put me on a paid leave of absence," he said.

"Matt remains the leader of the WordPress project and I remain Executive Director of WordPress. Our teams, priorities, and work continue as planned," WordPress.org executive director Mary Hubbard wrote. WordPress.com (an Automattic product) runs on WordPress.org.

While the reasons have not been publicly shared, Mullenweg hasn't been short of the odd high-profile incident in recent years. He accused WP Engine of profiting from the WordPress ecosystem, which resulted in WP Engine suing Automattic and Mullenweg.

He also offered insiders who disagreed with his direction an exit package worth either six months' pay or $30,000, mounting internal tensions.

"Matt Mullenweg is currently on leave from Automattic," a company spokesperson told us in a statement. "Mark Davies, Automattic’s CFO, will lead the company as interim CEO. The Board has full confidence in Mark's leadership and in the team's ability to execute against the company's priorities."

• New Incogni research has found that the privacy preferences of Americans don't really align with what they say
• Many of those with 'nothing to hide' will happily snoop on the phones of their family members and partners
• But those same people tend to get twitchy when handing over their phone to strangers, or their data to the government

A new survey by Incogni has found almost half of Americans say they have ‘nothing to hide’ when it comes to their privacy, but almost immediately change their perspective when it comes to strangers looking at their phone - or sharing their private messages with the federal government.

Even when offered substantial sums of money, many of those with nothing to hide still wouldn’t hand over their devices, and their personal habits such as covering cameras or installing privacy screens show a level of contradiction in what they say, and how they behave.

Of those surveyed as part of Incogni’s research, Gen Z were the most likely to say they had nothing to hide at 57%, whereas just 26% of Baby Boomers offered the same response.

Americans don't want strangers or the government accessing their phones

As it turns out, those who fell into the 45% of respondents who said they had nothing to hide were more likely to snoop on other people's devices. In fact, when polled on whether they looked at other people’s devices in public, people with nothing to hide were double as likely (42%) to snoop compared to their something to hide counterparts (27%).

Those with nothing to hide were also more likely to look through the phones of their partners and family members without permission. In fact, 41% who fell into this category admitted to snooping on their partners phones, and 35% had looked through their family members' phones.

Despite claiming to have nothing to hide, 39% still covered their cameras with tape, stickers, or sliding covers - especially those of Gen Z. Over a quarter of respondents also said that they deliberately obscure their personal information when signing up to online services with fake names, false dates of birth, and masked emails.

But the most interesting data comes from paying for privacy. 41% of those who said they have nothing to hide would pay more for a product if it was better for their privacy. But when offered money in return for handing over their phone to a stranger, 60% of respondents refused any amount of money. 20% said it would take an amount of $1 million or more, and just 6% offered access for $100 or less.

When breaking these numbers down by group, 58% of those with nothing to hide would not let a stranger access their unlocked phone for any amount of money.

Even when offered three months of their salary, just 26% of respondents would hand over their SMS, chat-app, and email messages with law enforcement. This number drops to 25% with Big Tech companies, 24% for local government, and a staggering 21% for the federal government.

Incogni theorizes that those who said they have nothing to hide may be equating privacy with secretiveness and secretiveness with guilt. It may also be true that many people fail to see how their seemingly innocent data, such as an email address or phone number, should be kept private.

As numerous data breaches have shown, the leaking of such information can lead to phishing emails, scams, and general harassment or doxxing. Incogni says that people fail to see why this information should stay private, especially in an era when social media and the websites we use hoover up as much information as possible to be sold to advertisers and third-parties.

“The findings suggest that the “nothing to hide” argument may therefore say less about how much people actually value privacy than about how difficult it is to see the consequences of losing it,” the report concludes.

• IBM and NASA launch open source AI model to help further lunar research
• Researchers will be able to better analyze petabytes of Moon data from last five decades
• IBM and NASA also release dataset for public usage and analysis

IBM has launched a new open source AI model it hopes will help spur on NASA researchers in their push to get humanity back to the Moon.

The new NASA-IBM Lunar Foundation model, available on Hugging Face, will allow researchers to analyze decades of lunar observation data, and identify geological features that are critical to understand for NASA as it looks to build a sustained human presence on the Moon.

The model has been trained by IBM and NASA researchers on a huge, multimodal NASA dataset, which will also be released alongside the model, providing wider access to the latest advanced AI systems in a bid to push on wider progress in lunar exploration.

To the Moon (and beyond)

At its most obvious level, the model will allow a much easier way for researchers to study petabytes of data gathered on the Moon's surface for potentially hazardous locations such as ice deposits or craters.

Currently, scientists often rely on manual analysis or low-resolution, task-specific AI models, which can be not only computationally demanding, but also often lack the accuracy needed for detailed geographic analysis.

The new release will now mean that instead of needing to build a new AI model for every potential issue, scientists can now adapt a single foundation model to investigate a range of lunar geologic features.

The model has already proved useful, identifying craters and volcanic features far more accurately (see below) and significantly reducing errors in locating potential ice deposits.

IBM, which has worked with NASA for over five decades, including on the Apollo missions, believes the model could help future astronauts navigate safely and even find essential resources, as well as helping scientists better understand the Moon's geological history.

“Uncovering the mysteries of the Moon requires an ability to learn from an extraordinary volume of scientific data,” said Juan Bernabe-Moreno, Director of IBM Research Europe, UK and Ireland.

“The NASA-IBM Lunar Foundation Model gives scientists a foundation to explore the Moon at scale, connecting observations across instruments, revealing patterns that are difficult to see in isolation, and providing an open platform the global research community can build on.”

The release of the dataset will mark the first time a unified, publicly-available cache has been made available and ready for machine learning. It brings together over 30 spatially aligned layers from nine instruments across four missions, including tens of thousands of images and maps showing unique geophysical properties of the lunar surface from NASA’s Lunar Reconnaissance Orbiter (LRO) and NASA’s GRAIL mission.

Identifying lunar ice deposits could be particularly vital, as the presence of both water and oxygen will be crucial to establishing a human base on the Moon, and even creating rocket fuel for future Mars missions.

Scanning the Moon's volcanic features, known as Iregular Mare Patches, can allow scientists to better understand the Moon's volcanic history and thermal evolution, as well as helping identify potential sites for landing and other surface operations.

Finally, studying the Moon's craters can offer a wealth of information on its history, including the age of different terrains, their geology, and even the chemical composition of the early lunar interior - as well as again helping to identify safe landing sites without hazards such as steep slopes and boulders.

Elegoo is running a massive limited-time sale on 3D printers right now - but for my money, the one you want to check out is the Centauri Carbon 2 Combo for $369 (was $449). And in the UK, Elegoo's multi-color 3D printer is down to £329 (was £398).

We awarded this 3D printer 4.5 stars and a TechRadar Pro Recommends badge after putting this one through its paces in our workshop. It's easily the best budget multi-color unit you can get right now.

The enclosed CoreXY printer uses Elegoo's excellent CANVAS system to print with up to four colors, while its 350°C nozzle opens the door to a wide range of materials. You also get automatic calibration, a 256 x 256 x 256mm build volume and printing speeds of up to 500mm/s.

• See the full Elegoo Day Sale

Today's top Elegoo 3D printer deal

Why we recommend it

In his rave 4.5-star review, our expert Alastair said the "Carbon 2 Combo impresses, offering one of the cheapest and most reliable multifilament machines on the market."

He summed it up saying: "Not only does it stand alongside some of the market leaders, but because it's able to handle engineering materials and has that fully enclosed environment, it is one of the best-value 3D printers on the market."

The CANVAS system is fantastic if you want to create more colorful models without manually changing filament during a print. Its four-color capability gives you much more freedom for making decorative models, signs, toys, and other projects.

The 350°C hardened-steel nozzle and enclosed chamber allow the Centauri Carbon 2 to work with PLA, PETG, ABS, and ASA, and Elegoo also lists support for PC, PA, and fiber-reinforced filaments.

For more options, take a look at our round up of the best 3D printers we've tested, including the Centauri Carbon 2 which we rated as the best budget multi-color device, and the best 3D printer deals we've seen this week.

Price context & historical value

Elegoo has reduced the Centauri Carbon 2 Combo from $449 to $369, saving you $80, or almost 18%. That's the lowest price I've found for the four-color 3D printer, matching a previous $369 deal from June. It's also on sale in the UK for £329, down from its usual £398.

There's also a discount on the optional Centauri Series Accessory Kit. It's currently $30 instead of $59.99 in the US (£40.79 down from £67.99 in the UK) when purchased as an add-on.

Should you buy it?

✅ Buy the Elegoo Centauri Carbon 2 Combo if...

You want to move beyond single-color 3D printing without spending a fortune on a multicolor setup. CANVAS provides four-color printing out of the box, while the enclosed design and high-temperature nozzle give you room to experiment with more demanding materials as your skills develop.

❌ Skip the Elegoo Centauri Carbon 2 Combo if...

You primarily produce very large models. Its 256 x 256 x 256mm build volume is ample for many projects, but bigger prints may need to be divided into multiple pieces, so a large-format printer would be a better choice.

The Catch: What to know before you buy

Elegoo quotes a maximum printing speed of 500mm/s, but its recommended speed is 250mm/s. I'd treat the higher figure as the printer's upper limit rather than the speed you'd expect for every model and material.

It's also a large machine. At 500 x 480 x 743mm and 19.35kg, you'll need a sizable, sturdy surface, particularly if you're used to a smaller open-frame printer.

• Shop all 3D printers at Elegoo

• Lenovo offers up Eva Longoria to help solve your SMB woes
• Desperate Housewives star is an entrepreneur and serial investor herself
• Users can submit questions now, with Longoria answering on her Instagram page

If you're looking for that extra bit of business support and advice, you might seek out a mentor, someone who's been there and done it all - but how about a well-known TV and film icon?

Lenovo has teamed up with Desperate Housewives star Eva Longoria, who both owns her own business, and has invested in companies involved in everything from food and beverages to media, to offer her unique advice on the issues affecting fellow entrepreneurs.

Entrants will be able to submit their burning questions to the star via a special phone number or through CallEvaNow.com, with Longoria providing assistance at a later date.

Call Eva

The "Call Eva" idea is part of Lenovo’s global Backing Every Business program, which looks to "connect entrepreneurs across the world who are facing similar business challenges, creating peer-to-peer relationships where they can exchange experiences, perspectives and practical advice".

Entrepreneurs in Brazil, France, India, Japan, Mexico, the United Kingdom and the United States will be able to take part, with Longoria selecting the most pressing to answer on her personal Instagram feed on September 16, 2026.

“One of the biggest lessons I’ve learned as an entrepreneur is that you don’t have to have all the answers yourself. Some of the best decisions start with asking someone you trust for insights, a fresh perspective or even just reassurance that you’re heading in the right direction,” Longoria said

“That’s what I love about Lenovo’s Backing Every Business initiative and now Call Eva. We’re giving entrepreneurs a place to bring the questions they’re really wrestling with, because chances are, another business owner has faced similar dilemmas. If something I’ve learned along the way can help someone better navigate a challenge, make a tough decision or take their next step with more confidence, that’s incredibly meaningful to me.”

“Technology can unlock enormous opportunities for small businesses, but technology alone doesn’t build a business. Entrepreneurs also need access to trusted advice, shared experiences and a community that understands the realities of building and growing a business,” said Emily Ketchen, Senior Vice President and Chief Marketing Officer, Intelligent Devices Group and International Markets, Lenovo.

“Backing Every Business brings those pieces together and Call Eva gives us a new avenue to extend that support while listening directly to entrepreneurs about the challenges they’re navigating. By understanding their questions, we can continue to find meaningful ways to help small businesses move forward and grow with confidence.”

Artificial intelligence is rapidly changing how software is designed, written and tested. Development teams can now use AI to generate code, produce test cases, identify likely defects and automate repetitive quality assurance (QA) tasks at a speed that would have seemed unrealistic only a few years ago.

That acceleration is valuable. But it also creates a new QA problem.

When the same class of technology is used both to create software and to decide whether that software is correct, organizations risk building a closed loop of confidence. An AI model may generate code based on a particular interpretation of a requirement, then generate tests based on the same interpretation. If the original assumption is wrong, both the code and the test can agree with each other while still failing the user.

AI, in other words, cannot be the sole judge of its own work.

This is not an argument against AI-assisted development. Errors, hallucinations and inconsistent outputs are expected features of a technology that is still maturing. The more important question is whether organizations have independent mechanisms capable of detecting those failures before they affect customers, employees or critical business processes.

Shared assumptions create shared blind spots

Traditional software assurance already recognizes the value of separation between development and testing. The people who build a system understand it deeply, but that familiarity can make it harder to challenge the assumptions on which it was built. Independent testers approach the same system from a different perspective, looking not only at what the software was intended to do but also at how it might fail.

The same principle applies to AI.

Models trained on similar data, prompted with the same requirements or operating within the same development environment may reproduce the same blind spots. A model generating a feature may overlook an ambiguous requirement, an unusual user journey or a device-specific edge case. A second model asked to test that feature may reinforce the omission rather than expose it.

This becomes particularly risky when AI-generated tests are treated as evidence of quality, simply because they run successfully. A passing test confirms only that the test’s conditions were met. It does not prove that those conditions were complete, independent or meaningful.

The result can be a technically consistent system that is practically wrong.

The most fundamental tension between generative AI and formal software assurance is repeatability. Modern AI coding agents are designed to generate and adapt. I.e. given an apparently identical objective, they may choose different steps, use different tools, interpret context differently and produce different code or tests.

This is not always because the system is learning during each run, it is also a consequence of probabilistic generation, changing context and evolving models. That variability can be highly useful when teams are exploring solutions, but it conflicts with the core discipline of QA. I.e. a controlled test must be capable of being re-run against the same version, in the same conditions, with defined expected results and evidence of a clear pass or failure.

Without that control, organizations may have AI activity rather than assurance, and outputs that look plausible, but cannot be reliably reproduced, measured, audited or defended.

Functional success is not user success

Many automated tests evaluate software through code-level signals. They check whether a service returns the expected response, whether a page contains a particular element, or whether a button can be located through an identifier or selector.

These checks are important, but they are not the same as validating the user experience. A test may confirm that a button exists even though it is hidden behind another element. It may verify that a field contains text without recognizing that the text is truncated, displayed in the wrong location or rendered in a way that makes it unreadable.

It may find a menu that is technically present but inaccessible on a smaller screen. It may confirm that a transaction completed while missing the fact that the confirmation shown to the user contains the wrong amount, account or status.

From the system’s perspective, the software may have behaved correctly. From the user’s perspective, it has failed.

This distinction matters because modern digital services increasingly depend on complex combinations of application code, browser behavior, operating systems, screen sizes, remote desktops, virtual environments and third-party components.

A change in any one of these layers can alter what appears on screen without necessarily causing a conventional functional test to fail. Testing must therefore examine not only what the underlying system reports, but what the user actually sees and can do.

Why visual validation matters

Visual user-interface validation provides an independent perspective because it tests the rendered outcome rather than relying solely on the application’s internal structure.

That independence is significant. Code-based tests often depend on knowledge of the system they are testing: object identifiers, document structures, accessibility labels, APIs or expected data responses. Visual validation can assess the final interface as presented to the user, including layout, positioning, content, state and usability across different environments.

Visual validation is not a separate phase of software assurance, nor a replacement for functional, integration, security, or performance testing. Instead, it applies across every assurance division wherever a user interface is designed, built, changed, or tested—from individual components and unit-level checks through integration, system testing, and user acceptance testing.

Functional testing confirms that an operation completed correctly; visual validation confirms that the result is displayed accurately, consistently, and remains usable. Reliable assurance requires both throughout the development lifecycle.

The need becomes more pronounced as AI generates a larger proportion of software changes. AI tools can produce code quickly, but speed increases the volume and frequency of change that quality teams must assess. Without an assurance layer focused on the rendered experience, defects can move through delivery pipelines faster than organizations can recognize them.

Visual validation acts as a check on the gap between technical execution and human experience.

Repeatability turns automation into evidence

AI is effective at generating ideas, scripts and possible test scenarios. Its outputs, however, can vary between runs. A model may interpret the same instruction differently depending on context, configuration or probabilistic variation. That flexibility can be useful during exploration, but it is not enough for formal assurance.

A test used to approve a software release must be repeatable. The same inputs should produce the same procedure, the same checkpoints and the same criteria for success or failure. Teams must be able to establish what was tested, when it was tested, which version of the application was involved and why the result was accepted.

AI is effective at generating ideas, scripts and possible test scenarios, but generative and agentic systems are not inherently deterministic controls. Their output can vary because of probabilistic generation, prompt and context changes, model updates, retrieval results and the decisions made as an agent selects tools and plans its next action. For software development, this flexibility can accelerate discovery. For formal assurance, it creates a material control problem.

A test used to approve a software release must be repeatable and auditable. The same application version, inputs and environment should produce the same defined procedure, checkpoints and success criteria, allowing teams to establish precisely what was tested, when it was tested, which version was involved and why the result was accepted.

Only then can passes and failures be measured over time, defects reproduced, and evidence relied upon in an audit or regulated setting.

This is the difference between using AI to accelerate test creation and allowing AI to become the test authority.

