Technology

• Aikido researchers uncovers ChainDrop, a Shai‑Hulud variant infecting 1,300+ npm packages with an infostealer
• Attackers compromised GitHub accounts tied to popular libraries (Keyv, Cacheable, flat‑cache, file‑entry‑cache) and pushed tainted releases with 2B monthly downloads
• Malware exfiltrates developer/cloud credentials and secrets to a public GitHub repo; admins should treat affected systems as compromised even after removal

Another Shai-Hulud variant has been discovered in the wild, infecting more than 1,300 npm packages with an infostealer.

Security researchers Aikido reported finding “at least 868 packages (across 1381 versions) that have been compromised by the worm.”

Shai-Hulud is a self-propagating supply chain malware that targets software developers by compromising open-source packages and CI/CD pipelines. It steals credentials, API keys, and access tokens and then uses those stolen secrets to publish additional malicious packages.

What to do in case of an infection

In May 2026, actors claiming to be associated with the TeamPCP group publicly released the Shai-Hulud worm's source code, saying they were “open sourcing the carnage” and inviting other threat actors to adopt and modify the code. Since then, there were multiple copycat campaigns and variants, including this one which Aikido dubbed ‘ChainDrop’.

Aikido said the attackers compromised the GitHub account of the person maintaining Keyv and Cacheable, widely used open source JavaScript libraries for caching data in Node.js applications. From there, they were able to move into other popular utilities such as flat-cache and file-entry-cache, as well as packages associated with organizations such as Deliveroo, Ornikar, OneReach, Picsart, Qlik, and ServiceTitan.

The malware was pushed directly into the projects’ main branches, and then generated additional package releases. The compromised packages have a combined 2 billion monthly downloads.

Aikido says the infostealer grabs developer and cloud credentials, encrypts them, and then sends them to a public GitHub repository called “Shai-Hulud: Here We Go Again.”

It also steals local configuration files, GitHub PATs, workflow tokens, and other ghp_, gho_, and ghs_ tokens, certain npm tokens, GitHub Actions secrets, AWS credentials, Kubernetes secrets, and more.

The researchers are saying system admins who installed a tainted package should treat their developer workstation or CI/CD runner as compromised, even if they removed the package.

Not too long ago, one of the world's most data-driven companies admitted that its AI spending was becoming “harder to justify”. Uber's President and COO, Andrew Macdonald, told the Rapid Response podcast that the company had blown through its entire 2026 AI budget in roughly four months, with around 5,000 engineers leaning on Anthropic's Claude Code.

Uber isn’t alone. Forrester research found that enterprises are deferring around 25% of planned AI spend to 2027, as CFO scrutiny over ROI intensifies. And McKinsey's State of AI report summarized that while 62% of companies are experimenting with AI agents, only 23% have scaled them in even a single business function.

While these may look like the statistics of a technology that isn't working, they’re actually the statistics of a technology being used in the wrong way.

If we rewind back to 1987, Nobel laureate economist, Robert Solow, observed something that many at the time really resonated with: “You can see the computer age everywhere but in the productivity statistics.” Computers were everywhere across the innovative businesses that had invested heavily in them, but the productivity numbers didn’t move.

The returns only materialized years later, once organizations stopped bolting computers onto old processes and started fundamentally redesigning how they worked.

Many executives, alongside Uber’s COO, are at exactly that inflection point with AI - people are using it, running out of budgets to maintain usage, and at the same time, not really seeing the productivity boost they were hoping for.

This is the Solow Paradox repeating its course, which begs the question: will enterprises learn from previous mistakes?

The flatline behind the hype

There’s a critical distinction that most enterprise leaders are still failing to make: AI activity is not the same as AI maturity. You can run 40 pilots, adopt six platforms and report impressive usage statistics, and still be no closer to measurable business value.

Uber found this out in painful, public fashion, and has since openly questioned whether the rising cost of AI token usage is translating into proportional productivity gains. What makes Uber's situation instructive is not just the financial exposure, but how the organization approached adoption. Internal leaderboards were introduced to rank teams by AI tool usage, with the incentive being to use more tools.

The outcome was more usage, but the business impact slowly became harder to justify.

This is what happens when you gamify adoption without redesigning the workflows underneath it. You optimize the tool usage metric, not the business outcome. Uber has now joined several other top organizations, including Microsoft, Meta and Amazon, in capping AI usage to tackle the issue.

What’s interesting here is that when AI token usage is unconstrained, activity becomes the proxy for progress, but when it’s capped, organizations are forced to confront a harder question: what is each token actually producing?

In that sense, token spend behaves like an economic mirror. It scales immediately with adoption, while productivity only improves when workflows are redesigned. The gap between the two is where most AI ROI disappears.

The real culprit: Individual task optimization

When AI tools are deployed at the individual level, they tend to optimize the task, not the workflow.

A developer writes code faster, a marketer drafts copy in a fraction of the time, or a data analyst generates a summary report in minutes rather than hours.

All of these examples are real gains, but if the code still sits in a review queue for four days, if the draft still passes through three rounds of manual approval, or if the report still requires someone to manually transfer it into a decision-making dashboard - the time saved will pool at the next bottleneck.

Individual productivity gains that don’t translate into workflow redesign don’t compound. They stagnate, and this is the core of the maturity gap. AI maturity isn't about how many tools you've adopted, or how many pilots you've launched. It's about whether you've moved consistently from opportunity to outcome.

That shift requires a fundamentally different way of working.

Now, the term ‘production-ready AI’ gets used loosely. It’s worth being precise about what it actually means in practice, because most enterprise AI deployments fall short of the bar.

Production-ready AI has four characteristics. First, the output feeds directly into a downstream decision or action without manual transfer. It’s embedded in the workflow, not adjacent to it.

Second, the system has clearly defined failure modes, so the organization knows exactly what happens when the AI gets something wrong, and who’s accountable for remedying it. Third, there’s a named owner responsible for performance, adoption and iteration. Finally, and most critically, the surrounding process has been redesigned - not merely augmented.

The framework that closes the gap

So, how can businesses make this shift in practice? The answer is maintaining disciplined execution.

One way to build that discipline is a structured cadence we call the 3-3-3 framework: three days to prioritize, three weeks to prove value, and three months to launch a first release. The logic is deceptively simple and deliberately structured.

In the prioritization phase, the question is not “what can AI do?”, it’s “which specific opportunity, tied to a specific business outcome, has the right combination of value, feasibility, data readiness, and organizational sponsorship to pursue right now?”

That focus alone eliminates a significant proportion of AI initiatives that consume resources without clear purpose. It’s the antidote to the open-ended experimentation that left Uber burning through its budget before April was out.

In the proof phase, the focus is validation - not in technical terms, but in commercial ones. Can this solution create measurable value for users and for the business? A proof of concept that demonstrates technical possibility without demonstrating business value isn’t a proof of concept, it’s a prototype without a destination.

In the launch phase, the solution moves into a real environment. It integrates with existing systems, gets adopted by the people it was built for and gets measured against the outcome it was designed to improve. Not against token usage and not against adoption rates.

This rhythm isn’t a rigid formula, however. The shape of the work always depends on the business problem, the data environment, the technical complexity and the organization's appetite for change. What the framework provides is momentum and the discipline to keep that momentum anchored in value.

Shifting from adoption metrics to outcome metrics

The most consequential change enterprise leaders can make right now is a measurement decision.

Enterprises that are serious about closing the gap between AI activity and business impact need to make three shifts. The first is from tool deployment to operating model redesign. Rolling out AI tools is table stakes but building a repeatable operating model - a structured path from idea to proof to scale - is the competitive differentiator.

The second shift is from adoption metrics to outcome metrics. Usage rates, logins and token volumes tell you whether people are using the tools, but they don’t tell you whether the tools are working. Define success in business terms from the outset: cost reduction, time-to-decision, revenue impact, customer satisfaction, and build your measurement framework around those outcomes.

The third shift is from centralized experimentation to distributed accountability. The AI factory model - where a central operating model connects business priorities with delivery, adoption and value measurement - works precisely because it distributes accountability across the organization. Every initiative starts with a clear owner, a clear problem and a clear definition of what success looks like.

Winning the AI day

The productivity paradox Solow identified in 1987 eventually resolved itself. Not because computers got better - though they did - but because organizations learned to reorganize work around the technology, rather than fitting the technology around old ways of working.

The same resolution is available to enterprises deploying AI today. But it requires leaders to make a deliberate choice - to stop measuring success in terms of how many tools have been adopted and start measuring it in terms of how many outcomes have been delivered.

The organizations that win the AI era will not necessarily be those with the largest number of pilots, but rather the ones that build the maturity to turn the right ideas into value and then scale that value with confidence.

That kind of maturity doesn’t happen by accident. It requires structure, discipline and the willingness to ask harder questions about what AI is actually delivering, and what it’s not.

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Thanks to rapid developments around AI, cybersecurity pros seem due for a reminder that the threat landscape has fundamentally changed. This time it's OpenClaw ringing the alarm bells, but in truth we see the same cycle repeating itself time and time again, just with new technology.

Within days of OpenClaw’s open-source, researchers discovered exposed management interfaces and malicious "skills" packages designed to trick users into installing compromised functionality.

While the legitimate security community did what it always does, innovate rapidly, attackers moved just as fast.

That reality should force organizations that haven’t already done so to rethink a dangerous assumption: the belief that if something malicious appears inside our environment, internet security products will detect it quickly enough to stop serious damage.

That assumption is unrealistic in the world of AI-driven automation and open-source agent ecosystems.

The better question is: ‘Why should unknown software be allowed to run in the first place?’

Uncontrolled AI adoption is the core issue

OpenClaw highlights the much larger issue of Shadow AI running across organizations. Employees are downloading local AI agents, experimenting with open-source models, installing community-developed skills and connecting all of these tools directly to corporate resources.

Unlike traditional SaaS applications, many of these agentic platforms execute directly on endpoints. They request filesystem access, interact with browsers, connect to cloud services and automate business workflows.

Every new skill, extension or plugin expands the attack surface. While AI usage is an important progression of technology, the problem that’s emerging is that organizations frequently have little visibility or control over which AI tools are entering their environment, let alone what they're allowed to do once they arrive.

Detection can't keep up with automated attacks

The industry continues investing enormous resources into detecting threats faster and there is absolutely value in that; but OpenClaw illustrates why detection alone cannot be the primary strategy.

By the time a detection platform identifies suspicious behavior, an AI agent may already have accessed sensitive files, authenticated them to cloud services, downloaded additional components or exposed confidential information. Instead of asking how quickly we can detect something, organizations need to first ask whether it should have been able to execute at all.

Control AI without disrupting the business

To effectively mitigate AI-driven cybersecurity threats, the industry must embrace a Zero Trust approach that moves from an allow-by-default to a deny-by-default posture.

In the context of Shadow AI, application allowlisting ensures only approved agents run inside your environment, while application containment further limits what those trusted agents are allowed to do.

This way, if an agent is compromised, any unnecessary access to files, memory, scripting engines, networking functions or other applications is blocked entirely.

Together, these controls enforce the boundaries your business already intended to have.

One of the biggest misconceptions surrounding Zero Trust is that it requires organizations to lock everything down overnight. This isn’t true.

When done correctly, application control allows organizations to understand what's already running, establish normal operating behavior and gradually enforce policies without disrupting users.

Define what good looks like

Cybersecurity has traditionally focused on identifying bad behavior, yet attackers are constantly inventing new forms of it. A more sustainable model is to define what good looks like for your organization.

If a script or application like OpenClaw is not explicitly approved inside your environment, it shouldn’t be allowed to execute.

The bottom line is that if an AI agent doesn't require access to sensitive directories, cloud resources, PowerShell or credential stores, those interactions shouldn't be possible. This deny-by-default approach dramatically reduces the opportunities available to both attackers and compromised applications.

Rather than chasing an endless stream of new threats, you're enforcing known business requirements.

The leadership lesson

Open-source innovation has enormous value and will continue driving technological progress, but every major cyber incident teaches a lesson.

The Open Claw incident shows that organizations can no longer afford environments where any new tool is free to operate with minimal oversight. Leadership teams need to stop measuring success by how quickly they respond to breaches and start measuring how effectively they've reduced the opportunity for one to occur in the first place.

Open-source AI ecosystems will continue evolving at remarkable speed, new capabilities will continue to emerge. In tandem, attackers will continue to innovate their own methods. Fortunately, your security strategy doesn't need to change every time a new threat emerges.

The principles behind hardening your environment remain the same: know what belongs in your environment, and allow only what you've explicitly approved. Restrict what trusted applications can do, and treat every request for access as untrusted until proven otherwise.