AI can help teams draft test cases, identify gaps and reduce the effort required to automate routine workflows. Once a test is adopted as part of an assurance process, however, it should become controlled, deterministic, traceable and auditable. Its expected results should be explicit. Changes should be reviewed. Failures should be reproducible. Evidence of passes and failures should be retained.

Without those controls, an organization may know that an AI system performed ‘some testing’ but be unable to demonstrate precisely what happened. That is a weak basis for operational confidence and an even weaker basis for accountability.

Regulated environments raise the stakes

The consequences of interface errors are not distributed evenly.

In a consumer application, a misaligned field or incorrect message may create frustration and lost revenue. In finance, healthcare, defense or government, a similar defect can influence a payment, clinical decision, operational instruction or public service. An interface that displays the wrong status, conceals a warning or presents outdated information can create consequences far beyond the screen itself.

Regulated organizations must also be able to explain and evidence their controls. It is not enough to claim that a system was tested. They may need to show that testing was consistent, that results were reviewed and that software behaved as expected in the environments where it was deployed.

AI-generated assurance that changes from one run to another makes that task harder. So does a testing strategy that concentrates on internal system responses while neglecting the final interface used by staff or customers.

Independent, repeatable visual validation can help provide a clearer chain of evidence. It shows not merely that an application returned the expected data, but that the right information appeared in the right place, in a usable form, at the point where a human decision or action was required.

This is particularly important when apparently minor presentation errors can alter behavior. A hidden warning, misplaced decimal point, incorrect unit or outdated status indicator may not prevent an application from functioning. It can still cause a user to take the wrong action.

In these environments, the interface is not simply a cosmetic layer. It is part of the operational control system.

Combining speed with control

The strongest approach is not to choose between AI and established quality disciplines. It is to assign each the role for which it is best suited.

AI can increase development speed, broaden test coverage and reduce the manual effort involved in producing automation. Independent validation can challenge the assumptions embedded in those outputs. Deterministic testing can convert useful AI-generated ideas into repeatable controls. Visual checks can confirm that technically successful software also works for the person in front of the screen.

This layered model allows organizations to benefit from AI without confusing productivity with proof.

It also recognizes that no single testing method can provide complete assurance. Code-level checks can confirm the behavior of individual components.

Integration tests can establish whether systems communicate correctly. Security testing can expose vulnerabilities. Performance testing can examine behavior under pressure. Visual validation, at all levels of UI development, can determine whether the final result remains accurate, accessible and usable.

The value comes from combining these methods, not asking one of them to stand in for all the others.

As AI becomes more deeply embedded in software delivery, assurance must become more independent rather than less. Organizations should assume that AI-generated software will sometimes be wrong, incomplete or unexpectedly inconsistent. The objective is not to eliminate every error at the point of creation. It is to make sure those errors are visible before they reach the user.

AI can help write the homework. It can even suggest how the homework should be checked. But the final mark must come from an assurance process that is independent, repeatable and accountable.

We've featured the best AI website builder.

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

• One in three workers laid off due to AI could need to be reemployed at a higher rate
• Context, judgment and meaning are irreplaceable human traits that AI can't bring
• Companies need to reinvest in AI – not just accept mediocre gains

Gartner has argued that the future of work is moving beyond simple AI automation – instead, it says that using AI to enhance human capability and redesigning how work gets done are far more critical for future business leaders.

Fundamental to Gartner's report is the importance of human workers and the preservation of human judgment and context, therefore the analysts warn that AI-induced layoffs could be costly in the long-term despite offering potential savings today.

In fact, the study warns that by as soon as 2029, one in three (30%) employees laid off because their jobs were replaced by AI will need to be rehired, and potentially at a higher cost to their future employers than had they just been kept on.

Gartner warns about AI layoffs and the importance of human workers

Ultimately, the analysts warn that treating AI primarily as a headcount-reduction mechanism could weaken future talent pipelines, remove institutional knowledge and expertise, reduce innovation ability, and create expensive recruitment challenges later.

First of the four upcoming trends predicted by the company is the human-AI relationship – companies are being urged to build stronger human-AI collaboration where AI and automation are largely seen as augmentation, not replacement.

It's also about a cultural change, because Gartner says workforces should adapt to AI, not just adopt it. Employees will need to learn continuously, adapt to changing roles and understand how to work effectively alongside AI.

Thirdly, human context, judgment and meaning should be protected, with Gartner increasingly worried that AI could inadvertently strip these away.

Finally, Gartner expects AI investments to be a continuous loop and not a single action – companies that reinvest will likely be the ones to see the best success.

"The competitive advantage will go to the CIOs and business executives who build an AI-shaped organization where AI value compounds by reshaping roles and allowing workflows to cross traditional boundaries, increasing velocity and reducing friction," VP Analyst Tori Paulman wrote.

For much of the AI boom, the infrastructure conversation has centered on compute: chips, servers and the increasingly large data centers needed to support them. But as AI moves from experimentation to deployment at scale, technology leaders face another infrastructure challenge that could be just as consequential: securing enough reliable power, quickly, to keep that compute running.

AI data centers are fundamentally different from traditional commercial and industrial power customers. They are larger, more concentrated and exceptionally time-sensitive, with near-zero tolerance for interruption. That makes energy availability more than an operating consideration. Increasingly, it can determine where AI infrastructure gets built, how quickly it comes online and whether organizations can turn enormous technology investments into business value.

Natural gas is emerging as a bridge fuel for AI's power challenge

For technology leaders, the key question isn't simply whether enough electricity can ultimately be generated. It's whether firm, dispatchable power can reach a data center when and where it's needed.

That's where natural gas is playing an increasingly important role. Given constraints on other non-intermittent power alternatives, gas can provide the around-the-clock generation needed to support large AI workloads. PwC's scenario analysis shows the potential scale: even in our most conservative scenario, AI-linked gas demand reaches 5.2 billion cubic feet per day (Bcf/d) by 2030, compared with roughly 1.6 Bcf/d today. By 2035, our scenarios put demand between 7.6 and 11.5 Bcf/d.

For data center developers and technology companies, however, those numbers tell only part of the story. Having enough gas in the system doesn't mean it can necessarily reach a data center on the required timeline. It must be produced, transported, stored and delivered at the right pressure through connected infrastructure. In other words, AI's power challenge is increasingly becoming a deliverability challenge.

The scarce resource may be time, not capital

Technology companies are committing tens of billions of dollars to AI infrastructure, but money can't quickly solve many of the constraints standing between a planned data center and an operational one.

Permitting, pipeline rights-of-way, grid interconnections, turbines, water and skilled labor can all extend development timelines. Developers are simultaneously competing for critical equipment and industrial capacity while navigating local zoning and water constraints. That changes the calculus around infrastructure.

In a market defined by speed to deployment, an existing pipeline, permitted corridor, storage asset or available generation capacity can be more valuable than a theoretically lower-cost alternative that takes years to develop. For technology leaders making decisions about AI capacity, site selection therefore needs to account for much more than land, connectivity and eventual power availability. The ability to secure reliable energy on the required timeline should be considered much earlier in the process.

Energy procurement is becoming a strategic capability

We're already seeing data center developers respond differently. Behind-the-meter generation, for example, can allow a campus to pair on-site or nearby gas generation with firm fuel supply rather than relying solely on the traditional grid interconnection process. PwC estimates that more than 30% of AI-related gas demand could be behind the meter by 2035.

Other models are emerging as well, including dedicated pipeline laterals paired with generation and more integrated arrangements connecting gas supply, transportation, storage, generation and data center load. The larger lesson for business and technology leaders isn't that every data center should pursue the same energy strategy.

It's that energy procurement can no longer be treated as a back-office function that happens after the technology and real estate decisions have been made. It is becoming a strategic capability.

Building AI infrastructure will require a broader ecosystem

This shift also changes who technology companies need around the table. The next generation of AI infrastructure will require greater coordination among hyperscalers and data center developers with utilities, natural gas providers and pipeline operators. Increasingly, these parties will need to solve for the entire path from energy supply to operational compute rather than solely optimizing their individual piece of the equation.

For technology executives, that makes partnership strategy increasingly important. Securing energy infrastructure earlier, understanding regional constraints and developing relationships across the power ecosystem can help reduce schedule risk before billions of dollars of compute are waiting for power.

AI may be a technology revolution, but scaling it is quickly becoming a physical infrastructure challenge. The organizations best positioned for the next phase will be those that treat energy as a strategic capability and recognize that natural gas can play a critical role in providing the reliable, dispatchable power needed to bring AI capacity online and keep it running.

In the race to scale AI, time to power may ultimately determine time to value.

We've featured the best AI chatbot for business.

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

Every new process, tool and approval layer carries a cost that rarely appears on a balance sheet.

Nearly 58% of professionals spend at least three hours weekly on admin, while over half find this side of work frustrating. Teams are busy and too much effort is being absorbed by the machinery around the work. Complexity can slow decision-making and make it more fragile. Speed switches off our quality critical thinking and pushes us to simply make a decision to stop the stress.

AI has made execution faster but has not necessarily meaningfully improved decision quality across the board, let alone consistently. If businesses are to make the most gains from their tech choices then they need to thoroughly reevaluate their processes and training. Basic AI use, particularly gen-AI, is not going to meaningfully grow the business versus those who take more care in tailor.

But… easier said than done. This is cognitively hard and so quite easy to neglect without even noticing. All the invisible, cultural ‘soft’ aspects of work aren’t always easily tracked and evaluated and may just be tick-boxed away if and when brought to mind. Keeping process improvement a focused aim and ensuring it evolves alongside new technologies like AI, and essential human requirements (think fulfilment, agency, flow) is not easy.

Getting it right will separate out high performers who never miss a trick from the average thinkers who scrape by.

Making big changes starts with small steps

"A journey of a thousand miles begins with a single step" is ancient wisdom echoed across many philosophies, cognitive behavioral therapy, and practical guides to business. And yet we need to be reminded of such basic principles again and again.

I’d recommend carefully cycling through the following on a regular cadence, looking at them with various departmental lenses and priorities that align with your industry, policies, customer contracts, and tech stacks. Small improvements done regularly stop drift away from best practices and organizational goals. For example:

Reducing admin. An absolute no-brainer to start with. No one likes admin, but it’s how we prove compliance and quality is taken seriously, though it’s not generally a value-add. Look at workflows as a process to be revisited at regular intervals and see what can be streamlined - while simultaneously ensuring the purpose and context of the process isn’t entirely hidden from those responsible for seeing the workflow through to completion.

Focus priorities. Do less, better, is a mantra for life. Many enterprises grow their offerings over time, but smart execs stay focused. AI tools should be used with that mindset such that all involved are uplifted to perform with excellence. There’s a place for doing everything across the board ‘X’ per cent better, but doing core delivery better by a factor is how a business delivers outperformance.

Consolidate information and reduce tool switching. This is the real bread and butter work of many a consultancy. A COO is well placed to work with the CIO and ensure that any changing data use is done smartly, without shadow AI or ad hoc workarounds that silo intelligence and ultimately make the business’ collective efforts harder for the benefit of one person or team.

Treat AI as an assistant, not a replacement. There’s definitely a cult of AI with highly inflated expectations delivering a lot of hype. AI is likely to become what they hope in time, but right now its use should be applied critically. Costs and performance are variable. Smart users are the other side of the AI ‘coin’.

With the right training in model use, prompt engineering, custom GPTs and skills, your people are given wings. Always remember though that anything can potentially happen: power cut, an API failure, a dependency removal. So if people can’t do their job without AI, then they are not in control.

Mounting hidden costs

These are the basics that many leaders build trust through clear guidance, establishing clear policies, providing regular training, sharing successful use cases, and defining where AI can add real value. But it’s rare for leaders to revisit the steps and go through a forensic process to ensure everything is still operating as intended as any part of the complex interplay changes.

With AI layered on top of data repositories, and IT infrastructure on or off premise in various types of cloud offering, businesses are dealing with a complexity that CIOs would not have dreamed of just five years ago. Staying on top of dependencies, sprawl, shadow IT, evolving models, agentic drift, and token costs, is all part and parcel of controlling costs, improving service and enhancing employee experience.

Costs of course encompass more than financial outgoings and risks. Particularly with AI-enhanced processes, the costs of time mismanagement or opportunity costs become more relevant. These pressures will encourage leaders to both research and experiment more with operations, increasingly pushing them to think more like consultants within their own businesses.

Build human intelligence too

Increasingly, I think of training as the biggest factor that will impact how AI ROI and optimal business outcomes are achieved. IT skills, systems thinking skills, the engineering mindset, and the whole spectrum of soft skills that holds together a complex organization. These are what will enhance domain expertise and allow teammates to live with the complexity of the modern business and not be fazed when it changes or aspects fail.

Employees more than ever need trained critical thinking skills to validate, evaluate and properly act on AI outputs. Producing pages and blindly trusting AI output is not going to end well, with AI slop positively counterproductive.

But underlying it all, it’s that awareness or mindfulness that will keep leaders checking and tweaking their processes to keep catching every scrap of breeze that the winds of tech and the economy send their way. AI is likely to punish the complacent as it propels the mindful to success in operational delivery.

We've featured the best online learning platform.

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

• Verdant argues some figures are overestimated by as much as 4-5x
• Steel and vehicle manufacturing are more likely to support jobs
• Megawatt growth doesn't correlate with job growth

A new Verdant report has argued data centers are unlikely to create as many jobs as many companies and reports believe – its latest estimations put all currently planned UK data centers at 10,400 permanent operational jobs, compared with the 40,200 jobs that industry body techUK projects.

techUK also claims that current data centers that are already in operation already support 24,300 jobs – a figure that Verdant contests as being closer to 4,400.

Ultimately, Verdant criticizes other estimations including techUK's for using older figures based on smaller campuses, but as data centers grow and become increasingly automated, they require fewer staff.

Are data centers actually creating that many jobs?

In short, Verdant explains that increasing automation means compute capacity can expand without employment rising proportionally, so adding another megawatt of compute doesn't necessarily mean adding a fixed number of new workers. Therefore, its rough estimation of 1.2 jobs per MW for new developments isn't hugely representative of all facilities.

The report also expects employment density to decrease further as facilities get larger, comparing data centers unfavorably to steel plants, vehicle manufacturing plants, hospitals and schools.

"The briefing concludes that while data centres may offer other benefits, employment cannot credibly be the primary justification for continued rapid build-out," the company wrote, calling for a pause on construction and wider public discussion.

All of this, of course, against the backdrop of hyperscalers investing billions to grow their capacities, with each new campus and expansion promising hundreds or thousands of operational jobs and tens of thousands of related roles across the likes of construction.

The AI infrastructure discussion is typically framed around the cost of data centers, the power requirements, and the compute needed to train and run models, including GPUs and high-performance storage. That’s hardly surprising given the eye-watering investment numbers occupying the headlines.

The other key commodity, of course, is data to fuel those models. According to Stanford University’s 2025 AI Index Report, dataset sizes for training LLMs are doubling every eight months. In practical terms, as each model is built, some data will move quickly into curation and model-development environments, where fast access is essential.

Much of it, however, will wait longer while teams establish its relevance to a particular AI use case – not sitting idle, but held securely and ready to move quickly into curation, training and transformation pipelines when needed.

From a storage perspective, this raises a point that is easy to overlook: a dataset does not need the same performance at every stage of the AI pipeline. What matters is that it is ready when it is needed – not that it sits on always-on, high-performance infrastructure throughout, which at scale becomes unnecessarily expensive.

The question for infrastructure planners, then, is not whether AI needs fast storage, but where organizations should keep the very large datasets that will be required in future, before they are ready to be processed. That choice is a strategic one, not a housekeeping one.

The right capacity tier should keep data protected and readily recoverable into AI, training and transformation pipelines, puts performance only where the work is actually happening, and returns the difference to the budget.

Your data portfolio as strategic advantage

As every organization's mission is different, so too each will be at a different stage of the AI journey. Some have raced ahead with systems already in production, while many others continue to explore how the data they already hold could support AI initiatives – documents, images and video, operational records, information collected through connected systems; the list goes on.

This is why knowing your own data is fast becoming a competitive lever rather than an IT chore. Models are available to everyone, so proprietary data is your competitive advantage – if you can access it and use it at scale.

The organizations that will move fastest are the ones that already know what they hold, where it sits, and how quickly it can be put to work. Shortening the distance between a business question and the data that answers it is now a measure of how fast a company can execute and succeed.

So data is not simply an input to AI: it is what shapes the model. The more of an organization's own data it can bring to bear, the sharper and more specific the resulting tools become, which is why the working assumption should be that almost anything the business holds is potentially useful.

The conventional approach has been to hold large datasets in a disk-based data lake until they are needed for further processing. Yet as data sets grow ever larger, so too could cost. If every candidate dataset has to live on always-on, high-performance infrastructure, cost sets the ceiling on how much data an organization can afford to keep in play at all.

The challenge, then, is to keep everything available to workflows as needed, so that the deciding factor is the use case, not the storage bill.

Tale of the tape

The smart play therefore is not to spend more, but to stop overspending where there is a better way. And it turns out one of the strongest answers here is a technology that has never stopped innovating: tape. Most people still associate it with backup and long-term archive – a role it continues to play well – but successive LTO generations have transformed its capacity, throughput and security while the industry looked elsewhere.