Organizations that embrace that philosophy won't just be better prepared for OpenClaw, they’ll be ready for whatever comes next.

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With back-to-school season in the air, you might be looking to stock up on a new Mac for college. But doing so can be a confusing affair, with many different models and configurations to choose from, and you can waste a lot of time trying to work out what’s best for your needs.

To skip all the bother, just give our guide a read. We’ve put together everything you need to know, from which Mac is best for you to how to get those all-important student discounts. You’ll be kitted out and ready to go before you know it.

How to choose the right specs for your Mac

(Image credit: Apple)

When you buy a Mac, there are a few specifications you need to choose, including the chip, memory and storage. You’ll also need to pick a color and, with some Macs, extra options like the display coating and power adapter.

The first three factors — chip, memory and storage — are the most important, and the ones where there’s the most to learn.

We’ll start with the chip, which determines how powerful your MacBook is. More powerful and more recent chips will generally be better, and the higher the chip’s number, the more recent the generation it belongs to.

The chip usually comes in a few different tiers. There’s the baseline option, such as the M5, M4, M3 and so on, then Pro chips like the M5 Pro, M4 Pro and M3 Pro. Then there are Max chips, including the M5 Max and M4 Max. The most powerful level is the Ultra, and it’s limited to desktop Macs like the Mac Studio. The latest version there is the M3 Ultra.

Apple’s chips combine CPU, GPU and memory onto a single system on a chip (SoC). The CPU and GPU will have their own core counts, and the more cores you get, the better able the chip is to handle difficult workloads.

So, which do you need? The baseline chips will be more than enough for essay writing and basic research. On the other hand, you might want a Pro or even Max chip if you’re doing anything that involves complex apps, data processing or graphics work.

As for memory, this is built into the SoC, but you can increase or decrease it separately from the chip selection when configuring your Mac (although it’s worth noting that some memory amounts require upgrading to a more powerful chip). More memory helps speed up multitasking and is also useful for demanding workloads.

The amount of storage you choose depends on how long you want to keep the Mac, how much of a digital hoarder you are, and the type of things you’ll be storing. Run lots of large apps or work with high-resolution video files? You’ll need lots of storage.

Here, it’s best to err on the side of caution, as it’s very difficult (although not impossible) to upgrade your storage once you’ve bought your Mac. While it can be done, it’s not for the faint of heart.

One alternative is to plug in an external storage drive to give yourself extra space. This isn’t optimal, though, as it’s one more thing to carry around, and if it becomes accidentally disconnected, you could suffer data loss.

Make sure to regularly back up your Mac, either using an app like Time Machine or with a cloud service like Backblaze.

How to get Apple’s student discount

(Image credit: Apple)

Apple has a special education store for students, teachers and more. Here, there are various savings available, depending on the product. For example, the MacBook Neo is priced at $599, down from the regular $699 price (bringing it back to the price it had when it launched, before Apple’s recent price rises).

Apple says that student discounts are available to “current and newly accepted college students and their parents, as well as faculty, staff, and homeschool teachers of all grade levels.” You’ll need to verify your student status, which you can do online or at an Apple Store.

Student savings can be had on more than just Macs. In total, the discounts apply to:

• Mac
• iPad and select accessories
• Apple Watch
• Displays
• AppleCare+ for Mac
• AppleCare+ for iPad
• AppleCare+ for Display

Apple says to look out for the mortarboard icon, which indicates a product bought through the education store is discounted.

You get all the same perks as if you were to buy through Apple’s regular store. You can pick components and colors, trade in an old device, personalize your device with engraved monograms and emojis, pay in full or over time, and more.

The three best Macs for back to school

(Image credit: Apple)

Here, we’ve picked three Macs that we recommend the most for students. All three are Apple laptops, which will be perfect for carrying to lectures and around campus. Note that if you don’t have many lecture hours or are studying from home, you might want to consider the Mac mini, which starts at $699 in Apple’s education store. It’s a brilliant computer with an affordable price tag, but as it requires an external display, it’s not ideal for lectures and seminars.

MacBook Neo

(Image credit: Future)

The MacBook Neo is the perfect option for students on a budget. The default model comes with 256GB of storage, an Apple A18 Pro chip and 8GB of memory. It costs $599 from Apple’s education store, marking a saving of $100 over the regular price.

If your school or college work mostly involves writing essays and researching online, the MacBook Neo is exactly what you need and will be able to handle everything you do. The only question is whether you should upgrade to 512GB of storage — doing so also adds a Touch ID button to the keyboard, which is a handy way to log in and verify purchases.

MacBook Air

(Image credit: Lance Ulanoff / Future)

Stepping up, a solid mid-range option would be the 13-inch MacBook Air with M5 chip. You can choose between M5 chips featuring an eight-core GPU or a 10-core GPU, but we’d stick to the former — if you need more graphical power, the MacBook Pro will be a better option, which we’ll come to later.

Next, you can choose between 16GB, 24GB and 32GB of memory. The option you choose here depends on your workloads, but generally 16GB will be enough for most students. Again, if you need more, go for the MacBook Pro.

As for storage, the entry-level M5 chip is locked to 512GB of storage. To get more, you’ll need to upgrade to the higher-end M5 chip, which ups the price. Consider how much storage you need before making this move — if you have an existing computer, see how much you’re using with that. Bear in mind that you can’t change the internal storage after purchase, so if in doubt, opt for more.

Finally, there’s the matter of the charger. The M5 MacBook Air comes with a 40W charger that can handle loads up to 60W. If you want fast charging, which Apple says can power your laptop up to 50% in about 30 minutes, you’ll need the 70W option. This adds $20 to the cost.

MacBook Pro

(Image credit: Future)

For the most demanding student workloads, you’ll want to look at the MacBook Pro. Our recommendation is to start with the 14-inch model with M5 Pro chip. Skip the nano-texture display for now — it’s a nice addition, but unnecessary for students on a budget.

Do upgrade to the M5 Pro chip, however, or the M5 Max if you know you’ll be doing really heavy work that requires a lot of computing power. Unlike the MacBook Neo and MacBook Air, the MacBook Pro has built-in fans that mean it has a far superior cooling system that is much better equipped for demanding jobs. With that at your disposal, you can pick a beefy chip if you need it.

With the M5 Pro, your choices for memory are 24GB or 48GB. The former should be enough for most, but if you’re unsure, step up to the higher amount. While there are other options, including 36GB, 64GB and 128GB, these require swapping the M5 Pro for an M5 Max and paying a much higher price.

The configuration we’ve picked so far comes with 1TB of storage included, which is enough for most people. That said, anyone working with large photos and videos, high-grade apps or machine-learning models will likely need more space.

Finally, there’s the issue of the charger. The default option is 70W, which isn’t enough for fast charging (the MacBook Pro uses much more power than the MacBook Air, where 70W is enough for fast charging). Seeing as the 96W upgrade costs just $20 more and enables both fast charging (empty to 50% in about 30 minutes) and High Power Mode, we think it’s worth it.

• Microsoft aims to cut down on "tokenmaxxing" by employees
• New guidelines will look to control AI token use to focus on ROI
• This is despite Microsoft reporting record financial results recently

Microsoft has apparently been forced to introduce limits on how much AI usage its engineers are allowed followed reports that some have been taking things to extreme.

The software giant is looking to cut back on "tokenmaxxing" within the company - where employees use far more AI tokens that may be necessary.

In an email seen by 404 Media, Microsoft warned employees that new limits on token usage would be introduced as it looked to focus on getting the most out of its AI platforms.

New guidelines

“As we accelerate our use of GitHub Copilot to deliver on our goals, we all need to be aware of how we consume tokens,” the email to employees from Jay Parikh, an executive vice president at Microsoft said.

“Tokenmaxxing is not what we are optimizing for," he continued. "I want all of us focused on maximizing outcomes that move the needle for our customers and our business.”

“As such, we are updating our internal guidance and managing token spend with the same discipline we apply to every other critical resource."

In a bid to achieve “get greater value from our token investment”, Parikh went on to say Microsoft is making access to the cheaper OpenAI GPT-5.6 model the default model for internal use.

Employees were also reminded (via a link to updated internal Copilot guidelines) that as of July 2026 Microsoft divisions have an “AI token budget target,” with employees also able to track their individual AI spending.

“While there is no target spend value being shared at this time. The data shows that many engineers spend in the range of hundreds of dollars a month to a few thousand dollars in tokens,” 404 Media reported the guidelines as saying.

Parikh noted that Microsoft does not want to impair the company’s progress towards becoming “AI-first,” and that it will keep learning and adjusting its AI policies as models and products evolve.

“We are not optimizing for fewer tokens,” he said. “We are optimizing for more impact per token."

The restrictions may come as a surprise to some Microsoft employees, given that the company recently reported yet another bumper financial quarter, and in that respect should have money to splash out on AI usage.

However it is the latest step by Microsoft as it looks to focus internal AI usage. In May 2026, it was reported the company was reportedly canceling most of the Claude Code license it uses internally, with engineers being told to use GitHub Copilot CLI, with users given a June 30 2026 deadline to remove Claude Code from their workflows.

However tokenmaxxing has proven to be an issue at other tech giants - perhaps most notoriously at Uber, which was forced to admit it had exhausted its entire annual 2026 AI coding token budget in just four months due to massive employee adoption of agentic tools like Anthropic PBC's Claude Code and Cursor.

Amazon also recently revealed it had spent $1.8 million on an internal Claude Sonnet deployment intended for matching author details with product listings, after it ballooned far beyond its planned budget and was ultimately given menial tasks to do.

Lioness season 3 is only one episode down, but it's already off to a very chaotic start.

We now know that its eight episodes will comprise two simultaneous timelines: one, Joe being kidnapped by unknown Russian operatives and, two, the six months leading up to her capture.

The Lionesses were tasked with extracting a target out of a Ukrainian war space when foreign operatives "offered" him up to the CIA. However, it's now looking like this was a trap for something much bigger.

Will we find out what's actually going on this week? Probably not. Even so, when does Lioness season 3 episode 2 arrive on Paramount+?

What time can I watch Lioness season 3 episode 2 on Paramount+?

Lioness season 3 episode 2 will drop on one of the world's best streaming services in the US and Canada on Sunday, August 9 at 12am PT / 3am ET.

Here's when it will be released in other nations globally:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 1:30pm IST
• Singapore – 4pm SGT
• Australia – 7pm AEDT
• New Zealand – 9pm NZDT

When do new episodes of Lioness season 3 come out?

(Image credit: Paramount+)

As mentioned, Lioness season 3 will have a total of eight episodes, with new entries airing weekly. That gives us the following schedule:

• Episode 1: out now
• Episode 2: August 9
• Episode 3: August 16
• Episode 4: August 23
• Episode 5: August 30
• Episode 6: September 6
• Episode 7: September 13
• Episode 8: September 20

Samsung Galaxy Z Fold 8 Ultra: Two-minute review

Spare a thought for the Samsung Galaxy Z Fold 8 Ultra, which isn't having the easiest time of it right now. Yes, it's a fantastic foldable phone, but it was launched in the shadow of its upstart sibling, the Galaxy Z Fold 8, with Samsung taking the OG folding phones' name and applying it to a fresh, dare I say cute, design.

The Galaxy Z Fold 8 Ultra, by contrast, is almost indistinguishable from its predecessor, the Galaxy Z Fold 7. That's hardly a criticism — I loved that Android device — but it's hard to stand out when you've launched alongside to the phone world's shiny new object.

If we can put the 4:3 aspect-ratio Galaxy Z Fold 8 aside for a moment — you can read our Z Fold 8 review if you're so inclined — I'll focus here on the Galaxy Z Fold 8 Ultra, a fantastic folding device in its own right.

If you're unfamiliar with the Galaxy Z Fold line, here are the highlights for the Z Fold 8 Ultra. 'Ultra', but the way, does not mean it somehow more closely resembles the Galaxy S26 Ultra, though the camera and CPU enhancements do bring it more in line with the performance of its flagship cousin.

Folded, the Galaxy Z Fold 8 Ultra looks like a standard, if slightly narrower than normal smartphone (the S26 Ultra is a few millimeters wider). Unfolded, it's an 8.0-inch flexible display — and the chief upgrade on the display side is a mechanical and material engineering marvel.

Under the protective plastic cover, ultra-thin glass and a flexible AMOLED screen are a pair of new titanium panels. One is pure titanium, with an all-new perforation design for better bending performance, and the other is an alloy that, while thinner than the previous polymer sheet, is stronger and more reliable.

The Galaxy Z Fold 8 Ultra is on the right here — note the reduced crease compared to the Z Fold 7Lance Ulanoff / FutureThe flatter Galaxy Z Fold 8 Ultra is on the right.Lance Ulanoff / Future

The quite noticeable result is an essentially flat main screen with a far less visible crease, with the promise that over the years the bendy display won't suffer noticeable deformations (i.e., a more noticeable crease).

There are still five (yes, five) cameras, and while the 200MP main camera is essentially unchanged, the ultra-wide is now a more powerful 50MP camera (up from 10MP). The 3x optical zoom is still 10MP, and I do wish it were a 5x optical zoom (or at least 4x like the iPhone 17 Pro Max's). You can go far further with digital zoom, but then you have to wonder how much of an assist your photos are getting from the on-board AI (assume a decent amount). All of the photography is further improved by the upgraded image processing.

Under the hood is the latest Qualcomm silicon, which supports an impressive array of AI features. As with other Galaxy devices, there's almost too much AI here, but features like Photo Assist and Now Brief are standouts.

All in all, the Galaxy Z Fold 8 Ultra is an excellent follow-up to the Galaxy Z Fold 7, and is set to easily take over from its predecessor at the top of our rankings of the best foldable phones.

Samsung Galaxy Z Fold 8 Ultra review: Price and availability

• Even more expensive than the Z Fold 7
• Still a good value for a two-in-one device

(Image credit: Lance Ulanoff / Future)

I guess it was inevitable that with the price of RAM and components rising, the latest Galaxy Z Fold would be more expensive than its predecessor.

The new Galaxy Z Fold 8 Ultra starts at $2,099.99 / £1,899.00 / AU$2,999. If anything, the $100 bump in the US is less than I thought it might be; double that would not have been surprising.

Released alongside the smaller Galaxy Z Fold 8 ($1,899.99 / £1,699 / AU$2,699 ), the Z Fold 8 Ultra has an inarguably premium price, though it seems more reasonable when you consider that this is a two-in-one device.

The Z Fold 8 Ultra is available in Graphite, Cream, Green Shadow, and my test unit's Violet Shadow.

• Value score: 4 / 5

Samsung Galaxy Z Fold 8 Ultra review: Specs

Here's a breakdown of the Samsung Galaxy Z Fold 8 Ultra's key specs:

Dimensions:

Closed: 158.4 x 72.8 x 8.9mm
Open: 158.4 x 143.2 x 4.1mm

Weight:

215g

Display:

Cover display: 6.5-inch AMOLED
Main display: 8.0-inch AMOLED

Resolution:

Cover display: 1080 x 2520
Main display: 2504 x 2256

Refresh rate:

Cover display: adaptive 1-to-120Hz
Main display: adaptive 1-to-120Hz

Peak brightness:

Cover display: 2,400 nits
Main display: 3,000 nits

CPU:

Qualcomm Snapdragon 8 Elite Gen 5 for Galaxy

RAM:

12GB / 16GB

Storage:

256GB / 512GB / 1TB

OS:

Android 17 / OneUI 9

Cameras:

200MP F/1.7 main, 50MP F/1.9 ultra-wide

Selfie Camera:

Main screen: 10MP F/2.2
Cover screen: 10MP F/2.2

Telephoto

10MP F/2.4 3x optical

Battery:

5,000mAh

Charging:

45W wired, 20W wireless, Wireless Powershare

Colors:

Graphite, Cream, Violet Shadow, Green Shadow

Samsung Galaxy Z Fold 8 Ultra review: Design

• Folded, it looks virtually identical to the last model
• Easier to unfold
• Unfolds flat... finally
• The crease is almost gone

There's little argument that the Samsung Galaxy Z Fold 8 Ultra is, despite the new superlative, a visually iterative update. Folded, it's hard to distinguish it from the Z Fold 7.; it's virtually the same size and weight, meaning it's still lighter than the Galaxy S26 Ultra. It's still an Armor Aluminum Frame, though the Gorilla Glass Ceramic 2 from the last Fold 6.5-inch cover display is now Gorilla Glass Ceramic 3. On the back is Gorilla Glass Victus 2.

It's not until you unfold the handset, or rather attempt to unfold it, that the design changes, er... unfold.

First, there's a new chamfered edge along the fold inseam, which makes it far easier to insert the tips of your fingers and unfold the phone. Samsung told us it made this change because some users complained that the 4.2mm thick Z Fold 7 was difficult to open. The even thinner 4.1mm Z Fold 8 Ultra is, in fact, easier to open. I might even call it a pleasure.

Speaking of pleasure, there's another tiny little change that I really love. The power/sleep/fingerprint/Gemini button is no longer recessed, and is now so much easier to find by touch.

The biggest design upgrade is almost purely mechanical, and Samsung pulled it off by swapping out various materials and hinge designs to finally achieve a virtually flat and almost creaseless unfolded body and display. That is to say, the screen and chassis are flat, although if you lay it on a table, that ample camera bump will keep the whole thing rocking.

Lance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / Future

Inside the 4.1mm body — it's so thin it only just accomodates the USB-C port — Samsung has re-engineered the rigid titanium panel along the hinge strip, transforming the perforations into an almost 'A' shape, which allows for easier and more reliable bending. That panel is paired with a new titanium alloy sheet (it's thinner and stronger than the old polymer one). Together, they make the folding and unfolding processes better, and, when the phone is fully unfolded, allow for a virtually flat frame and the least noticeable crease yet. I'll have more to say about this design in the Display section below.

(Image credit: Lance Ulanoff / Future)

As I've been carrying around the Z Fold 8 Ultra and opening and closing it, people have consistently asked how long the phone might last, and whether it fatigues at the bend. I reply that, in the course of using and testing Samsung's folding phones over the last seven years, I've found them surprisingly resilient.

This model is actually water-resistant (IP48; yes, I ran it under water, yes, it survived, and perhaps enjoyed it), though I would not take it to the beach if it's not in a sealed case. When I traveled to South Korea last month. Samsung showed me how it torture-tests these devices, including folding and unfolding them thousands of times. I'm quite confident that with normal use the Z Fold 8 Ultra will last for years — at least through all seven years of Samsung's promised OS and security updates.

• Design score: 5 / 5

Samsung Galaxy Z Fold 8 Ultra review: Displays

• Main screen is almost perfectly flat
• Responsive, colorful, main screen has sunlight-beating brightness
• Cover screen is wide enough to be useful as a regular phone
• I wish the cover screen was a little brighter

(Image credit: Lance Ulanoff / Future)

Samsung now has enough experience making folding phones to be well into the refinement phase. The Galaxy Z Fold 8 Ultra is already thin and light enough, and the last model, the Z Fold 7, folded the screen so tightly that there was barely any gap between the two halves of the display. Now, though, the new display technology allows the screen to unfold virtually flat and, thanks to both the hinge engineering and new anti-reflective coating, make the crease very close to invisible.

The crease is not entirely gone. When I run my finger over the center of the 8-inch display I can feel it, and if I view the screen at the right angle, I can just make out the slight half-inch-wide indent.

(Image credit: Lance Ulanoff / Future)

Still, everything looks fantastic on the tablet-size display, which now sports a 2504 x 2256 resolution, a slight upgrade from the Z Fold 7's 2184 x 1968 resolution. I played games, watched video, viewed countless photos, used it for full-screen turn-by-turn navigation in maps (it's easy to get lost in London, which I was visiting for the Galaxy Unpacked event at which this phone was launched), and played more games.

(Image credit: Lance Ulanoff / Future)

If I had one real criticism of the main screen, it's that it no longer has a digitizing display — but this is not an issue new to the Z Fold 8 Ultra. Samsung dropped this feature on the Galaxy Z Fold 7, and there were rumors that the S Pen-supporting digitizing layer would return with the 8, but that didn't happen. Without it, and a special S Pen, to protect the phone’s flexible display, I really don't feel comfortable drawing on it with a universal rubber stylus (which you can buy from third-party providers, but which lack the S Pen’s unique features.

(Image credit: Lance Ulanoff / Future)

The cover screen reads as a 6.5-inch display, but that's measured diagonally, and the reality is that it's not as wide as the display on the Samsung Galaxy S26 Ultra. The Z Fold 8 Ultra cover display is about 2.5 inches wide, and the S26 Ultra is about 2.75 inches.

I still find the Z Fold 8 Ultra's cover display more than usable. The virtual keyboard is large enough for me to comfortably type on it. Websites, texts, and social media look good on it. The only issue I found is that its max brightness is not as strong as the inner display (3,000 nits, max), and it was occasionally overwhelmed by direct sunlight.

It's also a good-looking screen across multiple content types and activities thanks to the variable refresh rate that can sit anywhere from a power-sipping 1Hz up to a silky smooth 120Hz.

• Display score: 5 / 5

Samsung Galaxy Z Fold 8 Ultra review: Cameras

• Excellent collection of cameras
• Best image processing I've seen from Samsung to date
• Finally, a 50MP ultra-wide camera
• Wish the telephoto was 5x optical

(Image credit: Lance Ulanoff / Future)

As with most of the Galaxy Z Fold 8 Ultra, Samsung didn't completely reinvent the photography suite. Instead, we have a strong collection of cameras with some key improvements, chief among them a much more powerful 50MP ultrawide and the overall updates to the ProVisual engine for some of the best photography I've ever achieved with a Samsung smartphone.

Yankee StadiumLance Ulanoff / Future3x zoom moon shotLance Ulanoff / FutureUsing digital zooom. Not the detail on the moon, which is likely added by AI.Lance Ulanoff / Future

I've spent more than a week photographing everything from the iconic landmarks of London to a soccer match between Wrexham and Liverpool at New York's Yankee Stadium. In virtually every scenario, the Galaxy Z Fold 8 Ultra's cameras did not disappoint. Samsung's ProVisual engine is finally focused on color fidelity, and while I can use Galaxy AI Photo Assist to alter mu images to my heart's content, I applaud Samsung's focus on photographic reality.

To recap, here are all the cameras (five of them!) you get:

• 200MP wide
• 50MP ultra-wide
• 10MP telephoto (3x optical)
• 10MP selfie (main screen)
• 10MP selfie (cover screen)

Like most high-megapixel main cameras on phones, the Galaxy Z Fold 8 Ultra's 200MP and 50MP cameras default to a binned mode, squeezing multiple pixels into one (the main 48MP camera on iPhone 17 Pro, for instance, similarly defaults to 24MP). The result with the Z Fold 8 Ultra is 12MP photos, unless you choose 50MP or 200MP. The majority of my photos were shot with the 12MP default.

Lance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance Ulanoff

Even though Apple defaults to a higher resolution, Samsung's overall higher megapixel count means it's theoretically squeezing even more information into each photo. In anecdotal side-by-side shots, Samsung's photography is now as good as, and sometimes better than, what I can get with the iPhone 17 Pro Max.

Portrait-mode photography is excellent, with the processing effectively separating wisps of hair from the bokeh background.Lance UlanoffLance Ulanoff / FutureLance Ulanoff

Portrait-mode photos have become a real highlight in Samsung's photographic arsenal. From the very first photo I took of my colleague Axel Metz (above) to a shot of my son and his girlfriend, I've been impressed with the phone's uncanny ability to capture every detail and strand of hair while warmly blurring the background. My favorite shot is this one, of one of the Beefeaters who guard the Tower of London guards. This gentleman was kind enough to pose for me, and I think even he was surprised at the result.

(Image credit: Lance Ulanoff)

While I was generally pleased with the telephoto performance, I'm not thrilled with the underpowered, 10MP 3x optical zoom lens. It obviously pales in comparison to the iPhone 17 Pro Max's 48MP 4x optical zoom. Those extra megapixels also help the iPhone produce unprocessed 8x zoom sensor crops. After 3x on the Z Fold 8 Ultra, everything else gets some digital enhancement. Most of the images I've shared are optical-strength only.

Lance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance Ulanoff

One lens that's gotten a big upgrade with the Z Fold 8 Ultra is the ultra-wide, which is now a 50MP lens. This helps improve the quality of those wide-angle shots, and macro images, as well. There's some real drama in these ultra-wide images, and I'm impressed with how even the edges remain sharp.

Lance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance Ulanoff

Night photography is also strong, and I was often pleased with how much light, color, and detail the Z Fold 8 Ultra could find in even the darkest environments.

Lance UlanoffLance UlanoffLance UlanoffLance Ulanoff

On the video side, the Z Fold 8 Ultra lives up to its name, letting you shoot and edit 8K video. I waded into my pair of hydrangea bushes and dozens of buzzing bees to capture some cool, up-close 8K footage that I was then able to fully edit inside the phone's camera app, including adjusting brightness, and even using the AI-powered audio scrubber to bring down the wind and sound of leaves brushing against the microphones.