The latest tape technology and systems now behave like any other tier in the stack, ready to stream data into fast storage when curation or training is ready for it. And tape’s economics get better as it grows. At the multi-petabyte scale AI programs now reach, cost per terabyte is a fraction of flash or even HDD infrastructure. Performance and capacity can also scale independently, adding more drives for throughput and more cartridges for capacity.

When considered with tape’s extraordinary energy efficiency, this storage technology emerges as a strategic capability to build into the data center, allowing an organization to keep its entire data estate in play, at a cost that scales predictably.

A safer place for valuable data

Cost of storage and operation often gets projects approved, yet protection is the one that keeps people up at night. Here, tape offers something the online tiers structurally cannot. Encryption is handled in hardware on the cartridge. Write-Once-Read-Many (WORM) media makes a dataset immutable in the physical sense, so that irreplaceable data cannot be rewritten.

And for the most valuable material, tape sets can leave the library altogether and be stored in a secure location or offsite – fully offline, fully air-gapped, and insulated from anything that happens to the production environment.

What counts now in building data and AI pipelines for your organization is ensuring data is ready to move into the right performance tier the moment it is needed. Data is the fuel for the models an organization builds, the decisions it makes, and how fast it can act on either.

Tape is what makes it affordable to keep all of that ‘data fuel’ at scale, protect what cannot be replaced, and put any of it to work on demand. Build it in now, and what you can do with your data is no longer limited by what you can afford to keep online, and instead becomes the means to get, and stay, ahead of your competition.

We've featured the best cloud storage.

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 British government is using its UK Space Strategy to drive growth and reindustrialise the country
• £7.8 billion fund will back the project until 2030
• Funding will boost European rocket programs, space science and exploration, rail connectivity, astronomy and space science research, and space weather forecasting

The British government has announced a multi-faceted UK Space Strategy which seeks to “reindustrialise the country” with a £7.8 billion investment between now and 2030. Uniting a number of scientific and communications programs, the strategy is also part of the UK’s defense plans, which have been under fire in recent months.

While improved rail connectivity and satellite communications for rural communities will make a difference to everyday life, the program is largely focused on various scientific research projects, from pioneering orbital assembly and manufacturing to exploration and extraterrestrial weather.

Replacing 2021’s National Space Strategy, the UK Space Strategy is backed by two key ministers, and supported by various bodies with an interest in orbital research, science, and defene.

Research and ISAM

The £7.8 billion fund is intended for a variety of purposes, unified under the UK Space Strategy. These include a £149 million contribution to the European Space Agency’s (ESA) Vigil mission, and £880 million to improve space-based intelligence, surveillance, and reconnaissance, technologies that enable the UK to monitor military activity and protect assets in orbit.

A further £2.8 billion aims to strengthen the connectivity in Low Earth Orbit and SKYNET defense communications programs.

The UK government expects the UK’s space sector to grow beyond its current £18.6 billion value, with further funds allocated to rail connectivity (£57 million), developing SaxaVord Spaceport in Shetland (£30 million) and space science and exploration missions (£163 million). Projects like the Rosalind Franklin Mars Rover are cited in the announcement, with an indication that similar projects can be part of the reindustrialization program.

Representatives from UKspace (a space industry trade association), ADS Group (a similar body for aerospace, defense, security and space businesses), the Space Academic Network, and the Met Office have thrown their weight behind the UK Space Strategy. In addition, there is support from Joanne Wheeler, MBE, director of the Earth & Space Sustainability Initiative.

A new frontier

A pair of prominent politicians back the UK Space Strategy, with Business, Innovation, Science and Trade Secretary, Jonathan Reynolds, stating "As space becomes a new frontier of economic and military competition, this plan will help keep Britain secure by strengthening our ability to launch satellites, detect threats and protect the services people rely on every day.”

Meanwhile, Defence Secretary Wes Streeting, said: “As threats in orbit grow more sophisticated, so must our ability to detect and respond to them, ensuring we protect the interests of the UK and allies while fueling economic growth along the way.”

Streeting also referred to the Defence Investment Plan, a commitment to increase defense spending to 2.7% of GDP by 2029, as part of the UK’s move towards a NATO commitment of 5% GDP by 2035.

• Calif researchers found a zero‑click WeChat VoIP flaw enabling account takeover via calls
• “WeWorm” spreads through ringing calls; victims need not answer to be compromised
• Tencent patched in Android 8.0.77 and iOS 8.0.76; no exploitation seen in the wild

Security researchers have found a flaw in WeChat which allows malicious actors to take over people’s accounts on both Android and iOS devices - but what makes this flaw stand out is the fact that it’s a zero-click bug - victims need not do a thing to be compromised.

WeChat is a “super-app”, allegedly used by roughly 1.4 billion people, and is especially popular in China. It started as a communications app, letting users send messages, and make voice and video calls, and has evolved to function as a social network, allowing users to share photos and videos, as well as a payment app through which users can transfer money, pay for things, order food, book taxis, and even access government and business services.

Security researchers from Calif have now disclosed finding a ‘memory corruption’ issue in WeChat's VoIP stack. For now, they decided not to share the technical details, and to instead demonstrate the flaw “at an upcoming conference.” To that end, they built a worm called WeWorm, capable of taking over target WeChat accounts and spread through phone calls made via the app.

A phone call would suffice

In practice, it works remarkably simple: an attacker uses WeChat to call a person they have in their contacts list (this is a prerequisite). They can use both an Android and an iOS device, and can call anyone, regardless of the model or the OS they’re using. As soon as the phone starts ringing, WeWorm gets to work, “worming” its way into the victim’s device.

The victim does not even need to answer the phone - having it ring is enough. If they answer, they’ll hear nothing but silence, yet the worm will continue operating. If they decline the call, the attack stops, but this is hardly a mitigation - the attacker can simply call again while the victim is asleep (or otherwise away from their device).

Within a few seconds, the attacker will have access to the victim’s WeChat account, including their messages, contacts list, and virtually anything else found in the app. What makes this bug particularly worrisome on the surface is the fact that WeChat can be used to transfer money and pay for things, but WeChat Pay has additional authentication and risk controls designed to prevent that from happening.

The good news is that there is no evidence of this flaw being exploited in the wild. The bad news is that this is not the first zero-click flaw found in modern-day smartphones, and most likely will not be the last one.

Tencent's response

Calif said it responsibly disclosed its findings to WeChat’s parent company Tencent, who came back with a patch. Versions 8.0.77 for Android and 8.0.76 for iOS have apparently solved the problem, although

Tencent did not list any details in its patch notes, simply saying the version brought “bug fixes”, but in a statement shared with The Hacker News, it said the exploit has been “mitigated for all users”, and that it was applied server-side - users need not install anything, aside from the patch.

It’s also worth mentioning that WeChat has apps for HarmonyOS, Windows, Mac, and Linux. However, it would appear that Calif did not test those, and Tencent did not include them in its patch. The researchers did say that they would be looking into this same flaw in other products, too:

“This specific WeChat bug is one instance of the many unconventional attack surfaces that are present across many messaging apps,” they said. “We're conducting more of this research across other apps and attack surfaces, while working with app developers on attack surface reduction. This may take an industry-wide effort, since some of it depends on the platform owners. Once that work is further along, we'll share our progress, including the technical details of this WeChat bug.”

• A GAO report requested by Bernie Sanders lists Amazon among the top employers of Medicaid and SNAP recipients in every state that supplied employer data
• Amazon's capital expenditure guidance for 2026 has risen from $200 billion to $220 billion citing AI demand as a primary driver
• Amazon contests the findings, stating the rankings used do not account for the employer's workforce numbers

The Government Accountability Office (GAO) recently published a report claiming Amazon is among the largest employers of Americans who rely on food stamps and Medicaid.

The report, requested by US Senator Bernie Sanders, who is the ranking member of the Senate Health, Education, Labor and Pensions Committee, was released publicly on July 22 2026, a month after it was sent to the senator.

The study is not the first of its kind: the GAO published the same in October 2020 at the request of the same committee, though Amazon was far less dominant on the list at a cursory glance.

A report that paints a worrying trend, but fails to provide a complete picture

GAO collected employment records from 15 agencies across 11 states, all of them the same agencies that supplied the 2020 data, and asked for a snapshot of September 2025.

The office then estimated the 25 employers in each state with the most enrollees. The resulting document showed Amazon near the top of every list: It ranked second in five states for Medicaid enrollees, and second or third for SNAP recipients in six different states. Adding the state figures links the e-commerce giant's employee list to 11,338 Medicaid enrollees and 12,346 SNAP recipients.

The report does not, however, directly or indirectly address AI, data centers, or Amazon's Capex ambitions, or point to a particular trend as a snapshot of a single month of data, and it fails to draw a direct comparison with its 2020-based iteration.

It has drawn a sharp rebuke from Amazon, which saw its spokesperson, Rachael Lighty, tell The Washington Post that the company dealt in raw numbers rather than percentages, which was misleading, and CNN that eligibility "is based on total household income and family size, not individual wages or benefits," so an employer offering part-time work will naturally show more eligible staff.

This is something the GAO tends to accept, even in its own footnotes: a larger employer simply has more employees in play and is therefore more likely to be on that list, which is skewed against part-time individuals who are more likely recipients of those food assistance programs.

It does make for an interesting approach to the entire model, which Senator Sanders has pointed out shows "triple" the number on SNAP and Medicaid simply because Amazon's employment statistics have swung so wildly of late.

The e-commerce giant's global workforce went from about 798,000 at the end of 2019 to a peak of 1.61 million in 2021, and stood at 1,576,000 at the end of 2025, effectively doubling from when the report was originally published in 2020, potentially skewing results against itself due to a larger employee base.

The findings and the defense presented by Amazon, however, have not gone down well with certain quarters; Senator Sanders has called the trends "beyond unacceptable", stating that "American taxpayers should not be forced to subsidize the starvation wages of large corporations".

Much of Amazon's recent focus, including a significant increase in Capex spending, has been towards AI and AI-related infrastructure under its AWS arm. Amazon guided to about $200 billion of 2026 capital expenditure on its Q4 2025 call in February, up from $131.8 billion in 2025. On July 30, Andy Jassy raised that to $220 billion, blaming higher memory prices, and said Amazon would still not have enough capacity for the demand it is seeing.

AI data centers are increasingly a point of contention among AI juggernauts, hyperscalers, and less-eager locals bearing the brunt of higher water and power costs, even as availability becomes equally challenging.

For a company spending $220 billion on AI infrastructure this year and rolling out an $1 billion commitment in late 2025 to raise base pay for its US fulfillment and transportation workers, being at the top of multiple lists of states with workers being eligible for (and using) Medicaid and food assistance programs might not be great timing when there is increasing scrutiny of trillion-dollar corporations and their massive profit margins by consumers and jobseekers alike.

• The expanding market for data centers and associated renewable energy supplies has attracted the insurance industry
• Data centers alone could represent a $91 billion market
• A destroyed AI data center could cost $50 billion to replace

The cost of data centers continues to rise, with insurance now added to real estate, communications, energy, and environmental impact. Several reports indicate that not only is insurance a growing cost for big guns like OpenAI and Meta, it’s a market that looks set to expand alongside the increase in data centers.

A new report by the Swiss Re Institute indicates the insurance industry could collect $91 billion in premiums from AI data centers between now and 2030, with a further $111 billion from renewable energy installations linked to the data centers.

With a combined market of around $200 billion across a three year period, the AI boom could represent an accumulation of risk. The report highlights four interconnected factors that could affect multiple businesses if only one is disrupted.

The assurance of data centers

Reliance on new data centers isn’t all about the end product. Construction companies, physical supply chains, and technology and communications organizations all play their part in assembling an AI data center facility. Power stations – traditional or renewable – have similar requirements, and once both types of installation are brought online, their importance increases.

Gianfranco Lot, Swiss Re's chief underwriting officer for P&C Re, told Insurance Business Mag: "AI needs data centers, power grids, and increasingly complex infrastructure - and all of it needs insurance. That creates growth opportunities across multiple lines of business, but also significant risk concentrations. The deployment of capacity will depend on our ability to understand and manage those, and getting paid for the associated tail risk."

Estimates suggest a single AI data center can cost $50 billion to replace.

New market, new opportunities

Insurers are preparing to offer comprehensive support for the data center industry. Risk management firm Aon has released an analytics tool designed to help insurers measure and map exposures for data centers, and it appears the wider industry is exploring options to underwrite these installations.

Indeed, Aon has its own estimations, working on a figure of a $29 billion market by 2030. Meanwhile, other insurers and analysts are assembling databases and exploring opportunities to provide financial fallback to data centers.

Four factors (large assets, geographic clustering, supply-chain dependencies, and shared networks) can each interrupt several businesses within the sphere of the data centers, and the Swiss Re Institute report highlights the importance of insuring against disruption. This represents a previously unseen level of integration and interconnectivity between industries, something that seems to be informing the market estimates.

Ultimately, the insurance price will be factored into the usage costs, with AI token prices and other tariffs added to the bill for end users.

• AI data centers are pushing rural land prices far beyond farm values
• Local officials now face threats over decisions tied to data centers
• Farmers are receiving offers that can be extremely difficult to reject

US officials are facing threats and intense local opposition over artificial intelligence projects that are driving fierce competition for rural property and resources.

The conflict is intensifying, with developers seeking large tracts of land and residents raising concerns about electricity use, water demand, and rising property values.

In several communities, officials have faced intimidation after voting on projects, showing how contentious the expansion of AI infrastructure has become.

Threats intensify as communities resist development

In Michigan, township officials received death threats after supporting a major data center proposal involving Oracle and OpenAI.

An official said threatening messages became severe enough to make ordinary disagreements over development far more troubling.

“We’ve got a lot of recorded messages wishing us dead,” said Kelly Marion, township clerk in Saline Township, Michigan.

Officials elsewhere have faced similar pressure, with some councils delaying meetings or restricting public participation following threats linked to data center plans.

In Box Elder County, Utah, Commissioner Lee Perry said he and two colleagues received threats after approving resolutions concerning development.

The dispute has also reached Marshall, Michigan, where council members were warned about a death threat after approving restrictions on new projects.

Salix, Iowa, postponed a vote concerning development after threatening social media posts prompted authorities to investigate possible risks.

The incidents come amid hundreds of local measures restricting data center construction across different parts of the United States.

Rising land values fuel another fight

The conflict extends beyond security concerns. AI companies are now competing with farmers and other landowners for sites with suitable infrastructure.

According to commercial property firm Avison Young, data center land purchases reached roughly $6 billion during the first half of 2026.

That figure represents a 79% increase from the previous year, while data centers account for 27% of American development sites.

Some developers have offered prices far exceeding agricultural values, giving landowners strong financial incentives to sell their farms.

Texas Agriculture Commissioner Sid Miller said developers sometimes offered farmers outrageous prices for their farms.

“When [data centers] first started popping up, nobody really knew much about them,” Miller said.

“I found out real quick that they were taking up our very best farmland. ... And [developers] give sometimes 10 times the value, so it’s hard for farmers to turn that down.”

In Northern Virginia, some sites with reliable grid access have reportedly reached millions of dollars per acre amid strong demand.

The National Association of Home Builders has warned that data center developers can outbid housing companies because their financial limits differ significantly.

Meanwhile, residents fear large facilities could increase pressure on electricity networks, water supplies, roads, and other local services.

Analysts at investment banks have also warned that political opposition could become a risk for future data center expansion plans.

For communities near proposed sites, the unresolved question is whether economic gains can justify the costs associated with scarce land and resources.

Via CNBC

• Russia has launched 32 Rassvet satellites, though coverage remains limited
• Rassvet remains vastly smaller than Starlink’s expanding satellite constellation today
• Russia plans 156 satellite launches in 2026, 292 in 2027, 318 in 2028, and about 900 in 2035

Russia has launched 32 Rassvet communications satellites as Moscow works toward building a domestic network capable of competing with Starlink.

The current fleet, however, remains too small to provide continuous service, while reported orbital problems have raised further doubts about progress.

Russia still plans commercial operations from 2027, although reaching that stage depends on expanding the constellation and overcoming serious technical limitations.

Thirty-two satellites leave Russia far from continuous coverage

Ukraine's Defense Intelligence chief, Oleh Ivashchenko, said the existing constellation cannot yet deliver reliable communications across the areas Russia intends to serve.

“We know that today the Russians are trying to put satellites into orbit. But so far, there are not enough of them, and their effectiveness is low,” said Oleh Ivashchenko, chief of Ukraine’s Defense Intelligence.

Ivashchenko did not disclose the spacecraft’s orbital paths, operating frequency, or the Ukrainian regions where the system currently provides coverage.

However, he maintains that Rassvet remains far smaller than Starlink, which has more than 12,000 satellites in orbit and continues adding around 200 spacecraft each month.

The much smaller constellation means Rassvet cannot yet provide the same level of continuous coverage as Starlink.

Moscow has committed 102.8 billion rubles, or about $1.3 billion, to Rassvet as part of efforts to establish domestic broadband connectivity.

Russia plans to launch 156 satellites in 2026, followed by another 292 spacecraft by 2027, when authorities expect commercial operations to begin.

The programme ultimately aims for 318 satellites by 2028, while later plans envisage expanding the network from 250 spacecraft toward 900 by 2035.

Those figures reveal the scale of work remaining, since the existing fleet represents only a fraction of Russia's planned communications infrastructure.