(Image credit: Future)

One of the other highlights is the Dual Camera shooting mode, which, while using a front and back camera, produces a rather distinct result. Instead of the 10MP selfie-camera image appearing as a picture-in-picture window on the front-facing camera video — as it does when using the similar Dual Capture mode on Apple’s latest iPhones — the Galaxy Z Fold 8 Ultra creates a split-screen view.

A post shared by Lance Ulanoff (@lanceulanoff)

A photo posted by on

I used this mode a few times in London, most memorably at the Royal Palace and at Borough Market, where I shot the famous strawberry stand. It's a great effect, and creates some really engaging videos.

Lance UlanoffLance UlanoffLance UlanoffLance UlanoffLance UlanoffLance Ulanoff

The other most notable video feature is a Galaxy AI enhancement called My FanCam. As the name implies, it lets you focus on your favorite video subject. The example we saw involved video of a soccer game. On playback in the camera app, you select the Galaxy AI icon and then the My FanCam option. The system identifies all the moving people (it doesn't work with animals or anything other than humans). You select the one you want, and the video tracks that subject. But the best part is that it can auto-crop around the subject in the aspect ratio of your choice — perfect for sharing on social media.

I ran a couple of tests with My FanCam, and it worked perfectly every time.

@techradar

♬ original sound - TechRadar

• Camera score: 4.5 / 5

Samsung Galaxy Z Fold 8 Ultra review: Software

• One UI 9 is clean, elegant, and intuitive
• Lots of AI, but none of it gets in the way

(Image credit: Lance Ulanoff / Future)

The Samsung Galaxy Z Fold 8 Ultra arrives with Android 17 and OneUI 9. It's a great combination. Overall, OneUI is a great Android overlay, because it's useful without getting in the way of Android. There are still some odd choices, like the existence of a Galaxy web browser that I never use (does anyone?), but some of the native Galaxy features are actually quite useful.

It's also a system with multiple AI platforms: Bixby, Galaxy AI, and Gemini. Of the three, Bixby, which can answer general questions and step into controlling key phone features, got the least amount of use. I do like though for it for how it lets you dig down to settings like brightness control without ever digging into settings. I could simply talk to Bixby and tell it what I wanted, like when I asked, "Can you make sure the brightness is set to 100%?" Bixby opened settings, brightness control, and pushed it to 100%.

Galaxy AI is a far richer collection of native AI tools, ranging from on-screen awareness to voice-driven photo editing.

All I said was, "remove the old man"FutureFuture

I had some fun editing photos with my voice — and I was shocked by how good the results were. With the above photo pair, I simply asked Galaxy AI to "Remove the old man". There was no hesitation, and in about 20 seconds I had the second image. I was gone, and Galaxy AI filled in the rest of my friend's arm, turned a small satchel he was carrying into a shoulder bag, and fleshed out the guy behind me. It looked like reality.

There's also a whole collection of Now features, including the "your world on a single screen" Now Brief, which now adds custom cards, and Now Nudge, which pops up contextual guidance for things like multitasking and automatically noticing that you might want to add an appointment to your calendar. I couldn't get Now Nudge working for me in messages in RCS — I suspect it may take some time for the system to learn about me and start making these suggestions.

Lance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / Future

On the quality-of-life front, the QuickShare updates that make sharing between this Android Phone and iPhones (and Macs) possible have been a revelation. I feel as if the world's been thrown open, and I can only say it's about time. Okay, I know that's a bit much, but this feature update is bigger than you might think.

Gemini is especially powerful if you give it access to personal details and data inside apps like calendar and mail. When I asked Gemini, without preamble, "Where am I going today?" it looked in my emails and gave me my schedule and location for my next meeting. Impressive.

Features like Circle to Search can be summoned by holding down the virtual home button and then circling on-screen objects. The results are quick and accurate

I can also hold down the power/sleep button to summon Gemini. Six months of access to the more powerful Pro version comes with the phone; after that, you have the most basic Google AI, which is still pretty good.

• Software score: 4.5 / 5

Samsung Galaxy Z Fold 8 Ultra review: Performance

• Powerful Qualcomm Snapdragon 8 Elite Gen 5 for Galaxy
• Performance is peerless
• Back can get a little hot

This is a powerful and smoothly performing smartphone. Qualcomm's latest silicon virtually matches the iPhone 17 Pro Max's A19 Pro Geekbench 7 single- and multi-core scores. The numbers, by the way, appear lower than phones tested last year with Geekbench 6 because, in the upgrade to 7, Geekbench completely recalibrated how it measures performance.

In the real world, I have yet to run into a task or situation the phone couldn't handle. Games like Asphalt Legends looked and ran perfectly. The Galaxy Z Fold 8 Ultra can handle multitasking with ease — you can have up to four apps open simultaneously on the main screen — and editing 8K video is seamless.

Lance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / Future

There were times when I could feel the back of the phone getting warm, but not so much that it became uncomfortable to hold.

In other performance areas, like audio, the speakers can get loud but with virtually no bass; they can also sound a bit tinny. Call quality is excellent, though my first few call tests were with phone scammers who somehow instantly found the new number.

5G speeds and WiFi 7 connectivity were strong and, with enough signal, fast. I've also enjoyed a solid Bluetooth 6.0 connection to my Samsung Galaxy Buds Pro 2 and Galaxy Watch Ultra.

Samsung Galaxy Z Fold 8 Ultra benchmark scores

Samsung Galaxy Z Fold 8 Ultra

Geekbench 7 single-core

1835

Geekbench 7 multi-core

4476

3D Mark Wildlife Extreme

6632

3D Mark Wildlife Extreme Low

1660

3D Mark Solar Bay Extreme Unlimited

1366

• Performance score: 4.5 / 5

Samsung Galaxy Z Fold 8 Ultra review: Battery

• 5,000mAh battery
• 45W wired charging
• All-day battery life

Even though this is a thinner Z Fold than last year, the battery is now a larger 5,000mAh, a feat made possible by the thinner titanium alloy, which replaced the thicker polymer layer and the new silicon-carbon battery technology (more power in less space).

That battery gave me, with constant, all-day, mixed use in bright sunlight, 12.5 hours of battery life. In our lab tests, we got a solid 14 hours. It's an all-day champ, to be sure.

The phone can also charge quickly with a 45W fast charger — I almost 50% in 15 minutes and 76% in half an hour — while wireless charging supports 20W charging. You can also put another Galaxy phone on the back and share a little power via Wireless PowerShare.

• Battery score: 5 / 5

Should you buy the Samsung Galaxy Z Fold 8 Ultra?Samsung Galaxy Z Fold 8 Ultra scorecard

Attributes

Notes

Rating

Value

The price of Samsung's best foldable just keeps going up

4 / 5

Design

Thin, flat, almost creaseless and just beautiful. I do wish the camera bump didn't mess up the on-desk flatness

5 / 5

Displays

Excellent displays and the upgrades to the main screen (flat, less of a crease, antireflection) make it a great content and productivity device.

5 / 5

Camera

Excellent collection of cameras. The ultrawide update is especially welcome. I do wish the telephoto was a bit stronger (optically). Powerful features like Photo Assist and My FanCam are strong additions.

4.5 / 5

Software

Clean, well-organized platform with lots of useful, baked in, AI features like Now Brief. Lots of AI.

4.5 / 5

Performance

Qualcomm's best mobile processor (tweaked for Samsung) does not disappoint.

4.5 / 5

Battery

5,000mAh battery. All day battery life is virtually guaranteed.

5 / 5

Buy it if...

You want the ultimate foldable phone
Sure, the Galaxy Z Fold 8 is adorable, but no other Galaxy folding phone has this collection of cameras, vast screen size, and thinness. It's the full package.

You want all-day battery life
The cutting-edge silicon-carbon 5,000mAh battery is a true workhorse.

You want the best photos
The Galaxy Z Fold 8 Ultra is unquestionably the camera leader among its Galaxy Z8 cousins, but it also has one of the best camera phone arrays I've used.

Don't buy it if...

You're on a bugdget
This is an exciting folding phone, but you will pay dearly. If cost is an issue, you may want to look to the Z Fold 8 or Z Flip 8.

You want more zoom
As much as I like these cameras, I still want a 4x optical zoom, and would love a 5x. Maybe next year.

Samsung Galaxy Z Fold 8 Ultra review: Also consider

Samsung Galaxy Z Fold 8
The Galaxy Z Fold 8 promises the same level of performance and AI as the Z Fold 8 Ultra, but in a cuter form factor and at a better price.

Read our Samsung Galaxy Z Fold 8 review

Motorola Razr Fold 2026
This foldable manages to match the Z Fold 8 Ultra in power and battery technology (but has a larger battery). The design is questionable, but it's generally a very good foldable that will save you money over the Z Fold 8 Ultra.

Read our full Motorola Razr Fold 2026 review

How I tested the Samsung Galaxy Z Fold 8 Ultra

I've been working, playing, and traveling with the Samsung Galaxy Z Fold 8 Ultra for almost two weeks. I've tried to use it as I would any smartphone, but with the added benefit of the large screen.

This is my seventh year testing foldable phones, and I am constantly astonished by the progress that's being made with the form factor, especially by Samsung. The Z Fold 8 Ultra is the full expression of its smartphone ideas and, as I carried it with me and pulled it out to take photos in London, Manhattan, and at home, I was constantly surprised and pleased with its performance.

More broadly, I've been testing phones for over 22 years and technology for 40. I use my wealth of experience to put products like the Z Fold 8 Ultra in context and perspective. As I see it, this is the best folding phone on the market right now.
Read more about how we test

First reviewed August 2026

Quantum risk has moved from theoretical to operational in 2026, and this shift is now impossible for enterprises to ignore. Google has committed to completing its post-quantum migration by 2029, the NCSC 2035, and the G7 says 2034. NIST has finalized its first full suite of post‑quantum cryptographic standards, triggering mandatory migration planning across regulated industries.

The timelines might not be perfectly aligned, but the message they send is: the risk is real, and the time to act is now. Breakthroughs in quantum hardware and AI‑accelerated quantum optimization are bringing “Q‑Day”ever closer. This is elevating quantum‑safe visibility, cryptographic discovery, and encrypted‑traffic intelligence to a now‑priority for every enterprise.

This is not the first time the industry has faced a widely anticipated but imperfectly understood threat. The parallels between quantum computing and Y2K are difficult to ignore. What began as stories of a supermarket system rejecting food as 80 years out of date, or a 104-year-old being invited to school because a computer registered her as four, soon evolved into fear as the scale of the problem became clear.

By 1995 the New York Stock Exchange had spent over $30 million remediating its systems. Y2k evolved into a defining moment for risk management and the key lesson was that organizations must understand and respond to exposure quickly and decisively.

Successfully addressing the threat quantum computing poses to encryption demands the same mindset, although this time applied across a far more complex and interconnected digital landscape.

The invisible threat already underway

A key distinction between Y2K and quantum computing is that the latter is not anchored to a single moment in time. The phrase “harvest now, decrypt later” describes the practice of adversaries collecting encrypted data today with the expectation that quantum capabilities will allow them to decrypt it in the future.

The implications of this tactic are significant, with 87 percent of organizations expressing concern about such scenarios as quantum computing advances.

Financial records, personal data, and intellectual property retain their value long past creation and the information encrypted today may still be sensitive well into the future. Decisions made now about cryptographic resilience will directly shape an organization's future security and reputation.

Why PQC is fundamentally more complex than Y2K

At its core, the Y2K challenge was a remediation problem with a relatively well-defined scope. Migrating to post-quantum cryptography is fundamentally different.

Cryptographic controls are deeply embedded across modern digital infrastructure, underpinning applications, APIs, cloud services, IoT devices, operational technology, and a growing web of third-party integrations. In many cases, they operate invisibly and are poorly documented. Organizations are not simply upgrading known systems, but first discovering what encryption levels have been used and where.

Addressing this means building a comprehensive inventory of cryptographic assets. All weak cipher suites, expired certificates, and non-compliant encryption methods must be identified.

Once found, organizations should standardize on stronger protocols such as Transport Layer Security (TLS) 1.3. This faster, more streamlined and longer protocol is ultimately more secure than older versions like TLS 1.1 and TLS 1.2, which will be broken by quantum computers in a matter of hours, minutes, or even seconds.

You cannot secure what you cannot see

In addressing both Y2K and today’s cybersecurity challenges, one principle consistently determines success: visibility. As organizations plan for a post-quantum future, 91 percent report that visibility into encrypted traffic is critical for PQC readiness.

Network-derived telemetry provides a scalable way to gain this. By analyzing traffic flows and metadata, organizations can build a comprehensive picture of cryptographic usage across both managed and unmanaged assets. This outside-in perspective complements internal inventories and helps uncover dependencies that might otherwise remain hidden.

With improved visibility comes the ability to assess risk more accurately, prioritize remediation, and ensure that the adoption of quantum-resistant approaches does not introduce unintended vulnerabilities.

Avoiding a repeat of history

The response to Y2K ultimately succeeded because organizations acknowledged the threat and took action. It was a forcing function that led to massive technology infrastructure upgrades and tech stack modernization.

Like Y2K, today’s quantum challenge isn’t just the potential event itself, it’s the scale of the remediation effort required across systems, applications, and embedded technologies, which makes early action critical.

The transition to post-quantum cryptography will not be achieved overnight. It will require a coordinated effort across security, infrastructure, development, and compliance functions, alongside close collaboration with vendors and strategic partners.

More importantly, it requires a shift in how the challenge is framed. Organizations that take proactive steps now by establishing a comprehensive inventory of cryptographic assets, improving visibility across their environments, and developing structured transition plans will be far better positioned to navigate the shift.

They will retain control over their timelines and reduce the likelihood of disruptive, last-minute change.

Those that delay may find themselves in a position that feels uncomfortably familiar. A known problem with a shrinking window in which to respond.

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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

We’ve been sold a comforting idea about artificial intelligence: that it’s making us dramatically more productive. Faster outputs, smarter tools, less effort. A quiet revolution in how we work.

But step back for a moment and ask yourself a simple question.

Do you actually feel more productive? Not faster. Not busier. Productive.

Because for most professionals I speak to, the answer is no.

Work feels quicker, yes. But also more fragmented, more reactive, and oddly more exhausting. The promise of efficiency is there on paper, but the true experience tells a different story.

That disconnect is worth paying attention to.

A typical working day

Look at how most of us spend a typical working day. We move between email, calendar, tasks, notes, messaging platforms, documents. Each tool holds a piece of the puzzle, none of them are the full picture. So, we become the system that stitches it together.

We check an email, then jump to our calendar to understand the context. We open a task list, then search our notes to remember why that task exists. We respond to a message, then dig through previous threads to find what was agreed.

This is not the work itself. It’s the management of work.

Now add AI into the mix.

We have tools that can summarize emails, draft responses, transcribe meetings, generate notes, and even suggest tasks. Each of these capabilities is impressive in isolation. They save minutes here, seconds there.

But they don’t remove the fundamental problem. In many cases, they amplify it.

Instead of switching between tools, we now switch between tools and their respective AI layers. An assistant in your inbox. Another in your document editor. Another in your meeting tool. Each one helpful, but none aware of the others.

So, we’re still managing everything ourselves. We’re just doing it faster.

This is where the narrative around AI productivity starts to unravel.

Defining success

We’ve defined success as speed. How quickly can a tool help you write, summarize, respond, or organize? And to be fair, AI has delivered on that front.

But speed without context is a blunt instrument.

If you’re responding faster but to the wrong priorities, you’re not more productive. If you’re generating more output but not moving meaningful work forward, you’re simply accelerating noise.

The real friction in modern work isn’t the execution of tasks. It’s the constant need to decide what matters, to reconstruct context, to align fragmented information across multiple systems.

AI, as it stands today, rarely addresses that layer.

At warpSpeed, we’ve approached this from a slightly different angle.

We didn’t start by asking how to make tasks faster. We started by asking why work feels so disjointed in the first place.

The answer was fairly obvious: everything is scattered. Email lives in one place, calendar in another, tasks somewhere else, notes somewhere else again. Every decision requires jumping between them.

So, we focused on bringing those elements together into a single, connected environment. a system where context flows naturally between them, facilitated by AI.

Not as a feature bolted onto individual tools, but as something that can see across them. Something that understands not just a single email or a single note, but the relationship between your communications, your commitments, and your priorities.

The difference, while subtle, is meaningful. This is how I like to think a successful assistant would function.

For example, when someone asks, “What should I focus on today?”, the answer isn’t generated in isolation. It draws on overdue tasks, unread emails that require responses, upcoming meetings, and previous commitments. It reflects the reality of that person’s day.

Small changes

Similarly, we’ve seen how small changes in interaction design can shift behavior. One example is email. By rethinking how users move through their inbox, we’ve seen people process large volumes of emails in a fraction of the time they previously spent. Not because they’re working harder, but because the system reduces friction and surfaces what matters.

These are not dramatic, headline-grabbing transformations. They’re incremental improvements grounded in real workflows. And importantly, they’re imperfect. We’re still learning, still refining, still discovering where the real value lies.

But they point to something broader.

If AI is to genuinely deliver on its promise of productivity, we need to rethink what we’re asking it to do.

Right now, most tools are designed to assist with tasks. Write this. Summarize that. Suggest a response. Create a list.

What’s missing is a deeper understanding of context and personalization.

Who is this for? Why does it matter? What else is happening around it? What should take priority?

Without that layer, AI remains reactive. It responds to prompts, but it doesn’t help you navigate your day.

Moving forward

To move forward, the industry needs to shift in three ways.

First, from isolated tools to connected systems. The value of AI increases exponentially when it can operate across your entire workflow, not just within a single tool.

Second, from generic intelligence to personal context. The most useful AI will be shaped by how you work, what you care about, and how you make decisions.

Third, from output to outcome. It’s not enough to generate content or complete tasks. The goal should be to move work forward in a meaningful way.

None of this is easy. It requires rethinking product design, data architecture, and user experience at a fundamental level. It also requires a degree of restraint. Not every problem needs another feature. Sometimes it needs fewer moving parts.

Productivity at scale

The irony is that the more powerful AI becomes, the more important simplicity becomes. Productivity at scale depends on removing the need to think through complexity, making intuition more valuable than ever.

Because ultimately, productivity isn’t about doing more things. It’s about doing the right things with less friction.

AI isn’t broken.

But the way we’re using it might be.

If we continue to layer intelligence on top of fragmented systems, we’ll keep getting the same result: faster work, but not better work.

The real opportunity lies in something quieter, but far more impactful. Using AI to remove the need to manage work in the first place.

Not to help you keep up.

But to help you stay focused on what actually matters.

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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

Mention high-frequency semiconductors, and the conversation often begins with gallium arsenide (GaAs). For decades, GaAs has been the material of choice for high-performance radio frequency (RF) devices that enable a wide range of applications, including satellite communications, radar, and mobile networks.

It is a mature, well-understood technology, and large, high-quality wafers can be grown economically, enabling consistent device performance and scalable manufacturing.

Yet a transition is underway. Increasingly, the industry is turning away from GaAs and towards gallium nitride (GaN), a material that offers clear performance advantages, particularly at higher frequencies, higher power levels, and more demanding operating conditions.

The promise of GaN is well established. The challenge lies in making it reliable, scalable, and commercially competitive.

And, as with many emerging semiconductor technologies, meeting that challenge is as much about measurement as it is about materials.

A material with advantages, and constraints

GaN enables the development of devices that can operate at higher voltages, higher temperatures, and greater power densities than their GaAs counterparts. This makes it particularly attractive for next-generation RF systems, including 5G and 6G communications, defense applications, and space technologies – where extreme environments are commonplace.

In principle, GaN can offer a straightforward upgrade path. It is sometimes thought of as a functional replacement for GaAs to deliver improved performance. Yet, in practice, the situation is more complicated, and a whole-system approach is required to redesign a module. Furthermore, the manufacturing approach for GaN is fundamentally different.

The hidden cost of heteroepitaxy

Unlike GaAs, which can be grown as large, high-quality wafers using established methods, GaN presents a fundamental manufacturing challenge because producing large, defect-free GaN substrates remains difficult and expensive.

As a result, most GaN devices are produced using a process called heteroepitaxy, whereby a thin layer of GaN is grown on top of a different substrate, typically silicon or silicon carbide. This approach allows manufacturers to leverage existing wafer technologies. But it comes at a cost.

When GaN is grown on a dissimilar substrate, differences in lattice structure and thermal expansion introduce defects into the material. These defects can affect everything from electrical performance to long-term reliability.

This results in a difficult trade-off: GaN offers superior theoretical performance, but achieving that performance consistently across wafers and devices is far more challenging than with GaAs. The advantage of using GaN therefore increasingly depends on material quality, and on the ability to control and understand it.

That relies on measurement.

Measurement as a competitive tool

For companies developing GaN technologies, metrology plays three distinct and essential roles.

The first is in process development. Growing GaN through heteroepitaxy involves carefully balancing multiple parameters, including temperature, deposition rates, and substrate preparation. Small changes can improve or degrade material quality. Without reliable measurement, it is difficult to know whether a process adjustment has made the material better or worse. Metrology provides the feedback needed to refine growth techniques and reduce defect densities.

The second role is in demonstrating material quality. In a market where performance depends heavily on the underlying material, manufacturers must be able to show that their GaN is superior to that of competitors. This requires measurement methods that are not only accurate, but also comparable across organizations. Customers need confidence that a claim about material quality means the same thing, regardless of where it is measured.

The third role is in device performance validation. Ultimately, customers care about how a device behaves in real applications. For RF components, this includes metrics such as power output, efficiency, frequency response, and thermal stability. Linking these device-level characteristics back to material quality is essential. It allows manufacturers to demonstrate that improvements in material growth translate into tangible performance gains.

Across all three areas, measurement is not simply a supporting activity. It is a central part of how competitive advantage is created and communicated.

From materials to systems

The challenges associated with GaN are part of a broader shift in the semiconductor industry.

As devices become more specialized and operate under more demanding conditions, performance is increasingly determined by subtle interactions between materials, structures, and processes.

This is particularly true in RF systems, where small imperfections can have outsized effects on signal integrity and efficiency.

It also connects to a wider trend seen in other areas of semiconductor technology, including photonics. There, heterogeneous integration is bringing together different materials and device types within a single system, creating similar measurement challenges.

In both cases, success depends on the ability to understand and control complexity at multiple scales.

A strategic inflection point

For the RF semiconductor industry, the transition from GaAs to GaN represents more than a simple material substitution.

It marks a shift towards technologies where performance is less constrained by established manufacturing processes, and more dependent on how well new materials can be engineered and characterized. This creates an opportunity.

Countries with strong capabilities in materials science, process development, and measurement can play a defining role in shaping how GaN technologies evolve and are applied successfully in the semiconductor industry.

The ability to measure material quality, correlate it with device performance, and establish trusted benchmarks will influence how quickly GaN is adopted across global markets. This means the future of high-frequency RF semiconductors will not be determined by materials alone.

GaN may offer superior intrinsic properties, but those advantages must be realized in practice. That requires consistent, high-quality material growth, reliable device fabrication, and credible performance validation – all of which depend on effective measurement and standards. This is why metrology will become increasingly central to RF semiconductor innovation, not as a downstream check, but as an integral part of development, manufacturing, and market adoption.

In high-frequency semiconductors, as in photonics, the ability to measure well is no longer just a technical requirement. It is becoming a defining feature of competitiveness.

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Prompt engineering was briefly the face of the AI jobs boom.

In 2025, technology recruitment firm SPG Resourcing reported that UK job listings for AI prompt engineers had grown by 180% over the previous year.

It was an eye-catching figure that captured the mood of the first commercial wave of generative AI. Businesses were trying to understand how to talk to LLMs and turn early experiments into something useful.

That requirement has not disappeared.

With job site postings for specialist AI roles in the UK rising by 61% from last year according to PWC, it’s clear that good prompts still matter. But most of that new demand is for people who can apply AI inside a business, not just talk to a model.

Many organizations have moved past the first demo. They are now trying to build AI agents, retrieval-augmented generation (RAG) systems, and AI-enabled workflows that operate inside the business.

That creates a different skills gap.

This is the shift behind what I refer to as ‘context engineering’. Although that term is not universally used, the capability is becoming essential.

Companies that want useful AI agents and retrieval-augmented generation systems need people who can design the environment around the model, not just the prompt sent to it.

From better prompts to better context

Prompt engineering is about the instruction, while context engineering is about the world around that instruction.

A support agent does not only need a well-written prompt, it needs the right customer record, policy, product history, and permission boundary. Similarly, a developer agent needs the relevant code, tests, dependencies, and deployment constraints.

In both cases, output quality depends on context. Without it, the model is guessing from incomplete evidence. With too much of it, the system becomes noisy and difficult to govern. The job is to make context useful, current, and controlled.