Technical problems could make expansion considerably harder

Reports indicate that some Rassvet spacecraft faced difficulty gaining altitude, with certain satellites drifting downward after reaching orbit.

Defense Express reported on August 25 2026 that one Rassvet-3 communications satellite was lost, while two others faced possible atmospheric reentry.

Such incidents could complicate Russia's schedule because each failed spacecraft reduces the already limited constellation and creates additional pressure on future launches.

Building the planned network would require at least 18 Soyuz-2.1b missions, despite Russia currently carrying out only six to eight launches annually.

The launch requirement therefore creates another obstacle, especially if replacement spacecraft become necessary after further technical failures during orbital operations.

Rassvet could eventually provide communications links for unmanned aircraft and military units operating beyond the practical limits of conventional radio systems.

That possibility gained greater attention after Ukraine and SpaceX restricted unauthorized Starlink terminals reportedly used by Russian forces during February 2026.

“We are working on this. Russia’s ‘Rassvet svg’ must turn into a ‘zakat svg,’” said Oleh Ivashchenko, chief of Ukraine’s Defense Intelligence.

Russia continues developing Rassvet despite these setbacks, but the current constellation remains unable to provide continuous connectivity expected from a fully operating network.

Via United24media

• Thailand has frozen 166 data center projects pending new national rules
• Officials found major gaps in data on existing data centers
• Large data centers are putting new pressure on water supplies

Thailand has halted 166 data center projects while officials work on new rules for electricity, water, locations, safety, and economic returns.

The pause covers 49 facilities already being built and another 117 projects still waiting for approval from government agencies.

Officials say the review aims to keep attracting investment while ensuring data centers provide jobs, technology gains, and useful services for Thailand.

Thailand puts data center growth under review

The decision followed a recent meeting of the national data center policy board, which ordered four groups to draft standards within one month.

Four subcommittees will each examine a different area: economic benefits, infrastructure needs, site and location standards, and environmental protection.

The review comes after agencies found limited information about the country’s total data center activity, including facilities already running and projects awaiting approval.

Information from 16 government bodies showed that 35 data centers were operating, with 11 receiving investment support through Thailand’s Board of Investment.

Another 24 facilities gained approval through other routes, while several smaller centers were operated by financial institutions.

The government now wants one central system showing project locations, approval status, electricity sources, water supplies, planning rules, and other key details.

That system would allow agencies to examine the combined effects of multiple facilities instead of reviewing each project through separate approval channels.

Bangkok has also begun checking existing sites, with six projects seeking approval and each requiring between 9 MW and 23 MW of power.

Three received approval and began operations from 2022 through 2024, while the remaining applications will stay frozen until national standards are ready.

Water, power, and economic gains shape new rules

The planned rules will cover electricity demand, water use, site selection, construction safety, backup fuel storage, environmental effects, and distance from nearby buildings.

Officials are also reviewing whether facilities using more than 2 MW should face rules similar to those applied to industrial businesses.

Large centers need constant power and significant water for cooling, creating concerns about pressure on local networks and supplies.

The government also wants prices for water and electricity to account for direct and indirect costs linked to large facilities.

That approach is intended to prevent households and other businesses from carrying costs tied to data center resource use.

Future projects could face a competitive approval process that weighs employment, technology transfer, clean energy use, and lower greenhouse gas emissions.

Prime Minister Anutin Charnvirakul said data centers matter to Thailand’s economy, although the government lacked complete information about existing facilities and planned developments.

The government is now seeking full details on data centers so it can develop laws that will guide future investment decisions.

Rather than expanding server capacity without assessing their demand, Thailand wants to gain more value from incoming projects.

The pause does not signal an end to Thailand’s data center ambitions, since officials continue seeking investment while examining how growth should proceed.

Via The Nation

• MagNav uses Earth’s magnetic field to guide aircraft without GPS signals
• Q-CTRL uses quantum gravimetry to navigate ships without satellite signals
• Saab uses quantum timing to keep radar networks synchronized without GPS

Global positioning systems (GPS) have long served as the invisible backbone guiding ships, aircraft, and military operations across the planet.

That reliance now faces a genuine challenge, as adversaries increasingly jam or spoof satellite signals to disrupt navigation entirely.

Three organizations on three continents have each tested working alternatives within the span of a few short weeks.

A wave of independent breakthroughs

The combined progress of these teams suggests the technology is edging out of laboratories and into active field conditions.

The US Defense Innovation Unit, a Pentagon organization tasked with fielding emerging commercial technology for military use, confirmed a successful flight test of its magnetic navigation program, known as MagNav.

The route carried an Embraer 170 aircraft over the Pacific Ocean, running from Seattle's Puget Sound toward southern Alaska and back again.

After four hours and 23 minutes without satellite guidance, the system improved location accuracy by 89% compared to older backup navigation methods.

"This is a significant win for the department's quantum sensing priorities, showcasing that MagNav capabilities are no longer a distant research goal," said Kyle Norman, deputy director of DIU's Kill Web portfolio.

Separately, Q-CTRL, an Australian quantum computing firm, announced a maritime field trial in the Coral Sea; its quantum gravimeter kept location errors within one nautical mile across the entire mission.

That figure reportedly beat conventional satellite backup systems by more than ten times during the same test window.

"Q-CTRL's demonstration shows a credible path to accurate navigation without reliance on external satellite signals," said Steve Sklenka, a retired Lieutenant General with the U.S. Marine Corps.

The company’s founder Michael Biercuk added that the technology is ready now, calling it proof that quantum tools can already support active defense missions.

Radar networks join the shift

Saab UK also reported a milestone, working alongside Aquark Technologies and Britain's Royal Navy to test radar timing without satellite input.

Multiple Giraffe 1X radar units operating from separate locations kept a single, coherent air picture using independent quantum timing sources.

Engineers introduced deliberate timing errors to mimic jamming conditions, then confirmed the network recovered once synchronization returned.

"This trial is a great example of how collaboration can accelerate innovation," said Andy Fraser, Group Managing Director at Saab UK.

Jason Ralph, a professor of electrical engineering at the University of Liverpool, noted that gravity sensing remains the only passive alternative technology that works globally and resists jamming or spoofing attempts entirely.

The trials arrive amid rising concern over deliberate satellite interference, with roughly 978,000 jamming events recorded worldwide during the first quarter of 2026 alone, most concentrated in the Middle East.

Taken together, these three trials suggest quantum navigation is edging closer to practical deployment rather than remaining a theoretical concept.

Whether it can fully replace GPS, rather than simply back it up during outages, still depends on further testing and cost considerations.

• OpenAI is leading the race to “quietly” open a data center in the Patagonia region of Argentina
• Argentine energy giant Pampa Energia is in talks to develop a 500 megawatt data center site
• The Loma de la Lata thermal power plant would provide the data center’s electricity, burning gas from the nearby Vaca Muerta shale gas formation

OpenAI is among several cloud and AI computing companies looking at Argentina’s Patagonia region as a possible location for fuss-free, opposition-avoiding data centers. Supported by low temperatures to aid cooling, and a clean energy source, a suitable site is currently being explored, following OpenAI signing a letter of intent with Sur Energy in 2025.

The OpenAI-Sur Energy partnership appears to have sparked growing attention on Patagonia, where other major hyperscalers are also said to have shown interest -- these include Google and Apple.

Widespread opposition to data centers in the US have prompted companies like OpenAI, Google, Apple, and Meta to look elsewhere to develop their cloud and AI facilities. However, communications limitations may prove difficult to overcome, and there is uncertainty about Pres. Javier Milei’s long-term future, factors which may explain OpenAI’s slow pace on the project.

Letter of Intent

While OpenAI and Sur Energy initially formalised their collaboration with a letter of intent in October 2025, there seems to have been little movement toward selecting a site, let alone breaking ground.

Sur Energy and Pampa Energia are not direct competitors. Rather, Pampa Energia is a large independent energy company, whereas Sur Energy is a specialized developer within the energy industry. Both organizations would typically be involved with the development of a data center in Patagonia, whether OpenAI’s Stargate Argentina or a rival build. Similarly, many other companies could be involved. For example, FlexDomes is reportly looking for investors into a data center in Patagonia.

Developments in Patagonia may not be limited to the energy from the Vaca Muerta shale field. Hydroelectric may be selected as an alternative; elsewhere, Green Capital is looking at wind and solar farms for a possible site in the Chubut province.

Will it really be easier?

However, whether Sur Energy provides the OpenAI plant with energy or Pampa Energia successfully attracts a data center from a rival cloud AI company, there remains a couple of key challenges.

While Argentina offers tax breaks and regulatory stability with its investor-pleasing RIGI incentives, shale gas energy, and minimal resistance to large projects with an ecological impact, it does not currently have the data links required to make a modern data center viable. That requires considerable investment in upgrading and (for large areas) installing fiber links.

But there is another potential challenge to establishing a data center in Patagonia. Less “anti-data-center” and more “anti-development,” the local area is occupied by the Mapuche Indigenous families, who have previously sued oil giant Exxon, French company Total, and BP-owned Pan American Energy for contracting an Argentine company that dumped waste illegally. Switching data center development to Argentina may have more attractive power and cooling options, but it is not without challenges for OpenAI and its competitors.

• Multiple states have revealed tax exemptions have cost more than $1 billion in lost revenue, more than 10 times some estimates
• Data centers are 'playing God' with their frontier models and need to face more regulation, Bernie Sanders says
• An Act issuing serious consequences, such as prison time and 'corporate death sentences', has been submitted

For many states across the US, the best way to lure lucrative investment from big tech companies was to provide tax exemptions on the equipment they would buy to furnish their data centers.

Before the AI data center boom, this was seen as a fair trade for citizens and politicians alike. But now that multiple states have revealed they have missed out on billions in tax revenue the tune is quickly changing.

Coupled with the growing national opposition movement, revelations that numerous construction sites have been using illegal generators, and frequent breakouts of AI models undergoing testing, it's no small wonder that politicians across the country are calling for greater regulation and greater taxation on big tech and AI.

‘They seem to have more money than God’

Ohio is the catalyst for this exemption withdrawal. The state projected the tax exemptions would cost them just $136 million in lost revenue for 2026 - a worthy cost to attract new investment and potential jobs for a state that has seen a long-term decline in its traditional industries and slow recovery following the 2008 financial crisis.

The loss in tax revenue turned out to be $1.6 billion - 10 times more than expected, or just over 5% of Ohio’s total tax revenue for the 2026 fiscal year. Following the revelation and associated public fallout, Republican Gov. Mike DeWine issued a pause on applications for the sales tax exemption.

But Ohio representatives, such as Democratic Rep. Tristan Rader, believe there is more to be done. Rader has called for a renegotiation on the tax exemptions offered to hyperscalers such as Amazon, Meta, and Google. “They seem to have more money than God and they’re able to build without the need for these types of incentives,” Rader said (via WSJ).

Rader is now calling for AI data centers and their respective companies to face additional requirements before projects are approved, including higher taxation and requirements that companies pay more for the energy infrastructure they rely upon.

Ohio isn’t alone in losing out on such a significant sum. In 2021, Virginia’s data center tax exemptions were predicted to cost $57 million, and Georgia predicted a tax revenue loss of just under $500 million in 2025. Both states have revealed their data center tax exemptions have led to a tax revenue loss of almost $2 billion each. Texas has seen just over $1 billion lost in tax exemptions for data centers.

But extra taxes aren’t the only repercussions hyperscalers and AI companies are facing.

‘We can’t allow a handful of greedy people to play God’

Senator Bernie Sanders has renewed his calls for greater regulation on AI technologies. Meta, OpenAI, and Anthropic have all recently revealed that their frontier AI models have escaped testing environments and wreaked havoc on third-parties.

There are also concerns that the guidelines behind the Trump administration's testing of AI tools could be hiding corruption, with Sanders stating that the control of AI technology is driven by “oligarchy & the power of Big Tech billionaires”.

In a post on X, Sanders wrote, “We can't allow a handful of greedy people to play God & determine the future of humanity.” Sanders also said that “CONGRESS MUST ACT” in a post accompanying the announcement of the Ban Artificial Superintelligence Act, sponsored by Sanders and Rep. Greg Casar.

The act seeks to pace US artificial intelligence development in line with international agreements, and implement export controls that would prevent AI superintelligence being developed anywhere in the world. The ultimate goal of the act is to prevent the development of AI technologies that exceed humanities control.

Casar added that, “Despite its potential deadly consequences, cutting-edge AI technology is less regulated than the average food truck.”

The Act also goes a step further than previous attempts at regulating AI. Companies and individuals who fail to align themselves with the Act’s regulations would face repercussions such as prison sentences of up to 20 years and, as Sanders put it, a “corporate death penalty”.

Engineering students don't need a workstation-certified laptop to run CAD software, but they do need dedicated graphics, enough RAM to keep SolidWorks or MATLAB from choking, and a processor that will not throttle the moment a simulation gets demanding.

And for students on a budget, the best pick right now is the Lenovo LOQ 15, down to $1000 (was $1500) at Best Buy.

This configuration packs in an AMD Ryzen 7 170 processor and an RTX 5050 GPU, alongside 16GB DDR5 RAM, 512GB SSD, and a 2K display. All in a 15.6in chassis that stays practical for daily carry between classes.

Why we recommend it

The RTX 5050 is the headline here. Most budget laptops in this price range settle for entry-level integrated graphics or an older, weaker discrete GPU, but the LOQ pairs a current-generation Ryzen 7 chip with an RTX 5050 that comfortably exceeds what CAD and simulation software like AutoCAD, SolidWorks, and MATLAB actually need.

That's why our engineering laptop guide singles out the LOQ line as the best way to get real GPU acceleration without paying workstation prices.

16GB of DDR5 RAM is the practical minimum our guide recommends for engineering coursework, and the two SODIMM slots mean you can upgrade later if a heavier workload demands it.

The 512GB SSD is on the smaller side for students who install multiple large engineering suites, so it's worth budgeting for an external drive or a future upgrade.

The 144Hz display and G-Sync support also mean this laptop isn't limited to class hours. It doubles as a genuinely capable gaming machine, which is a fair trade for students who want one computer instead of two.

For more picks, including the LOQ 15, see our guide to the best laptops for engineering students.

Price Context & Historical Value

A $500 drop from $1,499.99 to $999.99 is a 33 percent discount, and it puts a laptop with a current-generation RTX GPU under $1,000, which is rare.

Budget engineering-capable laptops with dedicated graphics typically start closer to $1,100 to $1,300, so this is a meaningful price for the specifications.

Should you buy it?

✅ Buy the Lenovo LOQ gaming laptop if... you are an engineering student who needs a dedicated GPU for CAD, rendering, or simulation work without workstation pricing; you want a 144Hz display for gaming between study sessions; or you need a laptop that can grow with you through a full course load without stuttering on demanding software.

❌ Skip the Lenovo LOQ gaming laptop if... you need more than 6 to 7 hours of battery life away from an outlet, your program requires a certified mobile workstation (ISV-certified drivers for tools like SolidWorks), or you would rather have 32GB of RAM from day one for heavier multitasking.

The Catch: What to know before you buy

Battery life is the trade-off. Gaming laptops in this class typically last 6 to 7 hours under normal use, so this isn't the laptop for students who need all-day battery life without access to an outlet between classes.

While we haven't reviewed this exact configuration, we have reviewed the previous AMD-powered Lenovo LOQ 15, and the machine remains our top choice budget laptop for engineering students.

Also worth noting that students with programs that require ISV-certified workstation drivers should confirm compatibility before buying.

• Shop all laptop deals at Best Buy.

• The city of El Reno, Oklahoma, has condemned a Bitcoin mining site after roughly 3.8 million gallons of water leaked, affecting schools, businesses, and even the county courthouse
• The leak happened despite a stop-work order issued by the city in 2023, which it never followed up on or attempted to enforce
• The water came from an unpermitted private fire hydrant and suppression line, even as the mining facility remained, as per filings by the operator, air-cooled for its operations

A city of roughly 20,000 people in central Oklahoma spent two days hunting for water that was pouring into the ground at an alarming rate.

When crews finally traced it, the source was a fire hydrant nobody at City Hall knew existed, on the grounds of a Bitcoin mining site that had been ordered to stop building three years earlier but had never followed through.

The city of El Reno has now condemned the property, issued a ten-day abatement notice, and scheduled an administrative hearing for September 14 2026.

Flaws in the handling of its own orders

City officials say the leak came from a private fire hydrant and the suppression line feeding it, not from cooling equipment. KFOR reported that Athlon had told El Reno its hardware was air-cooled and would not need water for cooling, and that the line in question was supposed to serve fire protection only.

Interim City Manager Ken Brown told reporters roughly 3.8 million gallons were lost, revising up an earlier estimate of about three million. The property is owned by Athlon BT, described in Canadian County assessor records as a company running data centers for AI storage and Bitcoin mining, and its structures are logged as mobile mining containers.

The company identifies itself as "Athlon Blockchain Technology Corporation" on its website, which is currently undergoing "scheduled maintenance" and is under fire for what is being seen as an unauthorized or unplanned water hydrant.

Ironically, the company has, at least on its website before it went dark recently, advertised "hydro-cooled solutions" in addition to its air-cooled offerings, which should raise a few eyebrows about its current claim, even as the brunt of the focus lies on the city's failure to shut down the endeavor.

The offending hydrant was installed without notifying the city, does not appear on municipal records, and was reportedly found concealed under a large pile of brush.

Brown said the city issued a stop-work order in June 2023 citing electrical, construction, and fire safety violations, along with expired building and electrical permits; gave Athlon until December 2023 to comply; and then never followed up. The company consequently continued building and, the city believes, began operating without a certificate of occupancy.

It doesn't help matters that there is little, if any, information about the operator beyond its website, which is currently under maintenance. KFOR's Spencer Humphrey traced the company to founder and CEO Tony Jiang Shi, a Stanford graduate based in Palo Alto who has registered several other LLCs used mostly for real estate.

The city has, for its part, claimed that residents will not pay for any of this and that it will bill the property owner for water, overtime, and equipment used to locate and repair the leak.

Finding the owner might be easier said than done, however; county records list Athlon's address as an El Reno house a couple of miles from the site, which the station found apparently abandoned, with packages piled on the porch addressed to Shi. Calls and emails from multiple outlets have gone unanswered, and Athlon has issued no statement since the situation started.

Modern laptops might've tried to kill off the built-in optical drive, but physical media is far from dead. Case in point: the Dell DW316 Slim external USB DVD-RW drive for $39 at Amazon.

Physical media is making a serious comeback (my hardware editor, with his massive library of films, games, and books, argues that it never went away). In fact, this Dell USB writer proved essential when I wanted to watch my wedding video from 20 years ago, which was locked on DVD.

If you need to rip CDs and DVDs, access archived files, or just kick back and watch a movie, the USB-powered Dell DW316 is an easy recommendation from me. In the UK, the Dell DW316 is £37 (was £50) for an imported drive, or £47 for one sent from the UK.

• Dell DW316 is also available for $40 (was $50) at Best Buy.

Why we recommend it

I put the Dell DW316 to good use myself this year when my wife and I celebrated our 20th wedding anniversary. As I mentioned, our wedding video is still on DVD and this gave us an easy way to watch it again.

Beyond digital nostalgia, it's a really practical upgrade to access older software, music, movies and other physical media that would otherwise be left gathering dust.

And unlike files stored on a computer, in the cloud or on a storage device, data burned to a write-once disc can't be accidentally deleted, overwritten or changed, giving you a permanent physical copy. Write-once media can create a physical copy of important documents, photos or other files that can be kept offline and separate from your computer.

The drive is just 14mm thick and weighs 200g. Power comes directly from your laptop's USB port, eliminating the need for a separate power adapter. It can also create discs using CyberLink Media Suite 12 which comes supplied free.

Price context & historical value

This drive has never been priced above $52 (at least, not since 2015), while its lowest price was $16 back in 2020. General trends show it more or less holds its price at around the $35 to $40 mark. For comparison, Dell's external disc drive is also available at the same price, $40 (was $50) at Best Buy.

Should you buy it?

✅ Buy the Dell DW316 if...

You occasionally need to access old CDs, DVDs or disc-based software, or want an inexpensive way to create physical copies of important files. The drive's small size means you can keep it tucked away until you actually need it.

❌ Skip the Dell DW316 if...

You need Blu-ray support or regularly work with large amounts of data. DVDs have limited capacity compared with modern storage devices, and this drive can't read or write Blu-rays.

The Catch: What to know before you buy

The DW316 connects over USB and is an older optical-drive design, so don't expect the transfer speeds you'd get from an external SSD or flash drive. Its purpose is accessing and creating optical media rather than moving large files quickly.

You'll also need compatible blank writable discs if you intend to use it for backups or archiving, adding a small additional cost on top of the $35 price.

• Shop all CD/DVD drives at Amazon

• 3 points

Data centers across the United States have been criticized for harming local environments sourcing power - sometimes illegally - from gas burning turbines that can release harmful pollutants into the air surrounding local communities.

But dozens of data centers have been accused of releasing harmful chemicals, heavy metals, and rare bacteria with the wastewater they release into nearby treatment facilities and waterways.

Violations have been logged for data centers in Wyoming, Virginia, New York, and Georgia, but the problem likely extends far across the rest of the US. Information on water usage and discharge for many data centers is hard to come by - or is being actively blocked.

Pollutants released into water across the US

In Wyoming, Meta was recently forced to halt water discharges from the construction site of its enormous 960-acre Cheyenne campus after a resistant bacterium - Cupriavidus gilardii - was found within a local water treatment facility.

The bacterium was identified after regulators tested a sample of the 801,000 gallons Meta had discharged into Cheyenne’s sewers. Following concerns that local residents could inhale droplets of the contaminated water if it was used for irrigation, local officials decided to stop accepting wastewater from the construction site.

Two water treatment facilities were forced offline as part of a multi-month decontamination and cleanup operation. Meta’s contractor responsible for the site, Goat Systems, is appealing the decision of officials to stop accepting wastewater from the site.

Multiple data centers across Virginia are facing enforcement actions from local authorities for violating wastewater and wetland regulations. In one such case, a data center under construction in West Virginia has funneled stormwater runoff into a local residential area, causing flooding on two occasions.

A data center near Lake Seneca, New York, is facing criticism from the Seneca Lake Guardian organization. The site was previously a cryptocurrency mining data center, but has been transitioning towards handling AI workloads instead. Seneca Lake Guardian has said that wastewater from the site flows directly into Lake Seneca at temperatures of up to 108F (42C), which can harm fish living in the lake and cause blooms of toxic algae.

The company behind the data center, Vulcan Infrastructure and Power, says it complies with all relevant environmental laws.

Multiple new data centers in Georgia have been approved to draw water from the Chattahoochee river, but local environmental guardians, such as water policy director at Chattahoochee Riverkeeper, Chris Manganiello, are being blindsided by a complete lack of information on how much water will be taken from the river, and what will be put back in.

“We need to know what is in this wastewater but there is a void of information,” Mangeniello told The Guardian. “I would like there to not be more Pfas [forever chemicals] going into the river but there is this level of anxiety because we don’t know what’s there.”

Don’t throw the Pfas out with the cooling water

Data centers pump water through miles of pipes crisscrossing their hardware in order to draw away excess heat. While there have been moves towards “closed-loop” cooling technology - where the water used is recycled within the system - there are still valid environmental concerns associated with these systems.

Before using a closed-loop system, the pipes need to be flushed through with water to wash away any debris or contaminants that were deposited within the pipes during assembly. This water is then released back into sewers to be cleaned by local treatment plants.

But many water treatment plants simply aren’t built to handle filtering water that contains industrial contaminants. These contaminants can include heavy metals or Pfas that can cause health problems in humans and animals.

Data centers are also being built in drought-hit regions, largely because the land is cheap, placing additional strain on already struggling water tables. Data centers can use hundreds of thousands of gallons of water per day to stay operational, and while closed-loop systems ensure this water is only taken out of the cycle once, it is still a significant sum of water to remove from regions experiencing droughts.

• Microsoft has fixed no fewer than 974 vulnerabilities in its latest Patch Tuesday release
• Two were already being exploited in the wild, 114 categorized as 'Critical'
• AI is to blame for boosting CVE discovery and also intensifying attacks

Microsoft's September 2026 Patch Tuesday has become its biggest security release on record, with the company issuing fixes for a staggering 974 vulnerabilities across the entire stack.

According to the company's release notes, an overwhelming majority (723) of the vulnerabilities addressed related to Windows, with Office coming in at second place with 111 of its own vulnerabilities being addressed.

While it's clear that the number of vulnerabilities is going up year-over-year, it's likely that the company was also simply able to find more of them that would otherwise have slipped through the net thanks to AI-assisted discovery tools.

This is Microsoft's biggest Patch Tuesday ever

Speaking about the September 2026 Patch Tuesday in a blog post, Dustin Childs explains that this could be the start of the "new normal." Childs goes on to reveal that Microsoft has patched 2,760 CVEs this year to date – more than double any other year that precedes it.

Childs' figures show that the company patched 1,139 CVEs in the whole of 2025, and a much lower 492 a decade ago in 2016. According to the post, 114 of the vulnerabilities patched in this latest update were 'Critical' – more than one in 10.

In its own notes, Microsoft described CVE-2026-85880 and CVE-2026-81963 as especially notable because they're both being actively exploited, hence the push to get them fixed and for customers to install the update.

Elsewhere in the industry, Microsoft isn't the only company addressing a higher volume of bugs. Childs also highlighted high activity from Adobe, while a number of browser developers including Google, Mozilla, Brave and Microsoft itself have doubled the release cycle to two weeks in order to get fixes into customer hands more quickly.

Besides fixing exploitable bugs, Microsoft also used the opportunity to issue fixes to known issues – including fixing Teams and Outlook crashes on Arm64 PCs – as well as to upgrade Copilot+ AI components.

• CISA, NSA, FBI warn Chinese AI firms of industrial‑scale knowledge distillation
• Companies like DeepSeek, Moonshot, Alibaba allegedly extracted billions of tokens from US frontier models
• Advisory urges detection of malicious prompts, deceptive responses to distillation, and cross‑provider intelligence sharing

Chinese AI companies’ core development strategy is to steal proprietary functionalities and capabilities from their US counterparts, law enforcement agencies have warned.

The US Cybersecurity and Infrastructure Security Agency (CISA) has published a new security advisory, drafted jointly with the National Security Agency (NSA) and the Federal Bureau of Investigation (FBI), warning American AI companies about an ongoing “aggressive, malicious, and targeted distillation activities at an industrial scale,” and sharing recommended mitigation steps.

Knowledge distillation

IBM defines knowledge distillation as a “machine learning technique that aims to transfer the learnings of a large pre-trained model, the ‘teacher model,’ to a smaller ‘student model’.” It is used in deep learning as a form of model compression and knowledge transfer, it added, particularly for massive deep neural networks.

So, knowledge distillation is not illegal or malicious, per se. Its goal is to train a more compact model to mimic a larger, more complex one. In the security advisory, the agencies stress it is “recognized as a legitimate and useful technique in AI research,” but add that China-based AI companies are using it in ill will.

In other words, the agencies claim that instead of spending months and millions developing new capabilities for their models, the Chinese are simply sending huge numbers of carefully designed questions to US models and extracting the answers.

Which companies are engaged in knowledge distillation?

Apparently, all companies worth anything. DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.AI all allegedly “extracted billions of tokens across millions of exchanges/requests from US frontier AI models, including variants of Claude, GPT, Gemini, and Grok, since at least late 2024.” CISA also stressed that this was likely done with the awareness of the Chinese government. It hasn’t outright said, “with its blessing”, although it could be read between the lines.

The advisory shares a thorough list of all the models that were being trained, as well as all the models being taken advantage of.

On the Chinese side, they include DeepSeek R1 and V3 models, Moonshot’s Kimi-K2 and Kimi-K3 models, and MiniMax’s M2 model. On the US side, they start with earlier models such as GPT-4, Claude 3.7, and Gemini 2.5 Flash Preview, all the way to Claude Fable 5, GPT-5, and similar.

When done in good faith, knowledge distillation is not illegal. However, the report says the companies routed the requests through multiple accounts, different API access points, multiple cloud providers, third-party AI aggregators, proxy services and “transfer stations”, as well as premium subscriptions shared between developers, all in an attempt to work around defenders trying to disrupt the process.

“This represents systematic extraction of proprietary functionalities and capabilities threatening U.S. technological leadership. Addressing industrial-scale distillation merits a coordinated response across the AI ecosystem, including effective information-sharing, spanning the U.S. Government, private industry, and allied nations,” the agencies concluded.

What US companies should be doing

To defend their intellectual property (and thus remain ahead of Chinese competing models) US AI companies should implement comprehensive detection and mitigation, the agencies said. That means hunting for anomalous and malicious prompts, accounts, networks, and behaviors. Furthermore, they should monitor subscription-to-usage ratios, immediate maximum usage from new accounts, and enterprise-scale throughput patterns.

The second step is to “deploy targeted response changes”: “Subtly alter responses for suspected malicious distillation attempts to attenuate the payoffs to companies conducting industrial-scale distillation campaigns.” In other words, AI companies should make sure their products lie when they spot they were being distilled for knowledge.

Finally, US AI firms should set up cross-organization intelligence sharing, correlating activity across model providers, cloud platforms, and API aggregators.

The bottleneck on sophisticated cyber operations that target nation states is breaking. Conducting a large-scale cyber attack used to mean scaling expert talent.

When the cost of adding a capable attacker approaches the cost of compute, the economics of offense fundamentally change.

This is already operational: Dream's threat research recovered an autonomous multi-agent framework that ran intrusion campaigns against government entities in Asia, executing twelve attack waves in four days with eight parallel agents, compromising 85 government accounts, and using a closed learning loop to adapt after failure.

The advantage is shifting from the number of experts to how effectively their expertise can be scaled.

AI benefits both attackers and defenders, but defenders start with a unique advantage: they already own the map attackers must discover.

Defenders that understand their environment can use AI to turn that knowledge into operational scale.

The Autonomous AI Government Hacker

In July, our threat research team recovered the operational workspace of an autonomous multi-agent framework that had been conducting intrusion campaigns against government entities in Asia.

Over roughly four days, the framework executed twelve attack waves and ran up to eight AI agents in parallel. Built on the publicly available Hermes and OpenClaw frameworks, it compromised 85 government employee accounts and used 84 of them to pivot through a government single sign-on environment.

What’s really intriguing is its autonomous operational decision making.

Assigning confidence scores

Every discovery was assigned a Bayesian confidence score to assess different paths and then chose how to proceed, just like an actual team.

Similarly, when an attack path failed, the framework automatically entered what it called a Learning Cycle, searched vulnerability databases and security research techniques relevant to that government's technology stack, and tried again. The framework audited itself – it created a closed learning loop: investigate, validate, act, observe the result, update its operational knowledge, and try again.

This was not a self-improving model. It was a self-adapting cyber attacker – there is a real expert behind it, embedded as AI system. The fundamentals of this attack weren’t even particularly impressive or novel. It is the scale – and the prospect for nearly infinite scale – that is daunting.

Until recently, one of the limiting factors in scaling sophisticated offensive operations was the expert reasoning required to decide what to investigate, validate findings, connect them into viable attack paths, and adapt when those paths failed. It was expensive, both in dollars and in expertise. That scarcity placed a natural constraint on offensive scale - scaling a sophisticated operation meant scaling skilled people, time and coordination.

AI is beginning to automate precisely that expensive layer of the operation: deciding what to investigate, validating hypotheses, learning from failure and choosing what to try next. Talent still determines the quality of those decisions. But the number of talented people no longer has to determine how many times those decisions can be made in parallel.

What happens when scaling an offensive operation no longer requires scaling the number of experts behind it at the same rate?

As someone who has spent 15 years in both offensive and defensive cyber roles, it’s becoming clearer every day that AI has changed that equation - the historical relationship between the amount of expert talent an organization has and the scale at which it can operate is beginning to break down.

AI does not eliminate talent - it changes what talent can scale.

An Attack Surface the Size of a Country

Government IT infrastructure is an interconnected ecosystem built over decades. It consists of ministries, municipalities, operational technology, legacy applications, cloud services, contractors, suppliers, and countless trust relationships connecting them together.

These connections typically exist for legitimate operational reasons (or at least historically legitimate reasons).

Of course, every connection is also a potential vulnerability.

This is how modern government attacks spread - not necessarily by exploiting one critical vulnerability, but by chaining together many ordinary ones.

Historically, this challenged both sides. No defensive team could continuously reason over every asset, identity, configuration, vulnerability and trust relationship across an entire country. But attackers faced a version of the same constraint. Their experts also had to decide where to spend their time to find a viable path from intrusion to crown jewel

Autonomous systems change that.

An autonomous attacker does not need to understand the entire government environment in advance. It can explore it continuously: discover a relationship, form a hypothesis, test it, learn from the result and move to the next one.

For the first time, governments may face adversaries capable of reasoning over national-scale attack surfaces faster than the institutions responsible for defending them.

The Race to Change the Outcome

The dramatic decline in the cost of offensive cyber expertise, via leveraging and weaponizing agents, is a tectonic shift. Until now, this was a skill limited to a select few and came with a high price tag.

Today, discovering, prioritizing and combining these techniques into viable attack paths is cheap, and one can repeat the process at machine speed.

With the pace of AI development, that statement becomes more true every day.

Offensive capability is becoming cheaper, faster and easier to reproduce.

But there is another side to this equation.

Defenders have always had structural advantages: more telemetry, deeper context, persistent access to their infrastructure, and knowledge of its configurations, identities and relationships, while also have a much better ability to act.

They too had the constraint of human capacity. No team could continuously reason over all that information, across every asset and relationship, all the time. The same AI that benefits attackers may operationalize defender’s historical edge at scale too.

This is where time plays a key role. Analyzing everything is not the same as defending everything. If AI detects a compromised identity in seconds but the credential remains active for six hours, the attacker still has six hours. If it identifies an exploitable path to a critical system but remediation takes three weeks, that path remains open for three weeks.

The opportunity, then, is not simply better analysis. It is reducing time-to-effective-action: the time between understanding a risk and changing the outcome.

And "effective" matters- disabling an identity, changing a firewall rule or patching a vulnerability is not enough. The system must verify that the attacker can no longer achieve its objective.

The defensive loop cannot end with intelligence - or even with action. It has to end with a verified security outcome.

The Gap That Matters

AI does not inevitably favor the attacker.