That’s what makes context engineering distinct from prompt engineering.

Agents raise the stakes

The rise of AI agents makes this more urgent. A chatbot with poor context may give a weak answer, but that same poor context may result in another agent making a serious error.

Once an AI system can call tools, query business systems, maintain state, and act across several steps, context becomes an essential part of the production architecture. It decides what the agent can see, what it can do, and how much confidence the business can place in the outcome.

I’m reminded of a joke about boundary testing. A developer walks into a bar and orders a beer, then he orders five beers, then he orders 999,999,999,999 beers, then he orders -1 beer. The bartender blinks, but everything is okay. A user walks into the bar, asks where the bathroom is and the whole bar explodes.

The same principle applies to AI projects. The first prototype may work against a narrow set of examples, then become fragile when it meets real data. Customer information sits in one system, operational data in another, and important knowledge in documents and files. The agent is expected to reason across all of it, but the context layer has not been designed for that job.

A financial services team, for example, may need to connect CRM data, an existing data platform, and internal documents before an agent can answer accurately. The hard work is not only moving the data. It is shaping it so the agent can retrieve the right evidence and stay inside the right permission boundary.

The job title is still catching up

This creates an awkward hiring moment. The need for context engineering is becoming clearer, but the job title is still unsettled.

Some organizations may seek to specifically hire ‘context engineers’, but many will not. The capability is more likely to appear inside roles such as AI engineer, agent engineer, AI platform engineer, applied AI engineer, or data engineer. In other businesses, it will be a team responsibility shared across data, platform, security, and software engineering.

Leaders therefore need to hire for the work, not the label. A candidate does not need to have ‘context engineer’ on their CV to be useful. The better signal is whether they understand how data moves through systems, how permissions are enforced, and how a prototype becomes something reliable enough for production.

This also means the talent pool is wider than many companies assume. Machine learning expertise is valuable, but context engineering draws heavily on existing engineering disciplines. Data engineers understand pipelines and retrieval.

Platform engineers understand operational resilience. Security teams understand access control and auditability. Software engineers understand how to turn messy requirements into maintainable systems.

The best candidates may look like full-stack AI engineers. They do not need to be specialists in every model, database, or framework, but do need enough range to connect the model layer with the business systems around it.

The Kubernetes lesson and what leaders should do now

The shift has a parallel with the move to cloud-native architecture and Kubernetes. Many companies treated Kubernetes as something to install, then discovered that the harder work was changing how teams built and ran software.

AI creates a similar risk. Companies can buy tools and hire a handful of specialists, but still fail to change the engineering habits around them. Context engineering requires teams to think differently about everything from documentation, and data ownership, to access, testing, and accountability.

It also changes the culture of software development. Engineers are already using AI to write, review, and iterate code. That can improve productivity, but it does not remove responsibility. In areas where performance, reliability, or security matter, human judgement becomes even more important.

CTOs and CIOs should not wait for context engineering to become a mature hiring category. They should start identifying the capability now.

The first step is to examine where AI projects are failing. Is the model genuinely weak, or is the system retrieving poor context? Are permissions clear? Can the team explain why the agent produced a particular answer?

The second step is to build cross-functional teams. AI cannot sit apart from data, platform, security, and product. In many cases, the best approach will be to upskill existing engineers who already understand the organization's systems.

The final step is cultural. Engineers need to become fluent in AI-assisted development while staying accountable for the systems they ship. Leaders need to make room for experimentation, but they also need clear standards for review, evaluation, and governance.

The model is not enough

AI hiring is changing because AI itself is moving into production. Models will continue to improve, and businesses will have many ways to access them. The harder advantage will come from knowing how to connect those models to the right business context.

Companies that understand this will build agents and RAG systems that are more useful, safer, and easier to govern. Companies that ignore it will keep blaming the model when the real weakness is the environment it has to work in.

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Light spoilers follow for Ted Lasso season 4 episodes 1 to 4.

Ted Lasso is back — and so, too, is Apple TV’s hugely popular sports comedy-drama. Three years after the final whistle was seemingly blown on the hit show, it returns not just as a continuation of where its third season left off, but also as a narrative and character-based evolution by way of a squad rebuild.

Even with its new line-up and the multi-year gap between seasons, though, Ted Lasso season 4 is a triumphant return to winning ways for the fan-favorite series — and I say that as someone who didn't dislike its divisive third season as many others did.

Home is where the heart is

Season 4 opens with Ted having to make a big life choice (Image credit: Apple TV)

Three years have passed since Ted (Jason Sudeikis) ended his AFC Richmond journey with the men's team and returned to Kansas to spend more time with his son Henry (Grant Feely). When season 4 reunites us with the eponymous soccer coach, we learn he's given up on the game entirely and now works as the assistant manager of a local grocery store.

A surprise visit from old friends — Richmond owner Rebecca Welton (Hannah Waddingham), Director of Football Operations Leslie Higgins (Jeremy Swift), and Keeley Jones (Juno Temple), now serving as chief marketing officer for the club's new women's division — soon has Ted questioning his current lot in life, though.

Ted Lasso season 4 is a triumphant return to winning ways

The reason? They want him to manage Richmond's newly founded women's team, work the same magic that he did with their male counterparts, and establish a similar culture of excellence that'll last well past his tenure in the dugout.

Higgins, Rebecca, and Keeley didn't just travel all that way for Kansas City's famous barbeque... (Image credit: Apple TV+)

Of course, this being the latest chapter of the beloved Apple TV show, it's not a spoiler to reveal that an at-first reluctant Ted eventually accepts their offer. After all, it would be an incredibly short season if he didn't.

This season's premiere feels like a largely superfluous prologue to the main event

Nevertheless, although this is a significant, life-changing choice for Ted, episode 1 spends far too much time grappling with the proposal laid at his feet — so much so, in fact, that I worried it would derail the series' return before it had really begun.

Indeed, with the bulk of episode 1's runtime spent on exploring Ted's inner struggle before its inevitable resolution, this season's premiere feels like a largely superfluous prologue to the main event of Ted actually becoming a Richmond native once more.

Higgins, Rebecca, Keeley, and Ted take in a US women's soccer match (Image credit: Apple TV)

That's not to say this narrative set-up isn't necessary, because it's the biggest decision Ted has faced since he left Richmond in the first place. Showing him wrestle with himself over whether he should take charge of Richmond's women's team, and deal with his loved ones' not-so-subtle nudges to do so, then, is a worthy storytelling exercise.

Nonetheless, an insightful subplot where Higgins learns about the Negro Baseball Leagues and Ted's inner conflict notwithstanding, I couldn't help but feel that season 4 episode 1's story could've been condensed and avoided the extraneous plot filler that drags out his prospective homecoming.

We're not in Kansas anymore

Welcome back, coach (Image credit: Apple TV)

Once season 4 properly gets underway in its second episode, though, it's like the show has never been away, nor missed a beat. Indeed, it effortlessly slips back into the purposeful stride that underpinned its first two electrifying seasons and parts of its third — again, a season I still largely enjoyed.

Once season 4 properly gets underway... it effortlessly slips back into the purposeful stride that underpinned its first two electrifying seasons

There's a satisfying air of familiarity as Ted — and, by proxy, the audience — reunites with the pillars of the AFC Richmond community, too. Rebecca, Keeley, and Higgins aside, other well-known faces like Roy Kent (Brett Goldstein) and Coach Beard (Brendan Hunt) welcome us and Ted back in typically eccentric fashion, and further emphasize the continuity between the show's past and its latest chapter.

Roy Kent is one of the series' many fixtures who returns for its fourth season (Image credit: Apple TV)

By virtue of Ted managing Richmond Women, season 4 also represents a new era for the acclaimed series. With that comes a whole line-up of fresh faces — the first of which we're introduced to is diligent but emotionally cold soccer coach Alice Chilton (Tanya Reynolds).

It soon becomes clear that Alice is... a fascinatingly complex and likeable individual in her own right

Initially resentful of Ted for pipping her to the top job and Rebecca for not even considering a woman for said position, Alice starts out as a — and this'll sound harsher than intended — dollar store Roy Kent. Or, rather, the season 1 version of Kent, who was an antagonistic figure whose sole purpose was to rail against Ted's cheery demeanor.

Coach Beard (left) and Ted are joined on the staff roster by player-turned-coach Alice (right) (Image credit: Apple TV)

Thankfully, it soon becomes clear that Alice isn't a Kent knock-off, but a fascinatingly complex and likeable individual in her own right. She also not only comes around to respecting Ted, but also quickly embeds herself as an integral cog in a new-look, eccentric triumvirate alongside Ted and Coach Beard, as well as a fully-formed foil to this established intrepid duo.

Clearly, Ted's capacity to thaw even the iciest of exteriors has no limits, and I'm eager to see how Richmond Women's primary coaching team collectively evolves throughout season 4 amid myriad issues that'll come their way.

New team, new problems

Katy 'Boots' Quinn will become many viewers' favorite character (Image credit: Apple TV)

And fall their way, those problems most certainly do.

Jude Mack's Katy 'Boots' Quinn is easily the highlight of this season's new additions

Indeed, season 4 metes out its share of obstacles, starting with a goal-scoring crisis after Richmond Women's main strikers are ruled out for the season. Meanwhile, in a far cry from their time in charge of the men's team, Ted and Beard no longer have free rein to walk into the locker room whenever they please — an obvious boundary that becomes a recurring, comedic point of contention for all concerned. Ted also finds himself in plenty of awkward one-on-one chats with his new squad, most notably with zany, slightly unhinged goalkeeper Katy 'Boots' Quinn (Jude Mack), who's easily the highlight of this season's new additions.

Gemma, seen here after a local five-a-side game, is tapped to become Richmond Women's new striker (Image credit: Apple TV)

'Boots' is far from the only unique personality in the Richmond Women squad.

We don't get to meet the vast majority of this rambunctious rabble until episode 3 but, in its follow-up, they manage to do the impossible: make Ted lose his cool and lay down the law amid dressing room splits. Ultimately, though, they're an instantly lovable collection of characters with distinct quirks and personal problems that'll inform their individual character journeys, and I get the impression that viewers will be just as captivated by this group — and their various trials and tribulations — as they were by the men’s team.

Ted Lasso tackles its heavy real-world issues head-on

Off-the-field challenges also permeate many of season 4's early subplots, many of which give major supporting characters in Waddingham's Rebecca and Temple's Keeley a stage on which to shine.

From gender inequality and pregnancy and motherhood to systemic underfunding and the media coverage gap, Ted Lasso tackles these heavy real-world issues head-on. That's to be expected, but it's nevertheless pleasing to see the show do so with warmth, empathy, and the occasional slice of its trademark irreverent humor.

Lizzie will have to navigate playing for Richmond and being a mom in season 4 (Image credit: Apple TV)

On the whole, Ted Lasso season 4’s opening four episodes handle their secondary storylines reasonably well. However, a few subplots lean into comedy at the expense of substance and subsequently feel a little shallow due to their flippant execution.

Take episode 2, where Rebecca grapples with perceptions that she isn't much of a feminist. It's a subplot that highlights Waddingham's comedic timing and dramatic range, but falters somewhat by prioritizing quick laughs over meaningful narrative resolution, thereby coming across as unbalanced.

The other major misfire in episodes 1 to 4 is Goldstein's Kent.

His presence remains vital to the series, but he feels oddly overused in a season that has moved away from Richmond's men's team. Of more concern is how the show worryingly appears to be turning his character into a caricature of his signature gruffness. Pair that with his recycled 'will they, won't they' subplot with Keeley — an eye-rolling dance that's run its course — and Roy's evolution feels increasingly sidelined in favor of easy gags. Hopefully, a finer balance will be struck between the Kent of old and his new persona in chapters to come.

My verdict

Noteworthy flaws in Ted Lasso season 4's early episodes aside, it's great to see this wonderfully silly, optimistic, cosy comfort show back on the air.

There was understandable scepticism when Ted Lasso season 4 was officially announced, with plenty of 'cash-grab' and 'who asked for this?' murmurings in the wake of what felt like a definitive finale.

As heart-soaring returns go, though, Ted Lasso's comeback delivers a match-winning performance in its first half, rich in both laugh-out-loud moments and striking emotional notes. Keep up this kind of form, and few will argue against another trophy-laden season of television.

Ted Lasso season 4 episode 1 is out now on Apple TV. New chapters air weekly.

There has never been a construction race like the one now under way in the data center industry.

AI's demand for compute is driving the largest and fastest infrastructure buildout the sector has ever seen, with hyperscalers and developers racing to bring capacity online faster than power grids, planning departments or supply chains can comfortably keep up.