The framework we recovered had to steal its map of the environment, one probe at a time. Defenders already have that map. Every configuration, credential, telemetry stream and trust relationship could take an attacker – even an AI attacker – days to weeks to discover. What defenders could never do was reason over all the assets they had, continuously, due to the lack of talent capacity to do that.

AI begins to remove that human-attention constraint. It allows defenders to amplify expert talent across thousands of investigations in parallel, continuously identifying attack paths, prioritizing those that pose the greatest risk, and focusing action where it matters most.

Attackers get the same leverage. But they don't start from the same place. Defenders have a home-field advantage: they already know and control the environment the attacker must discover.

The gap that matters is no longer simply the number of experts on either side. It is how effectively each side can scale that expertise- and direct it toward the right risks first.

Ultimately, the race is not about who can know more.

It is about who can scale talent in the right way- and turn that scale into an outcome first.

We've ranked and reviewed the best antivirus software available.

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

Over the past few years, I've become absolutely fascinated and have fallen in love with BenQ monitors. I love how they have become more Apple-esque, yet they include some features that most people wish Apple would add to their monitors. While I would love to have a studio display someday, I think that the quality would be amazing.

I am absolutely loving my MA series monitors across several of my workstations. I'm still loving my MA320U on my main desk in my home office studio, but the MA270S has made its home as the vertical monitor in my setup, where I currently have my RD monitor as well.

This panel is unbelievably crisp, integrates with everything in my DisplayPilot 2 app, and offers extra ports. It's got a halfway decent speaker for virtual meetings, though I wouldn't listen to music through it beyond background lo-fi. All around, this monitor has been an absolute treat for a ton of reasons.

BenQ MA270S: Price and availability

The BenQ MA270S retails for just under $1,000 on BenQ's website. It's also widely available from online retailers, including Amazon.

If that price doesn't scare you and you're looking for a 32-inch variant, they do have an MA320UG panel that is the same type of panel, just 32 inches. Make sure you check that one out if you're interested.

BenQ MA270S: Unboxing and First Impressions

The unboxing experience for this monitor is much like that of every other BenQ monitor I've tested. It comes in a simple brown box that's somehow still very well packed and secure. In the box is the monitor or panel, the stand, documentation, and every cable you could possibly need.

That is one thing I will always appreciate about BenQ: they include every single cable, regardless of how you use this monitor. If there's an HDMI option, they include an HDMI. If there's USB-C, they include USB-C, so you can get up and running right away.

The first time I laid eyes on the monitor, I immediately recognized how glossy the first panel was. Of course, that could be an issue if you're in a high-glare area, but I decided to put it to the test anyway. It took me exactly one second to know exactly what I wanted with this monitor.

I added it to my test setup that already has a BenQ R/D monitor. I knew this would be a perfect vertical monitor, even though there's a difference between the slightly matte display on the R/D monitor and the glossy display on this one.

Plus, to the left of my desk is a window. I have a semi-transparent shade on it, but still, there's a window. I did worry for a moment if there was going to be too much glare, but after setting everything up, I completely forgot that it was a concern. I was able to get to work immediately. Now, 100 days later, I am absolutely thrilled with this monitor.

BenQ MA270S: Design & Build Quality

As I briefly mentioned above, this monitor is incredibly clean. It comes with everything in the box, which is awesome. It has a fairly high-gloss finish. This is the kind of glossy finish that you would find on a studio display.

This is the kind of glossy finish that you would find on a MacBook or on a high-end creative laptop. It's beautiful. It's not just glossy for the sake of being glossy, but it's glossy to show just how sharp the image is, how beautiful the blacks are, and how vibrant the colors are.

That, plus the native integration with Apple's walled card, makes this monitor an absolute dream to use with a Mac. While I have used this desk setup with a PC, I prefer to use it with my MacBook Pro M4 Pro 14-inch. I can plug in a single cable through a docking station, technically, too, and run both these monitors without any problem.

When I need to just listen to a little bit of music or join a virtual meeting and I don't want to use my soundbar, I can run the audio through this monitor. While it's not great, it could get the job done before a virtual meeting if that's all you need it for, or maybe some lo-fi background music. If you're trying to actually listen to music or need to play audio for some other reason, I would suggest using headphones or an external speaker.

The bezels on this are sharp. The port access is phenomenal, and the ability to fit a clean Mac desk setup is truly uncanny. Sure, there's still a part of me that wishes I could have a studio display; however, with every upgrade to the BenQ Mac-specific line-up, that desire shrinks a little bit, by little bit, by little bit.

To bring me back to the ports for a moment, I genuinely appreciate that BenQ doesn't try to hide their ports under some sort of breakable plastic cover. Instead, they make the cables highly accessible, pointing directly over the monitor to avoid the cable dangling down underneath the bezel and being visible from the front.

The ports are firm yet not difficult to plug things into. They are well spaced, leaving room for even awkward cables, and they're in a good position. All around, a big win for me.

I've said it once, maybe even twice now, but I'll say it again: this is essentially BenQ's version of a 27-inch studio display. While the studio display has better speakers and a built-in camera and mic, this display wins out in pretty much every other category.

It's easy to set up and easy to use with both the Apple ecosystem and others, in case you need to plug in something else. It's got spectacular color accuracy, a beautiful panel, high resolution, a nice gloss, and it functions just as beautifully as it looks.

BenQ MA270S: In use

Looking back at my arrival date, I've had this monitor for exactly 166 days as of this review. In that time, it has lived almost every single one of those days on my desk in the photos as a vertical monitor paired alongside my BenQ RD series monitor.

It truly is a remarkably good 5K monitor, especially with the built-in features that let me adjust brightness and volume directly from my keyboard. I've used this monitor for accessing emails.

I always have my calendar, some messengers, and reminders up on this monitor, as I can have it scaled up to the smallest size Mac offers and still see every single line super crisp. Unlike the Studio Display, what I really appreciate about this monitor is that it doesn't just have USB-C. It has USB-A, USB-C, HDMI, and others to make these a lot easier.

BenQ MA270S: Final verdict

At the end of the day, most Mac users decide whether they care about the Studio Display. Since it was released, most people with an X-ray monitor have thought about switching to the Studio Display, but usually see the cost and change their minds.

That's where this monitor comes in strong, serving as a shield unless you are sitting on cash to burn or need the proprietary one for some other reason. This BenQ monitor feels like a true MVP.

I have absolutely loved using this monitor for work, and I look forward to continuing to use it as much as possible in the future. For me, this is one of the best photo editing monitors I've ever used.

For more top picks, we've tested the best monitors for Mac mini and the best monitors for MacBook.

• Check Point Research exposed coerced insider flaw in ChatGPT’s agent architecture
• Containers shared metadata via internal service, enabling cross‑account prompt injection and data theft
• OpenAI closed the path, but CPR warns similar risks may exist in other AI platforms

ChatGPT’s AI agents were allowed to pull sensitive data from one account shared with an entirely different account because, colloquially speaking, all agents used to walk down the same hallways, experts have warned.

A new report from security experts Check Point Research (CPR) dubbed the flaw “coerced insider”, since it revolves around persuading the agent instead of abusing a vulnerability.

Coerced insider

When an AI agent is given a task that needs code execution, it handles that task in an isolated container which also sometimes needs to install software. To enable that, without giving containers direct internet access (which would be too risky), OpenAI routes those packages through an internal JFrog Artifactory instance. As a separate security contingency, containers from different accounts cannot talk between themselves.

However - they can reach the same internal service (our proverbial hallways), which exposes an item management feature that lets the containers attach text or binary properties to a repository item. As a result, any container can read back the properties written by any other container.

“Check Point Research confirmed the isolation gap directly: a property written from one account’s container was fully readable from a different account’s container moments later, with data too large for one property simply split into chunks and reassembled on the other end,” the researchers explained.

“The package delivery metadata effectively became a shared clipboard between containers that were supposed to be walled off from one another.”

From there, the exploit turns into your usual, off-the-shelf prompt injection. The only difference is that the malicious prompt is not delivered directly to the victim, but rather left in the hallways, and the results are not shared with the attackers directly, but rather left in those same proverbial hallways, too.

The attacker then delivers a prompt or a shared conversation that instructs the agent to check the same storage during its next ordinary reply. The agent checks, sees the malicious instructions, executes them, all the while replying to the victim’s question in the usual manner. The victim is oblivious to the fact that data theft is taking place in the background.

What kind of information can be stolen?

But this is just half of the equation. How destructive this attack ends up being still depends on the amount of data being shared with the victim agent.

The bare minimum is the information shared while chatting to the agent. It then grows with every connected app: Gmail, Google Drive, Microsoft Teams, GitHub, and similar. “In Check Point Research’s demonstration, ChatGPT retrieved the victim’s email data through their connected Gmail account and delivered it to the attacker’s session, all within a single ordinary turn,” CPR stressed.

The good news is that you’ll likely never be exposed this way, at least not via ChatGPT. CPR says it disclosed the findings to OpenAI, who then confirmed that the specific internal Artifactory instance identified in the research has been commissioned. In other words, the hallways attack path has been closed.

The bad news is that this doesn’t automatically mean everyone’s safe. This particular path might be closed, but the architectural pattern behind the flaw could be present in other platforms, CPR warns.

“Any AI assistant that operates inside an organization’s trust boundary, holding credentials, running code, and reaching connected services, can become what Check Point Research calls a coerced insider,” the report states. “The model itself does not need to be malicious. It only needs to be persuaded, through text it was never meant to trust, to use access that was granted for entirely legitimate reasons.”

Going forward, businesses are advised to learn which AI tools their employees are using, and what those tools are connected to. Then, they should govern what AI tools and agents are allowed to do, treating all of their actions (not just output) as something that needs to be monitored.

• Qualcomm to help build custom silicon and optical networking for AWS data centers
• Amazon will acquire 25 million Qualcomm shares, worth over $4 billion
• AWS data centers are more efficient than the industry average, but behind Google's

Qualcomm and Amazon have announced what they have describing as a "multi-generational product collaboration," in which Qualcomm will help build future AI data center infrastructure for AWS.

Because this isn't a one-off project, instead of announcing a single component, the companies are likely to work together across multiple generations of infrastructure spanning both custom inference silicon and high-speed optical connectivity.

Together, the two companies are expected to combine their expertise in AI infrastructure and data centers to improve performance, power efficiency and cost efficiency for a future where data centers exist in even higher volumes.

AWS and Qualcomm to work together on future data centers

The project spans two key areas – custom AI silicon and networking hardware. On the silicon front, Qualcomm will help produce custom AWS silicon with a major focus on inference, giving the chipmaker a potentially big entry into the data center semiconductor market – one that Nvidia has seen major success in.

As for networking, Qualcomm will be behind high-performance optical connectivity for AWS data centers, covering connections of up to 1.6T initially but plans to scale.

With data centers under intense pressure from all angles to boost efficiency and reduce resources consumption, operators are being forced to make progress in all areas, and reducing losses between components with efficient networking is often overlooked compared with outright chip efficiency.

"As AI demand accelerates, data center infrastructure will require advances in both computing and connectivity to deliver greater performance with more efficiency,” Qualcomm CEO Cristiano Amon summarized.

In Amazon's 2025 sustainability report, it declared a global average PUE of 1.14, which was nearly 9% better than the public cloud industry average of 1.25. Still, Google says it managed a fleet-wide average of 1.09, so Amazon's work with Qualcomm could be key to it overtaking Google.

"By working together on customized silicon and advanced connectivity, we’re delivering more performant, efficient, and cost-effective infrastructure for our customers," AWS VP Prasad Kalyanaraman added.

As part of the deal, Qualcomm has issued warrants for Amazon to acquire around $4.03 billion in stock, per a SEC filing – the equivalent of 25 million shares priced at $161.26. Qualcomm is currently trading at $174.09, up nearly 5% in five days.

DDR5 might be the memory standard for newer PCs, but it costs far more than DDR4, especially when you're shopping for faster or higher-capacity kits.

If you're upgrading a DDR4 system, I've found a terrific deal on the G.Skill 32GB Trident Z RGB for $215 (was $258) at Newegg when you use code LUYRF222.

For your money, you get two 16GB DDR4-3600 modules with CL18 timings, aluminum heat spreaders, customizable RGB lighting and Intel XMP 2.0 support.

Today's best DDR4 RAM deal

Why we recommend it

32GB is enough memory for demanding multitasking, gaming and creative applications. The DDR4-3600 speed is also a good fit for compatible DDR4 systems, particularly if you're upgrading an older machine that's currently running slower or lower-capacity memory.

The two matched 16GB modules provide a dual-channel configuration, with timings of 18-22-22-42 at 1.35V.

G.Skill's Trident Z design adds aluminum heat spreaders and customizable RGB lighting, making this a good choice if your PC has a windowed case and you want your memory to complement other RGB components.

Price context & historical value

Newegg sells the 32GB Skill Trident Z RGB kit for $257.49, and it's currently available for $249.99. Using coupon code LUYRF222 brings the final price down to $214.99.

While that's a decent price in today's inflated memory market, it's worth remembering just how much cheaper DDR4 used to be. Newegg sold this exact G.Skill kit for just $69.99 in August 2023, less than a third of its current discounted price.

Unfortunately, it's unlikely to drop down to that level again, so the current deal is worth considering if you need to upgrade your DDR4 system now.

Should you buy it?

✅ Buy the 32GB G.Skill Trident Z RGB kit if...

You have a compatible DDR4 desktop and want to increase its memory capacity without replacing your motherboard and processor to move to DDR5. The combination of 32GB capacity and DDR4-3600 speed makes it a solid upgrade for an older system.

❌ Skip the 32GB G.Skill Trident Z RGB kit if...

You're building a completely new PC around a recent processor and motherboard. In that situation, I'd seriously consider DDR5 instead, as you'll be investing in the newer memory standard rather than spending more than $200 on DDR4 that you won't be able to carry over to a future platform.

The Catch: What to know before you buy

You'll need to enable XMP, DOCP or A-XMP in your BIOS to reach the kit's advertised DDR4-3600 speed on compatible hardware. Otherwise, the memory will initially run at its default SPD speed.

Compatibility is also important. G.Skill recommends checking its motherboard QVL, and it specifically warns against mixing separate memory kits, even when their specifications appear identical, as doing so can cause stability problems.

• Shop all RAM at Newegg

For the past decade, quantum computing has been relegated to the horizon, a distant, theoretical challenge rather than an immediate operational imperative.

Breakthroughs have generated headlines, but without a firm deadline for when quantum computers could threaten today’s cryptographic standards, CISOs have had little incentive to make quantum readiness an immediate priority. IBM’s 2025 Quantum-Safe Readiness Index shows how much work remains, with the average organization scoring just 25 out of 100.

Yet, that window of preparation is contracting rapidly. This spring, Google warned that “quantum frontiers may be closer than they appear,” pointing to advances in hardware, error correction, and algorithms that are accelerating progress toward cryptographically-relevant quantum computers. Google has since set a 2029 target for completing its own migration to post-quantum cryptography (PQC).

Yet, that growing urgency still comes without a firm deadline. Unlike the fixed, binary deadline of Y2K from years ago, the quantum risk profile is nebulous; the exact threshold of peril remains undefined, even as the required remediation timeline spans several years.

Large enterprises need time to identify cryptographic dependencies, assess legacy infrastructure, coordinate vendors, and secure the budgets required for migration. Those decisions reach well beyond cryptography, affecting how the business plans, funds, and prioritizes risk. In fact, the availability of quantum computing capabilities will touch almost every aspect of companies around the globe.

Turn quantum risk into an enterprise-wide priority

Quantum readiness already has a prescribed technical solution. In 2024, NIST finalized its first set of PQC standards and encouraged organizations to begin transitioning as soon as possible. For some systems, migration may just involve a software update or configuration change. For others it may be much more complex. The challenge for a large enterprise is knowing where those changes need to happen.

A practical first step is to build a cryptographic bill of materials (CBOM), cataloging what cryptography is in use and where, which systems can be updated relatively easily, and where legacy infrastructure may require replacement or another mitigation strategy. This is an intensive effort, but there are software platforms that can help.

Next, organizations should prioritize systems based on the value of the data and how long it needs to remain protected. Financial records or customers’ customer personally identifiable information (PII), for example, may warrant greater urgency than an internal chat log with little long-term value.

Data longevity is especially important because adversaries are already collecting encrypted traffic in the expectation that future quantum computers will be able to read it, a practice known as "harvest now, decrypt later." For sensitive data, the attack may already have happened even though the business impact hasn't.

Data exposure is only one part of that assessment. Public key cryptography (PKC) also underpins authentication, including single sign-on and other mechanisms used to establish identity. If that cryptographic foundation can no longer be trusted, organizations face the risk of impersonation, with consequences for access to applications, infrastructure, and data.

Much of this work sits outside the CISO's direct control. Infrastructure, applications, data, and third-party relationships are often jointly owned across the business, and so are many of the budgets needed to address them. CISOs must make a business risk pitch that shows other leaders – the CIO, CTO, procurement, compliance, and executives – where the greatest risks are and what needs attention first.

Make crypto-agility part of the migration

Preparing for a post-quantum future also requires crypto-agility. Cryptographic standards will continue to evolve as new vulnerabilities emerge and algorithms change. Organizations need systems and platforms that can accommodate those changes without another costly, multi-year migration. That means buying and building in ways that can accommodate a future algorithm change through software rather than hardware rip-and-replace.

The UK's National Cyber Security Centre recommends building that flexibility into PQC migration plans and establishing criteria for retiring traditional algorithms, with the goal of removing sole dependence on traditional public-key cryptography. It also means rethinking how organizations budget for the transition.

Large enterprises often operate on annual budgets approved well in advance and adjusted only slightly throughout the year, but a post-quantum transition may require more flexibility as standards and threats evolve.

This principle should also influence procurement. SOC 2 compliance already requires organizations to scrutinize vendors' privacy policies, certifications, and access controls, but cryptographic dependencies can be another blind spot. Asking which standards a vendor supports, how cryptography can be updated, and what its PQC roadmap looks like can reduce the risk of buying infrastructure that becomes difficult or expensive to migrate later.

The quantum timeline starts with today’s budget

While a firm deadline for quantum readiness remains elusive, budget cycles offer a more disciplined, actionable framework for planning. Executing a multi-year migration requires sustained financial commitment over successive cycles; every passing budget period effectively compresses the available window for remediation.

Most CISOs already understand quantum risk. The challenge is moving quantum readiness from something planned for next quarter or next year into funded work. With only a limited number of budget cycles available for a multi-year migration, repeated delays quickly add up.

The priority is to turn that awareness into an inventory, clear business priorities, and a phased migration plan that can be funded over the coming budget cycles. By starting now, organizations have time to focus on the highest-risk systems and address legacy infrastructure before the timeline becomes critical.

We've featured the best web hosting services.

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

This is easily one of the best-value SIM deals I've seen right now - and it's a steal for data-guzzlers, regular travellers, and anyone who hates being locked into a monthly contract.

Right now, this EE Rolling Unlimited SIM is just £15 a month (was £35) at Scancom when you use the code HUKDSAVE.

As a rolling SIM, there's no monthly contract to sign, letting you cancel any time. The plan includes unlimited monthly calls, text, and data. There's also 25GB Europe Roaming included at no extra cost.

Today's best unlimited SIM deal

Why we recommend it

Unlimited data, calls, and text, and free European roaming data make this one of the best-value SIM deals around right now.

At £15 a month, rather than £35, you get EE's reliable network speeds with absolutely no contract to sign, so you can cancel any time.

The generous 25GB data roaming for Europe is ideal for frequent travellers (whether that's for work or pleasure). And it's more than enough data allowance for streaming, video calls, map navigation, and checking messages and emails when public or hotel Wi-Fi is slow.

I haven't seen a similar cost with similar benefits from EE either on Amazon or direct from the network provider.

Price context & historical value

No two ways about it, £15 a month for unlimited data, calls, and text is an excellent price. For comparison, an Unlimited Rolling SIM plan without the 25GB European data roaming is priced at £25 a month at Amazon. Buying a monthly contract unlimited SIM with no free roaming data direct from EE is currently £23 a month.

Should you buy it?

✅ Buy the EE Unlimited Rolling SIM if...

You don't want to sign up to a monthly contract, use a lot of data at home, or you're often traveling to Europe for work.

❌ Skip the EE Unlimited Rolling SIM if...

You'd rather buy direct from EE to get the network provider's support and sign-up extras, or you need more than 25GB European data roaming.

The Catch: What to know before you buy

As it's part of the EE network, make sure you get the service in your area. You can use EE's coverage checker here.

It's also worth pointing out that Scancom is also technically a B2B site, and you'll use the company for support, rather than EE's in-house team.

That doesn't mean you need to be a business to buy and use the SIM, and we've seen reports online that the company won't check for business credentials anyway. But that's its main purpose is for professionals.

• Shop the full SIM range at Scancom

• Google is investing over $15 billion into Finland over two years
• Nuclear energy, wind power and battery storage are top of mind
• The company is also improving local forests, adding new saunas

Google has announced plans to invest around $15.1 billion into Finland's AI and digital infrastructure over the course of the next two years, making it its largest single investment in Europe to date.

The company said the extra capacity is needed to meet growing local demand for services like Gemini, Maps and YouTube, but instead of just growing its data centers, Google is also allocating money for grid upgrades, clean energy projects, battery storage and more.

The country's cool climate and low-carbon electricity are especially attractive for hyperscalers as they try to improve the efficiency of data centers against a backdrop of heightened public and regulatory scrutiny.

Google is investing heavily in its Finnish data centers

The Hamina campus, which it's been running for around 15 years, is especially notable because it uses both seawater-based cooling to minimize its water consumption impact, as well as an offsite heat-recovery scheme to redirect waste heat into local properties.

Local communities in Hamina, Kajaani, Muhos, and Vaala are set to receive a combined $36 million in funding to support upskilling and education, while as many as 37,000 jobs are expected to become available throughout the 2027-2028 construction phase.

On the energy front, Google has signed a 22-year power-purchase agreement to support the extension of the Loviisa nuclear plant and has drawn up plans to add new onshore wind capacity and a new 94MW battery facility to bridge the gap between renewable energy availability.

Google Global Infrastructure VP Bikash Koley also stressed the company's other community and environment investments, including native forest and wetland regeneration, accessible recreational trails, public saunas and fishing piers.

For Finland in particular, Google claimed to have invested around $4 billion in Hamina and related infrastructure alone since acquiring the site, a former paper mill, in 2009.

• Chrome will get new updates every two weeks to minimize real-world attacks
• Smaller, incremental changes should also make it easier to track any issues
• Other major browsers are also shifting to two-weekly release cycles

Google has confirmed that Chrome has officially moved from a four-week Stable release cycle to a two-week one, with effect from September 8 2026 with the launch of Chrome 153.

Besides adding new features, the main objective is for Google to give us performance and security fixes more promptly in an era of increased complexity and heightened vulnerabilities.

And it's exactly those security concerns that pushed Google to want to double Chrome's update frequency in the first lace, with the company now having to deal with a higher volume of patches than ever before.

Chrome will get updates every two weeks

Together with a higher volume of attacks in general, Google has also benefitted from AI-powered vulnerability discovery tools, giving developers more work to do than before. "With automated AI discovery tools and community bug reports generating higher patch volume, shorter release cycles make managing security fixes significantly simpler," the company wrote.

Crucially, the faster cycle reduces the time between a fix landing in Chrome's public codebase and it actually reaching end users, making it less likely for a bug to be exploited in the wild.

Chrome has been adhering to a four-week cycle since 2021, but the world is a very different place in the space of just half a decade.

With the higher pace of releases, Google also anticipates a smaller scope of changes, which could actually be a good thing because it could be easier for developers to identify what went wrong in the event of any issues.

Desktop, Android and iOS versions of Chrome will all be impacted by the change, with Chrome 154 already slated for a September 22 release.

More broadly, Google says Chrome isn't the only browser getting more frequent updates. Microsoft, Mozilla and Brave are also making similar changes, and they're all undergoing those changes right now.

Enterprise infrastructure has always adapted as scale increased. Virtualization tackled server sprawl, cloud computing reduced the need to provision physical resources for every application, and automation made increasingly complex environments manageable. Artificial intelligence presents a different kind of scaling problem.

The discussion around enterprise AI has largely centered on models, GPUs, and inference performance, but those technologies represent only a fraction of what organizations must operate. Every production AI deployment creates a continuous flow of data that must be ingested, protected, moved, analyzed, retained, governed, and eventually archived.

Those activities place demands on infrastructure that are very different from the workloads storage systems were originally designed to support.

This is becoming increasingly apparent as organizations move beyond pilot projects. AI is no longer a single workload running on isolated infrastructure. A single application may include high-speed storage for model training, object storage for inference data, lower-cost capacity for operational datasets, immutable storage for cyber resilience, and long-term archives to satisfy regulatory requirements.

Traditionally, those functions have been handled by separate products with separate management tools, security policies, and operational teams. That architecture worked reasonably well when data moved slowly and applications followed predictable lifecycles. AI changes both assumptions.

Training datasets expand continuously. New models are introduced far more frequently than traditional enterprise applications. Inference workloads fluctuate as demand changes. The same dataset may move repeatedly between active processing, backup, compliance, and archival over its lifetime.

Each transition introduces another operational task, another opportunity for inconsistency, and another point where administrators must intervene. Before long, the effort required to manage the infrastructure begins to rival the effort required to build the AI applications themselves.

Complexity becomes the real infrastructure challenge

For years, the answer to operational complexity was automation. Administrators automated provisioning, scripted maintenance, and orchestrated repetitive tasks. Those capabilities remain valuable, but they were designed to execute predefined actions under predefined conditions.

AI environments are considerably less predictable. Infrastructure must continually adapt to changing workloads, shifting performance requirements, evolving security policies, and rapidly growing data volumes, often without the benefit of stable operating patterns.

That is where autonomous data infrastructure represents something more substantial than another automation framework. Rather than treating storage as a collection of independent systems, it starts with the assumption that the platform itself should continuously optimize how data is managed throughout its lifecycle. Capacity, performance, protection, and cost become policy decisions rather than infrastructure projects.

Data moves between performance tiers automatically according to business requirements instead of being exported, migrated, and re-imported into separate platforms. A single namespace spans workloads that historically required multiple storage systems, allowing infrastructure to evolve without repeatedly forcing administrators to redesign the environment.

That architectural change may ultimately prove more important than the automation itself. Many organizations underestimate how much operational complexity accumulates simply from running multiple storage platforms. Every environment has its own authentication model, monitoring tools, lifecycle policies, upgrade schedules, recovery procedures, and performance characteristics.

As AI expands across the enterprise, those management layers multiply alongside the data. Reducing the number of operational boundaries often creates greater long-term value than introducing another layer of orchestration.

The same principle applies to cyber resilience. AI has increased the value of enterprise data far beyond traditional business records. Training datasets, model checkpoints, vector indexes, and inference pipelines have become strategic assets in their own right. Protecting them requires more than backup software. It requires infrastructure that assumes failures and attacks will occur and is designed to recover without depending on manual intervention.

Governance becomes part of the data lifecycle

The conversation also extends beyond security to control. As AI initiatives become more strategic, organizations are under growing pressure to understand where data resides, who can access it, and which legal and regulatory frameworks govern it.

That is especially true for enterprises operating across multiple countries or in highly regulated industries, where data residency requirements, digital sovereignty initiatives, and industry-specific compliance obligations increasingly influence infrastructure decisions.

Rather than treating these as separate governance exercises, modern infrastructure must make location, retention, and access policies part of the data lifecycle itself, enabling organizations to meet regulatory requirements without introducing additional operational complexity.

One of the more significant design decisions behind autonomous data infrastructure is that immutability exists within the storage engine itself rather than being implemented solely through administrative policy. Instead of modifying existing data in place, new versions are written separately while previous versions remain intact.

Combined with distributed self-healing that rebuilds only affected objects instead of entire disks, this creates a fundamentally different operational model for resilience. Recovery becomes part of normal system behavior instead of an exceptional event requiring administrators to coordinate lengthy repair efforts.

Infrastructure operators become infrastructure architects

Perhaps the most interesting implication has little to do with storage technology itself. Infrastructure teams are already responsible for environments that are growing faster than headcount, and AI is accelerating that imbalance. The objective is not to remove people from operations, but to reduce the amount of time highly skilled engineers spend on repetitive maintenance that adds little strategic value.

As more routine activities become policy-driven and continuously optimized, infrastructure professionals can devote more attention to architecture, governance, capacity planning, and aligning technology decisions with business priorities.

That evolution mirrors what is happening across software engineering, networking, and cybersecurity. AI is steadily shifting human expertise away from repetitive execution and toward system design, governance, and strategic decision-making. Autonomous data infrastructure reflects the same progression.

Rather than asking administrators to manage an ever-growing collection of storage products, it treats the infrastructure as an adaptive system that operates within policies established by the people responsible for it. The most effective approach is not to take humans out of the loop, but to keep them in control of the decisions that shape security, compliance, and business outcomes while allowing the platform to execute routine operational tasks autonomously.

Viewed from that perspective, autonomous data infrastructure is less about storage than it is about preparing enterprise IT for the next decade. AI has exposed the limitations of architectures built around isolated products, manual coordination, and steadily increasing operational overhead.

Organizations will continue investing in faster GPUs and more capable models, but those investments will deliver their greatest value only if the infrastructure beneath them becomes equally capable of managing complexity. The next generation of enterprise infrastructure will not simply store data more efficiently. It will actively participate in operating the environments that modern AI depends upon.

We've featured the best business intelligence platform.

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

For years, ambitious European technology founders heard the same advice: to build a global software business, you'd eventually need to move to Silicon Valley. The Bay Area had venture capital, experienced operators, and many of the world's largest technology companies.

Today, some of the world's fastest-growing AI companies are proving otherwise. Lovable, based in Stockholm, has just achieved a $13.3 billion valuation and reaches nearly two-thirds of employees of the Fortune 500. ElevenLabs, founded in London, achieved an $11 billion valuation in early 2026 and surpassed $500m ARR later in the year.

AI has rewritten the economics of building a company: foundation models, coding assistants and automation tools let small teams create, iterate and scale with far fewer people than previous generations needed. Success now hinges on attracting exceptional talent, not on being near Sand Hill Road.

That changes the question for Europe. It's no longer whether we have the talent or the capital to build globally significant technology companies. We do. It's whether that talent becomes founders, or stays employees.

Europe has the talent

London has become one of the leading hubs for frontier AI talent outside the United States, supported by organizations such as Google DeepMind, the Alan Turing Institute, and Imperial College London. The capital's King's Cross area has become a focal point for AI research, startups, investors and global technology companies.

Elsewhere, cities including Paris, Berlin and Munich continue to cultivate world-class engineers, researchers and product leaders. I have lived in the US before, but I chose to found my own company in London for exactly this reason: the talent I needed was already here.

The fight for future founders

The expansion of American AI companies into Europe underlines the strength of that talent pool. OpenAI and Anthropic have both expanded their London research and engineering operations, joining Google DeepMind and Microsoft AI in competing for the same engineers, researchers and product leaders that emerging startups need.

These companies can offer salaries, resources and career paths that no early-stage company can match, and for many skilled operators, joining one is the logical choice.

The cost is largely invisible. Every experienced operator who spends a career inside a global AI company instead of starting one is a company Europe never gets to build. The result is fewer breakthrough companies and fewer founders to inspire the next generation.

Operators make the best founders

Many of the strongest founders start out as operators. Before launching their own companies, they spend years learning how to build products, attract customers and scale organizations, developing judgement against real business problems.

I've seen this progression in practice. Before co-founding ElevenLabs, Piotr Dąbkowski worked alongside me at Tessian, a cybersecurity company, where he was building AI-powered products years before the current wave. The judgement he developed there as an operator helped shape what became one of Europe's most valuable AI companies.

In the AI era, successful founders are defined by more than technical expertise. They have commercial judgement and an instinct for seeking out problems that need solving. These qualities make them valuable employees today and position them to become successful founders tomorrow.

They're also exactly what I hire for. We look for traits over skills: people who seek out responsibility before anyone hands it to them, and who want to understand how the whole business works rather than just their corner of it. Technical skills matter, but those are the operators most likely to build something of their own one day, and they create enormous value long before they do.

Back them at the point of the leap

As technology becomes more accessible, entrepreneurial ambition becomes the scarce resource. So support for aspiring founders has to begin long before they start seeking venture capital. Many experienced operators already have the expertise, networks and market insight to build successful businesses. What they lack is the confidence, encouragement or early backing to leave a stable job.

At my own company, we've put money behind this belief. Anyone who has been with us for five years can make a single pitch and get $250k to go and build their own company, along with office space and the backing of people who've worked beside them for years.

There's no cap on how many founders we'll fund. It isn't a perk designed to wave people out the door. It's a recognition that the people best placed to back a first-time founder are the ones who've watched them work, and that when I left my last company to start this one, I had to pitch strangers instead. Programs like Entrepreneur First have shown the value of backing exceptional individuals before they even have a company. Europe needs more mechanisms like this, wherever they come from.

This is how ecosystems compound. Former PayPal employees, the so-called "PayPal Mafia", went on to found or help build companies including LinkedIn, Palantir and YouTube. Europe is beginning to generate its own founder networks, with former Skype employees founding companies such as Wise, Bolt and Starship Technologies. Back one generation of founders and they build the next.

Europe has the fundamentals in place: exceptional talent and a maturing investment ecosystem. The missing link is the pipeline from operator to founder, and today's scaleups are the ones who can build it. Every operator who takes the leap expands Europe's capacity for innovation and entrepreneurship, and makes the whole ecosystem more self-sustaining.

We've featured the best AI website builder.

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

• Ukrainian drones forced American soldiers to rethink movement, concealment, and battlefield survival
• Blackhawk troops changed their tactics after persistent aerial surveillance exposed their movements
• American armored vehicles suffered losses despite attempts to conceal them from drones

A 10-day US Army combat training exercise in Germany has drawn attention after reports claimed Ukrainian drones overwhelmed an American mechanized company during the drill.

At the center of it is Blackhawk Company, part of the 2nd Battalion, 7th Cavalry Regiment, which spent the ten days training at a range in Hohenfels.

The company commander, Capt. Allan Watson, disputes that account, insisting the report failed to capture what his soldiers actually accomplished over those days.