In that scramble, enormous attention goes to the things visible on a spreadsheet: megawatts, cooling, chips, network and, rightly, cybersecurity.

The dimension that gets quietly deprioritized is the physical protection of the buildings themselves. It is the easiest thing to defer under deadline pressure, and the hardest to retrofit once the concrete is poured.

A regulatory change in the United States is about to make that blind spot worse, and it is worth understanding even if you never operate a US federal facility, because of what it signals.

On 30 September, the Federal Data Center Enhancement Act is due to expire, with no replacement waiting. It set minimum standards for federal data centers, including, unusually, protection against physical intrusion, and it was the operational mandate that forced data-center-specific assessment.

Broader frameworks such as FISMA and the NIST control catalogue still apply, but they provide the principle; the Enhancement Act provided the practice. Principles without a mechanism to enforce them tend to be interpreted generously.

And when the government's own floor is allowed to disappear, the benchmark private operators quietly measure themselves against tends to go with it.

Security baselines

This is not a hypothetical worry about whether the requirement comes back. The Act's predecessor lapsed in 2022 and only survived by being folded into the following year's defense bill. A rule that needs a legislative vehicle to return is one that can quietly fail to, and security baselines rarely erode through a single dramatic decision. They erode through the absence of one: a mandate that simply never gets renewed because nothing forces the issue.

It helps to be concrete about what is at stake, because physical security is not an abstraction. It is the contractor with unescorted access to a hall of servers; the unmonitored loading bay; the maintenance door propped open for convenience; the departed employee whose credential still opens the cage. These are the routes by which data is stolen, infrastructure is sabotaged, and a facility the size of a warehouse is taken offline.

The real exposure is not in the data centers we already have. Established operators keep that spending in place through existing contracts and their own risk appetite. It is in the new builds, the AI-era expansions specced and procured at extraordinary speed, most of them private, built by developers no mandate ever bound. Remove the assessment framework and physical security becomes something that can be scoped down in procurement to hit a budget or a timeline, with no compliance flag and no one formally alerted. The gap opens in the facilities we are racing to build.

There is a contradiction at the center of this. Governments increasingly classify data centers as critical national infrastructure, the UK now does, and rightly so. Reducing their security baseline at the same moment runs in two directions at once. You cannot call something critical and simultaneously make its protection optional.

A sensible fix

The fix is not simply more regulation, though a sensible renewal would help. It is to stop treating physical security as a compliance obligation that rises and falls with the statute book, and start treating it as core design.

The consistent lesson from securing large-scale critical facilities is that physical security fails when it is a collection of disconnected tools, a camera here, an access reader there, bolted on at the end of a project.

It works when it is designed from the start as one integrated system, where access control, video, identity and alarms inform each other and an anomaly anywhere triggers a coordinated response.

Treating the physical and the digital as separate problems is part of how the gap forms in the first place. In a modern data center they are the same problem: a propped door, a cloned badge or a rogue contractor is a cyber incident waiting to happen, and a facility that cannot correlate a door event with an access log or a camera feed will always be reacting after the fact rather than stopping an intrusion in progress.

For operators, the practical implication is simple: the physical security of an AI data center should be specified at the same moment as its power and cooling, not bolted on once the shell is up. Retrofitting protection into a live, fully-loaded facility is far harder, and far costlier, than designing it in.

The AI buildout is a genuine engineering achievement, and the energy and compute challenges are real. But the industry is optimizing hard for the risks it can measure and deferring the one it finds inconvenient. A statute lapsing in Washington should not be what decides whether the buildings holding the world's most critical compute are properly protected.

For IT infrastructure we have all agreed is critical, getting its physical protection right should be a given, not something we quietly leave to whoever is under the most deadline pressure.

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Samsung Jet 95S: Two-minute review

I'm no stranger to testing powerful cordless vacuum cleaners, and have crossed paths with models that have boasted 280AW of suction before — my Dyson Gen5detect review is a case in point. The Samsung Jet 95S, announced earlier in 2026, also shares the same suction spec, but costs a fraction of the Dyson's RRP, and that wasn't the only pleasant surprise it came with. It began to impress even before I took it out of its packaging.

The box that was delivered to my door was much lighter than what I've experienced with other cordless vacuums recently, so much so that I thought it was surely missing parts. Once opened up, I didn't even need to glance at the user manual to put the free-standing dock together and assemble the vacuum — surprisingly very intuitive! And the fully assembled machine looked so much more compact that my Dyson V15s Detect Submarine hanging off its Free-Dok.

Well, 'compact' may not be the right word, but it's definitely shorter — about half the height of the aforementioned Dyson, but that's because the V15 hangs at a height. The battery pack, however, adds weight to the otherwise light stick vacuum, albeit the Jet 95S is still lighter than some of the newer Dyson's I've tested — tipping the scales at about 2.69kg with the heavier Jet Dual Brush+ floorhead compared to about 3.6kg for the Gen5detect.

A little more compact than a Dyson (right), the Samsung Jet 95S (left) is rather unassuming (Image credit: Sharmishta Sarkar / TechRadar)

Then there's the suction power which, as I've already mentioned, puts it in the same league as the Dyson Gen5detect, a stick vac that I'd readily recommend for its power. As good as the Dyson is, the Jet 95S can more than match that performance, even outdoing its more expensive competition in some of my tests, whether that's on hard floors or carpet. For example, where the Gen5detect might need two passes to suck up entangled hair from carpet fibres even in its Boost mode (maximum suction), the Jet 95S can manage it in one in its Jet mode.

And therein lies another point of difference that's impressive: where you typically get only three suction settings on most cordless vacuums, there are four on the Jet 95S, and even the lowest is better than Dyson's Eco mode.

While I can't fault its cleaning prowess, I found the main floorhead — the Jet Dual Brush+ — to lack easy manoeuvrability, even on hard floors, which means you're exerting extra energy to get the machine around your floors. That's not the case with the Slim LED brush, though, but that's designed for hard floors only and for squeezing under low-lying furniture.

The most surprising thing about the Samsung Jet 95S, however, is how much value it offers. For about half the price of the Gen5detect's RRP, you're getting the exact same suction and arguably better performance, in a more compact (and slightly lighter) setup, and no shortage of additional attachments. You even get a telescopic tube that you won't get with any current Dyson.

And while you can buy a Shark vacuum for less money, none offer the same kind of performance. So, in all honestly, it doesn't bother me that there's no additional perks here, like self-emptying or a mop attachment — the Jet 95S already packs in plenty of bang for your hard-earned buck.

(Image credit: Sharmishta Sarkar / TechRadar)Samsung Jet 95S review: price & availability

• Currently only listed on the Samsung Australia and New Zealand sites
• While NZ has no RRP listed, it's AU$799 in Australia
• Also available from authorised third-party retailers

Announced in March 2026, the Samsung Jet 95S costs AU$799 in Australia and is available to buy directly from Samsung or from select third-party retailers like The Good Guys and JB Hi-Fi.

It's also listed on the Samsung NZ site, but no price is mentioned, although third-party retailers have the Jet 95S listed for NZ$919.

Compared to some Shark cordless vacuums that are constantly discounted on, say, Amazon, this price does seem high, but it is, in fact, excellent value given its spec list and performance (as you will read in more detail below).

The similarly specced Dyson Gen5detect Absolute will set you back AU$1,549 at full price in Australia, but has been regularly discounted down to the AU$950 mark and it's still more expensive than the newer Samsung. Sadly, the Dyson seems to have been discontinued in New Zealand as it's no longer listed on the officially website.

While it might be cheaper to buy a Shark, especially since the Shark PowerDetect Clean & Empty can regularly be had for under AU$700 and it self-empties, its suction cannot match the Jet 95S.

• Value score: 5 / 5

(Image credit: Sharmishta Sarkar / TechRadar)Samsung Jet 95S review: Specs

Weight:

2.5kg (with Slim LED Brush)

Dimensions:

25 x 93 x 20.2 cm

Filter:

HEPA filtration with pre-motor filter

Bin capacity:

0.8L

Max suction:

280AW

Max runtime:

60 minutes

Charge time:

210 minutes

Attachments:

Jet Dual Brush+, Slim LED Brush, Pet Tool+, Combination and Long Reach Crevice Tool, Flex Tool

Samsung Jet 95S review: Design

• Waist-high free-standing dock with integrated storage
• Expandable and bendable wand; comes with several useful attachments
• Lighter than many modern cordless vacuums, but not quite lightweight

As I've already mentioned, when the Samsung Jet 95S got delivered to my home, I honestly thought the box was missing parts because it was so much lighter than what I'd expected it would be. That was unfounded because everything was neatly packed away inside and it only took a glance at the individual parts to know exactly how they all slotted into place to assemble the Jet Standing Station (as Samsung calls the free-standing dock) and the stick vacuum itself.

Fully assembled, the stand with the machine is barely waist-high — well, it is for me and I'm only five-feet tall! And that gives the whole package a very compact feel compared to newer Dysons hanging off the British brand's Free-Dok. And even though the Jet 95S uses about the same amount floor space as the Dyson, it doesn't feel... imposing.

The heaviest bits are the base for the Jet Standing Station and the removable battery pack, with the latter making what is a very lightweight stick vacuum relatively heavy and slightly less unwieldy than some compact Shark vacuums I've previously tried. That, however, is an issue with all newer cordless vacuums with removable battery packs, so I can't quite blame Samsung for it. Despite the battery, though, the Jet 95S is still lighter than the Dyson V15 Detect or newer models, tipping the scales at 2.69kg with the Jet Dual Brush+ affixed to the wand (it's about 2.5kg with the Slim LED floorhead).

(Image credit: Sharmishta Sarkar / TechRadar)

Speaking of attachments: there are three motorised tools — the aforementioned Jet Dual Brush+ for carpets and hard floors alike, the Slim LED Brush for hard floors only and the Pet Tool+ for sucking up finer and shorter strands — as well three non-motorised options that include a crevice tool, dusting brush and a bendy attachment. The last tool is can be handy when you need to reach some awkward spots when using the Jet 95S in handheld mode.

The wand is even expandable, with four height levels, meaning anyone — short or tall — will find a comfortable posture that won't strain your back while you move the Jet 95S around your home. As a short person, I didn't need to expand the tube at all, but a taller friend (standing 5'5") needed to increase the height by just one level to make it more comfortable to use.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

Maneuverability is a small issue with the Jet Dual Brush+ floorhead and, sadly, that's the one I found myself using the most in a test space with mixed floors (tiles in the living and dining area, carpet in the bedroom), just so I didn't have to keep swapping out the floorheads each time a did a full-house clean.

The Slim LED Brush, however, is easier to move on its little wheels, but the battery making the unit top heavy can feel like it's impeding smooth movement. That said, the Jet 95S is definitely easier on the wrist compared to Dyson's heavier models that weigh upwards of 3kg.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

I don't have pets, but the Pet Tool+ has been designed to pick up strands that are typically small and thin, and easily missed by the larger floorheads, but it can also be used on upholstery.

By far my favourite attachment has to be the Flex Tool, which allowed me to get into little nooks and crannies that a straight tube would typically not allow for. You can attach it to the handheld unit or to the end of the wand, then affix the crevice or dusting tool to get to hard-to-reach spots high or low. In my case, I was able to vacuum an air-conditioning vent's grill by bending the Flex Tool at a 90º angle and attaching the small brush to the end of it. I was also able to get behind my couch from the side (rather than reaching from over the backrest) to clean up months of dust along the skirting boards.

The Flex Tool can help you reach high or low spots that aren't always easy to get to (Image credit: Sharmishta Sarkar / TechRadar)

As with many cordless vacuums available now, there's a small LCD display that shows you the suction setting and the time remaining for the chosen mode, but you don't get a breakdown of dust sizes and amounts like you do on a Dyson or even the Dreame Z50. The information on screen might be minimal, but I can't complain given how much it costs.

One design aspect that I'm still unsure about is the onboard dust canister. I was expecting it to have a bottom trapdoor that would open on the press of a button to empty (like a Dyson's bin), but that's not the case. I had to detach it from the handle, remove the filter and internal metal cylinder, then tip the canister over to empty it. It's not a difficult process, but I think I'd much prefer the Dyson method of emptying, with the option to dismantle the canister for a thorough clean every once in a while.