Entering a battlefield dominated by drones

Blackhawk Company entered a 14-by-27-kilometer range where Ukrainian personnel from the 412th Regiment supported opposing forces during initial operations.

The Ukrainian elite formation, called Nemesis, had battlefield experience and used aerial systems to observe American movements across the range.

The American unit claims to lack the counter-drone equipment its soldiers would have preferred throughout the event.

Rather than relying on unavailable equipment, soldiers altered how they occupied positions, moved vehicles, and concealed personnel from aerial observation.

Bradley vehicles moved beneath dense vegetation, while troops used steep ground and difficult routes to reduce their exposure from above.

The company also studied its movements from an aerial perspective, changing routines that might have made detection easier for enemy operators.

Despite those changes, American vehicles were destroyed during simulated combat, including Bradley vehicles plus tanks, while some crews were also counted as losses.

Watson, however, rejected the idea that these losses proved heavy armor had become unsuitable for modern combat environments.

He said armored vehicles remained useful because they provided mobility and protection while allowing soldiers to move through difficult terrain during operations.

Adapting tactics changed the exercise

The commander said drones could locate American forces, but exploiting that information still required personnel operating at ground level.

That distinction became important as the exercise progressed, because Ukrainian aerial surveillance did not remove the need for conventional reconnaissance.

On the sixth day, Blackhawk Company shifted from defensive tasks toward offensive operations, while the Ukrainian formation later operated alongside American troops.

Watson said the soldiers became increasingly confident as they adjusted to conditions that challenged assumptions formed through earlier training.

The Ukrainian participants also shared methods for operating inexpensive drones over long distances and linking battlefield observation with rapid engagement.

“They put on a masterclass in sensor-to-shooter kill chain management and speed,” said Capt. Allan Watson, Blackhawk Company commander.

Watson also said the experience showed that technology alone does not determine battlefield outcomes, because human decisions remain essential during combat.

For Watson, the principal lesson was not that drones had replaced armored formations, but that units must adjust tactics when aerial surveillance becomes persistent.

However, this is also not the first US military exercise where Ukrainian drone teams have caught American forces off guard.

In an earlier exercise in Germany, US troops were defeated so quickly that exercise officials allowed those units to re-enter the scenario.

These events were designed to expose weaknesses, test countermeasures, and help American forces prepare for drone-heavy warfare.

Ukraine’s experience against Russia has made its drone units especially capable in unmanned systems and electronic warfare operations.

The repeated setbacks, therefore, raise a more direct question about whether US forces should adapt more quickly and improve their capabilities.

Rather than explaining away each defeat as a training outcome, American forces need to treat these exercises as warnings.

Via Task&Purpose

• The LOCUST X3 laser is developed by AeroVironment, Inc.
• It is designed as a “group 3 killer” – meaning it is intended to tackle particularly dangerous drones
• The Xbox controller makes the LOCUST X3 laser simpler to target

A new US Army contract worth around $465 million has been awarded to AeroVironment, Inc. for its LOCUST X3 anti-drone weapon, a 30-kilowatt laser that can be mounted on military vehicles.

Designed to take down mid-sized attack drones, the LOCUST X3 can specifically handle what the Department of Defense refers to as “Group 3” – unmanned aerial vehicles weighing 1,350 pounds and capable of lifting 125 pound payloads over a distance of 8 miles.

Interestingly, AeroVironment, Inc. has designed the LOCUST X3 to be relatively easy to control. Operators (which may be soldiers, sailors, airmen, or even Space Force guardians) can target the anti-drone laser using an Xbox controller.

“The apex predator”

Incredibly, this is the first high energy laser weapon to be awarded a production contract in US history, following several years in development, which included military testing.

Wahid Nawabi, Chairman, President, and Chief Executive Officer at AV said: “The transition of directed energy from experimentation to an enduring, fielded capability reflects years of collaboration, innovation, and operational success alongside the U.S. Army.”

Aaron Westman, senior director for business development at AeroVironment, Inc., outlined how the LOCUST X3’s role is viewed by the company. “It can really kill a lot of threats. Its job is to really, let’s say, thin the herd to be able to kill high volumes of threats.”

John Garrity, vice president of directed energy systems at AeroVironment, Inc, expanded on the use of an Xbox controller for targeting the anti-drone system.

“To a young soldier, sailor, airman, guardian that’s using these systems, it’s not unlike what they’re using at their own house for video games," he noted.

“Group 3 killer”

The purpose of the LOCUST X3 is to dispatch attacking drones relatively efficiently. But what does “Group 3” actually mean?

Garrity told reporters that “LOCUST X3 is intended to be the Group 3 killer. When we talk about Group 3, that’s just one of the more prevalent threats that you see in warfare today, seen in conflicts in Iran and in Ukraine with Shahed drones.” The LOCUST X3 is intended to be a one part of the US Army’s response to done attacks, with other weapons contributing to the multi-layered defense against Group 1-3 UAV threats.

The one-way Shahed-136 drones have been used against US troops in the Middle East. The LOCUST X3 is positioned as a solution to this, and not just due to its portability. It also has longer range than many similar countermeasures.

US interceptor missiles are believed to be largely depleted thanks to the conflict with Iran. Anti-drone weapons like the LOCUST X3 are viewed as a forward-thinking alternative.

• 69% of Americans oppose AI data centers near their communities, a national poll finds
• Public support for nearby AI data centers has fallen sharply since 2025
• Only 4% strongly support new data centers in their communities today

American resistance to AI data centers has intensified sharply over the past year, several national surveys released in 2026 have found.

A new Decision Desk poll conducted by SurveyMonkey found that over two-thirds (69%) of respondents oppose construction of these facilities near their homes.

Nearly half of those surveyed (45%) said they would strongly oppose a data center built anywhere close to their own neighborhood.

Data centers do not have widespread American public support

Separate research from Heatmap Pro, carried out by Embold Research in mid-August 2026, points to an even sharper decline in public backing, as its poll of 2,045 registered voters found 75% opposed building a facility near their community.

Only 4% of respondents said they would strongly support a proposed data center in their area, a drop from 13% recorded a year earlier.

Resistance now cuts across age, income, party affiliation, and the split between rural and urban communities nationwide.

Republicans remain 43 percentage points net negative on the issue, independents sit at 65 points negative, and Democrats register 75 points negative.

Rural voters, a group that has trended Republican in recent years, are 63 points net negative as well.

Officials across the political spectrum have taken notice. New York Governor Kathy Hochul ordered a one year pause on new facilities, and Texas Governor Greg Abbott froze several pending projects pending a required audit.

Heatmap Pro figures reveal that over 530 counties and municipalities have restricted or banned data center construction.

Political and economic fault lines

President Trump has pushed back publicly against the trend, framing local opposition as economically self-defeating.

“The only reason that communities throughout the U.S.A. should not want Data Centers is if they want to end up being backwards and poor,” Trump wrote on Truth Social.

“If they want to be successful and rich, with far lower taxes and jobs all over the place, let Data Reign.”

However, Republican supervisor Dawn Vogel backed a local moratorium earlier this year, putting her at odds with Trump's national agenda.

“I don’t think this is a Republican or Democratic issue…It’s an issue of what’s the best use for the land, what’s the best use for our natural resources,” Vogel said.

“You can have all the data you want to in the world, but if you don’t have water to drink, you don’t have humans to use the data.”

Lawmakers who once championed data centers as economic development tools are now revising their positions under mounting public pressure.

Ohio Senator Jon Husted, an early advocate, introduced legislation this year requiring data center operators to cover added electricity and water costs.

The gap between economic promises and local resource concerns appears to be driving much of the shift.

However, labor unions have generally taken a more favorable stance, citing steady construction jobs and strong wages tied to the facilities.

• The AVEN thrust-vectoring nozzle has been added to the X-BAT AI-piloted fighter with vertical take-off capabilities
• Thrust-vectoring allows a plane’s exhaust to be redirected, instead of relying purely on manipulating airflow across the wings for movement
• The engine was first trialed on an F-16 fighter in the 1990s

Shield AI has revealed the X-BAT AI-piloted fighter jet relies on a jet engine variation first developed over 35 years ago and tested on a General Dynamics F-16 in the 1990s.

The AVEN – Axisymmetric Vectoring Exhaust Nozzle – essentially replicates the actions of a wing, but instead of manipulating airflow across the airfoil, it directs the exhaust, in a process labeled “thrust-vectoring.”

Developed for the F-16 as part of a dedicated GE Aerospace program investigating Multi-Axis Thrust Vectoring (MATV), the nozzle was proved to work. The technology has recently been revived thanks to GE Aerospace and Shield AI, with the AVEN paired with an F110-GE-129E engine.

The VTOL X-BAT needs AVEN

Using the Axisymmetric Vectoring Exhaust Nozzle, the X-BAT is given flight capabilities that would prove demanding for humans to repeatedly endure. It enables hovering, but also superhuman reaction speeds, and removes the risk of G-force induced blackouts. Without pilot fatigue, the X-BAT can commit to extreme maneuvers in aerial combat.

Designed as a Vertical Take-off and Landing (VTOL) aircraft, the X-BAT can be deployed in areas with little or no runway. The Axisymmetric Vectoring Exhaust Nozzle is a key part of this, providing the necessary thrust for the X-BAT to take off. As the craft launches more like a rocket than a standard jet fighter, the AVEN and the F110-GE-129E engine appear to ensure a steady detachment from the launch dock as the X-BAT heads skyward.

It’s a setup that might resemble something out of a 1950s sci-fi comic, but in reality can only work successfully without a human pilot.

AVEN isn’t unique to the X-BAT. While the GE Aerospace project with the F-16 proved the technology worked, it was pursued elsewhere, most notably with the Russian Sukhoi Su-27SM revision of 2002. Earlier craft, like the Harrier variants, use “2D thrust vectoring” where thrust is directed horizontally or vertically via exhausts on either side of the aircraft. Indeed, the notion of thrust vectoring dates back to the V-2 rocket, the long-rang rocket used by Nazi Germany in the final months of World War Two.

Modernising the AVEN

Shield AI and GE Aerospace haven’t simply stuck to the original AVEN hardware and attached it to the F110-GE-129E engine. The nozzle has been re-engineered, with modern materials and production techniques. Inevitably, it has also been adapted to work with 21st century guidance systems, and the AI piloting and control systems are also accommodated.

First test flights of the X-BAT are expected to take place in Kansas by late 2026, ahead of a planned 2028 operational validation and full production.

The GL.iNet Beryl 7 is a travel router that is designed for those on the go who still need control over their networking.

Especially today, it feels like people are more aware of their networking than ever. There's fear over what people are able to see. There's fear of what other people can see of your own data, and there are people trying to take control of their own connections. That's one very real use case for the Beryl 7.

Alternatively, another use case that is possibly more common, or at least more widespread, would be that a lot of people travel with an abundance of gadgets these days. It used to be that people would have their phones, and that would be about the only thing they would connect to Wi-Fi, then maybe a laptop, then maybe an iPad.

Now the average family, to my understanding, travels with several tablets, laptops, phones, and oodles of other internet-connected devices, or perhaps that's just my family when we travel.

Regardless of which camp you're in, having a parallel router can actually prove to be incredibly helpful. Personally, I have seen some people use it as a way to connect to a VPN easily and with whatever device they have with them. I've seen some people use it as a way to be able to only have to connect to a guest Wi-Fi once and then extend that network to all of their devices.

I personally have used it in the sense of, when traveling, not having to disconnect and reconnect our devices at every stop that we make. Instead, I can connect just once and then keep all the kids' iPads and devices, as well as my own, on a known and already saved network, just simply for ease of setup.

I've also seen people use it as a way to turn Wi-Fi networks into a wired network and vice versa. All around, a little device like the Beryl 7 turns into a Swiss Army knife of networking capabilities.

GL.iNet Beryl 7: Price and availability

The Beryl 7 is available direct from GL.iNet store in the US here and in the UK here. The travel router is priced at $130 / £117.

It's also widely available from online retailers, including Amazon, where I've seen it down as low as almost $100.

The Beryl 7 specifically is not as nice as some of its bigger brothers, but for the price, if you're not changing a ton of settings but more setting and forgetting, this one might just be the perfect little addition to your tech bag.

It's lightweight, doesn't take a ton of space, and setup and go is super easy, especially with the ability to run this off of just a single low-powered USB-C.

GL.iNet Beryl 7: Unboxing and First Impressions

As a tech lover, I was excited to get my hands on this one. It seems like it's a solid update and even an upgrade from past models, and I wanted to see just how lightweight it really was. I got the mint green colorway, which is pretty striking, and for something like this, it is a little bit more fun than just a black model.

Normally, I'm an all-black or, these days, maybe even some silver technology kind of person, but I didn't mind the flash of color for something like a little networking device.

The weight is just as light as I expect it to be, or should I even say how much I hoped it would be. The ports are simple, the mode switch is sleek, and the ability to use USB-C really is just that convenient.

Even as a heavy tech reviewer, I've almost made it to where every single thing I carry is USB-C, which has become incredibly helpful for when traveling, working remotely, or at different offices and just going about my day-to-day. Needing to carry multiple cables and multiple different types of cables is a thing of the past… almost.

Having USB-C on even my travel router that I'm testing is super convenient. Further, it's nice to see two 2.5 GHz network ports, a USB 3.0 port (even though it is capped at a pretty slow speed), and two folding antennas that are satisfying enough to be near fidget-toy status.

GL.iNet Beryl 7: Design & Build Quality

Talking specifically about the build quality. While this is plasticky and the folding arms are fun to play with, it does feel like over a couple years, or even just some hard daily use, the arms could get pretty loose and won't snap open quite as nicely.

I'm also wary of dropping this because it feels like a single drop could crack the entire shell. Cases are available for the device, and if you're using it for business travel, I recommend picking one up.

With that being said, though, it is really nice to see little rubber feet on the bottom of the portable router, making it so that it's not just the sound or experience of plastic sliding along whatever I decide to put this down on.

Moving to the ports, they feel pretty well built. Cables snap in pretty easily and feel like they're a tight connection, and I appreciate the layout and spacing between all the ports.

It makes more sense to spread out even just these four ports than it does to have them all crammed together for a look of minimalism. Having them spread out a little bit on the back side of this unit makes more sense from just a usability standpoint.

GL.iNet Beryl 7: In use

I brought this with me on a few different planned trips, and then it's come in handy at other times as well.

The first trip I brought it on was a quick little family trip. Knowing that we were going to stop at a hotel on the drive and how insane it was to get everything set up for just a few hours in a hotel and then continue driving the next day, zero part of me wanted to spend time connecting my devices to the hotel Wi-Fi. I also needed to spend time setting up pack-and-plays and getting everything squared away.

I made sure to bring this travel router to try out what this would look like in real time. I already had all the devices programmed and ready to go ahead of time to the network I had set on the Beryl 7.

When we got to the hotel, I had to connect one single device to the hotel Wi-Fi, and then I was able to broadcast that signal to all of the devices. It was stable enough for 5 iPads, a laptop, and a couple of phones, and therefore earned its place in my bag for the next trip I went on.

The next trip I went on was a quick work trip where we stayed at an Airbnb. I knew I'd be working pretty heavily, and I did not want to have to deal with potentially sketchy Wi-Fi, connecting to an unknown source, and then again having to connect all the devices I travel with.

On this trip specifically, I had two laptops, two iPads, and my phone, just for my own devices, let alone my team that I helped support technology-wise. I brought the Barrel 7 so that I could connect one device and then broadcast my own network, or at least that was the plan. What I ended up actually doing was connecting directly to an Ethernet port and not even having to connect and then broadcast via Wi-Fi.

One thing that I wish I would have done on that trip is I wish I would have set up the VPN earlier on my Beryl 7. I was able to do it during the trip, realizing how handy it would have been to do ahead of time, but I ended up needing to remote into my network rack back at the office.

While I can do that through VPN connections on my laptop, having one on this portable router, for some reason, just feels so much easier because then I can connect quickly on my iPad as well without having to toggle through things. I can just know that anytime I connect to this router, or if anybody else needs to connect to it, they can all be on the same VPN.

Personally, for me, it was just to change some settings and prep some things for the upcoming week. But, I could see this being super helpful for those who have Home Lab servers that need troubleshooting or other things like that. Further, if you have a work VPN that you need to be connected to, check with your employer.

Potentially, this could be a great option for you to not have to connect several devices, but you can connect one. For some work, that may be a great option. But, one thing to keep in mind is the speed limitations if you are choosing to use VPN. Moving things around on the network that you're connected to should be fine, but pulling files through the VPN to your device or vice versa will feel very slow.

GL.iNet Beryl 7: Final verdict

Whether you're working out of a coffee shop and don't want to connect multiple devices, or you have a secure VPN you need quick access to on any device you're bringing. If you simply want to be able to connect to a Wi-Fi network and turn it into a wired network, or take a wired network and turn it into a wireless signal, a little travel router like this can make things a lot easier.

Or perhaps you're like me, and you're starting to learn more and more about how scary network traffic can be, and you want to make sure that you're never connecting directly to a sketchy Wi-Fi. That's a great first step, and utilizing something like this and a VPN to help scatter your traffic may be a spectacular solution for you.

If you're looking for more networking capabilities, more features, and more power, make sure to check out GL.iNet for some of their other spectacular options, or keep an eye out for more reviews coming.