• Design score: 4 / 5

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSamsung Jet 95S review: Features

• No SmartThings support and it's definitely not necessary
• Smart Motion is a thoughtful feature, but ultimately superfluous
• Not necessarily a quiet vacuum

The 280AW of suction might be the headline act here, but one way Samsung has kept costs down is by not adding SmartThings support here like it has for its Bespoke Jet range. Which also means the Jet 95S doesn't use Samsung's Clean Station, but I don't mind that at all, especially at its price point. And, honestly, I didn't see the need for SmartThings support in any of the Samsung vacuums I've tested (stick or robot) and the Jet 95S makes an excellent case for not needing superfluous features.

Speaking of which, there is one feature that seemingly adds value but, ultimately, ended up being something I didn't ever need to use. It's called Smart Motion and it kicks in automatically when the vacuum is left switched on but at rest — like leaning against a sofa or chair — in case you need to, say, answer the door or move a cable from the vacuum's path. It will shut down completely when still and restart automatically if you move it within a minute.

Without the wand being extended, the Samsung Jet 95S (right) is shorter than the Dyson V15 Detect Submarine (left) (Image credit: Sharmishta Sarkar / TechRadar)

Given the power and mode buttons are so well within reach of the thumb, I found I was just switching the vacuum off if I needed to set it aside for a minute or two. And given its novelty, most users will likely even forget the feature exists. However, for those who are wont to just leave their vacuum idling against a chair or table, the Smart Motion feature will kick in and help conserve some battery life.

Dynamic suction is available, of course, which means you can just keep using the Jet 95S at its default setting (Mid) and let it do its thing. It's not really quiet, though, hitting about 89dB in the Jet mode in the Decibel X app on my iPhone in an otherwise silent room.

• Features score: 4 / 5

(Image credit: Sharmishta Sarkar / TechRadar)Samsung Jet 95S review: Performance

• Excellent and quick vacuuming on hard floors and carpets in all settings
• Most messes can be cleaned in a single forward motion
• No loss of suction on either floorhead even when pulling the vacuum back

Samsung really knows how to optimise suction power to the best effect — it did it with the Bespoke range of cordless vacuums where I said the suction lived up to its 'Jet' name in my Samsung Bespoke Jet review. The South Korean electronics giant has done it again with the cheaper Jet 95S, taking full advantage of the airflow moving with up to 280AW (Airwatts) of power.

As I've already said, that's the same amount of suction the Dyson Gen5detect boasts, although it's not industry-leading. The Dyson V16 Piston Animal has 315AW while the Dreame Z50 Station goes further with 330AW, and Samsung's own Bespoke Jet Ultra offers 400AW. It's not about the number, though as, ultimately, it's the air flowing through the machine that will determine how well the vacuum functions — and the Jet 95S performs remarkably well.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

With four suction modes at your fingertips (literally) — Min, Mid, Max and Jet — I found that the default setting of Mid was the best option and was happy to leave it as such for all my tests and regular cleaning. This mode adjusts suction automatically, whether that's when it detects different floor types or detects excess dirt.

Regular daily cleaning jobs were a walk in the park for the Samsung, sucking up visible dust, debris and hair even on the lowest (Min) suction setting on hard floors. It took a Mid setting on a very dirty carpet (covered in crumbs and hair) for it to get clean, but without having to repeatedly go over the same spot — just one or two passes were enough.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

To put the Jet 95S through more serious testing, I used it to clean up a thick layer of coffee grounds and a mixture of oats, chia seeds, tea from a tea bag and freeze-dried raspberries — between them, they indicate a variety of dust and debris sizes that a typical household would need cleaning up.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

On hard floors in my test space (matte-finish tiles) and set to the default Mid suction mode, the coffee grounds were sucked up in a single movement — forward to clear the middle of the dirty patch and back again to suck up another strip.

I was expecting it to take a full front-and-back pass to clear out the mixture but, again, it surprised me by picking up different-sized dirt in just a single forward motion, leaving a clean strip of floor in the middle of the patch. I noticed no scattering when larger particles hit the plastic frame of the floorhead either, which makes cleaning even easier.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

The same mix of oats, tea dust, chia seeds and fruit on carpet gave the Jet 95S a little more of a challenge, but that translates to needing a forward and backward pass to clear a strip (as compared to just a front swipe on hard floors).

Step it up a notch and both the Max and Jet settings can blow any of the competition out of the park. My biggest pet peeve is hair strands getting entangled in carpet fibres that don't necessarily come off even when vacuuming on, say, Dyson's Boost mode or the highest suction on a Shark, but I found 100% hair pickup during my testing of the Jet 95S. I also found no tangling within any of the motorised attachments.

• Performance score: 5 / 5

(Image credit: Sharmishta Sarkar / TechRadar)Samsung Jet 95S review: Battery life

• Maximum runtime of 60 minutes with non-motorised tools
• Quite average battery life with motorised floorheads
• Relatively quick recharge time, with handy battery life indicator

Battery performance, however, is quite average, with Samsung rating it for a maximum runtime of 60 minutes with the non-motorised attachments. That almost tracks, with my tests giving me 56 minutes on the Min mode (lowest suction) when the crevice tool was attached to the handheld unit.

With the motorised Jet Dual Brush+ floorhead and using the default Mid suction setting, I maximum I was able to eke out on a relatively clean floor was 37 minutes. This number will vary depending on how often dynamic suction kicks in, but it's not bad at all and quite competitive with other brands.

Move it up to Max and a full charge got me 10 minutes with the Jet Dual Brush+, while Jet barely give me 7 minutes. Again, it's on par with what I've previously experienced with Dyson and Shark alternatives.

Sharmishta Sarkar / TechRadarSharmishta Sarkar / TechRadar

Like I've previously mentioned, the Smart Motion feature might help some users conserve a little battery life but, in my opinion, it's neither here nor there and superfluous.

The Jet 95S took about 3 hours to top up from 21% to full, which is relatively quick compared to Dysons that offer the same 60-minute runtime (which average around the 4-hour mark), but I love that there's an indicator light above the handle that changes colour while it's charging.

It follows the traffic-light system where it's red when levels are low, yellow (more like orange) when it's come up to mid levels and green when it's fully done. This visual indication is handy when you need to complete a job in a larger home and don't necessarily need to wait for a full recharge.

• Battery score: 4.5 / 5

(Image credit: Sharmishta Sarkar / TechRadar)Should I buy the Samsung Jet 95S?

Attributes

Notes

Score

Value

It's very well priced for the kind of performance it offers.

5 / 5

Design

It may not stand out from a design perspective, but its compact, unimposing and has plenty of features to suit any user.

4 / 5

Features

It doesn't offer much that's different, and the one feature it does is, ultimately, superfluous.

4 / 5

Performance

It might come across as a no-frills stick vacuum, but it cleans remarkably well and can outperform even more expensive models.

5 / 5

Battery

Quite standard in terms of runtime, and that's absolutely fine at its price point.

4.5 / 5

Buy it if...

Value for money is priority when buying a cordless vacuum

Vacuums are frequently discounted, so you can always get a Dyson or Shark for cheaper than what the Jet 95S costs, but factor in its cleaning performance and the Samsung wins hands down.

You want a powerful vacuum cleaner

It may not match the suction of some other models on the market, but 280AW is still plenty and Samsung puts it to very good use here.

You regularly need a handheld vacuum

It's not especially light, but it's still easier to use in handheld mode than some of its competition. Moreover, the Flex Tool adds versatility to help you reach awkward spots and angles.

Don't buy it if...

You want a tech-laden vacuum

From a features point of view, the Jet 95S comes across as a no-frills option, so if you're after some smart tech, you'll need to look elsewhere... and spend more.

You want a mop attachment as well

There are plenty of alternatives that ship with a mopping floorhead, or you can opt for a robot vacuum, but the Jet 95S misses out.

You prefer to not clean the dust canister yourself

If self-emptying is a key criterion for choosing a stick vac, you'll need to look elsewhere.

Also consider

I might have scored the Samsung Jet 95S full marks, and I'd easily recommend it over anything else I've personally tested, but it's always good to have options. If you'd like a few alternatives, I've listed a few below at different price points for you to consider.

Shark PowerDetect Clean & Empty

It might have lower suction power than the Samsung Jet 95S, but it still cleans well and comes with an auto-empty charging dock that doesn't even need replacement bags. And while it's more expensive at full price than the Samsung, it's regularly discounted to below the AU$700 / NZ$800 mark.
Read our full Shark PowerDetect Cordless review, which is the non-emptying version.

Dyson Gen5detect Absolute

With the exact same suction and very good overall performance, this Dyson is packed with some sensible tech you won't find on the Jet 95S. However, it can be expensive, even when discounted, and it seems to have discontinued in New Zealand.
Read my in-depth Dyson Gen5detect review for more information

Samsung Bespoke Jet AI

I'm a little partial to the overall design of Samsung's Bespoke Jet vacuums and the Clean Station is one of the best self-emptying charging docks I've tried. The Lite models get you the same 280AW of suction, but the Ultra scores you 400AW, but they also cost more than the Jet 95S. Moreover, the AI part is basically market-speak for dynamic suction, but they all clean very well.
Read our full Samsung Bespoke Jet AI review to learn more

How I tested the Samsung Jet 95S

(Image credit: Sharmishta Sarkar / TechRadar)

I used the Samsung Jet 95S in my own one-bedroom apartment for about two months, cleaning every 2-3 days. However, I did put it through TechRadar's standard tests by sprinkling oats and tea dust from a tea bag. Additionally, I also created mixtures with chia seeds and pieces of freeze-dried raspberries to emulate different debris sizes that a standard home might encounter. This mixture was used on both hard floor — matte tiles in this case — and a mid-pile carpet.

Separately, I even vacuumed a handful of coffee grounds from tiles for additional testing.

To test its hair pickup, I collected my own strands from my brush and scattered them over the mid-pile carpet in the bedroom and walked over them for a couple of days to ensure they were well embedded into the fibres. I also scattered some breadcrumbs and biscuit crumbs on the same carpet, allowing them to also sink in over a couple of days.

Thankfully the Samsung Jet 95S was able to suck them all up and leave the floors in my home clean.

Read more about how we test vacuums

[First published August 2026]

• IPVanish has updated its Apple TV app to widen its VPN protocol choice
• Beyond IKEv2, the app supports WireGuard and OpenVPN (with Scramble)
• Both existing and new subscribers can unlock everything with a single step

IPVanish has given its Apple TV app a notable upgrade, adding support for the WireGuard and OpenVPN protocols in addition to the current IKEv2.

For anyone who streams from the sofa, this is a meaningful change. Protocol choice affects speed, stability, and how easily a VPN slips past networks that try to block it, so having multiple options is much better than a single default.

The update also comes with a bold competitive claim. IPVanish argues it's now the only provider offering WireGuard, OpenVPN (with Scramble), and IKEv2 together on Apple TV, building on its early arrival as one of the first premium services on the platform.

Subbu Sthanu, IPVanish's General Manager of Consumer Cybersecurity, framed the launch around the living room, saying the provider wants to give Apple TV owners "the ultimate balance of speed, security, and customization."

If you're shopping for the best VPN for your living-room setup, more protocol flexibility is exactly the kind of feature that separates a bare-bones tvOS app from a properly capable one.

IPVanish — starting from $2.19 per month
A fast VPN with a decent track record for unblocking streaming services, IPVanish can really help you boost your Apple TV experience. It supports unlimited simultaneous devices so you can extend protection to all your machines, too. With its cheapest plan working out to the equivalent of $2.19 a month — that's $52.56 for 2 years — IPVanish is also among the cheapest VPNs you can get right now.

What's new in the IPVanish Apple TV app

The refreshed app, rolled out in late July 2026, brings two of the most widely used VPN protocols to Apple TV for the first time, sitting alongside the existing IKEv2 option.

WireGuard is the headline addition. Built on a lean codebase with modern encryption, it's designed to deliver fast connections and low latency. This makes it well suited to streaming and gaming on a big screen.

OpenVPN is the other new arrival. As one of the oldest and most battle-tested protocols around, it's prized for flexibility, supporting both UDP and TCP connections and editable port settings.

Crucially, OpenVPN ships with IPVanish's Scramble feature. Scramble obfuscates VPN traffic so it looks less recognizable to networks that try to detect and limit VPN connections, which can help you stay connected on fussier Wi-Fi.

Why the VPN protocol choice matters

Apple TV just got more ways to connect.WireGuard and OpenVPN are now available in the IPVanish Apple TV app, joining IKEv2. More protocol choice. More control over your connection. pic.twitter.com/nJD37VE1s3July 27, 2026

The value of multiple protocols comes down to fit. No single option is best for every network, so being able to switch lets you match your connection to the situation.

WireGuard offers the best balance of speed and security for most people, and it's the one to reach for when you just want smooth 4K playback. OpenVPN is the more configurable fallback, handy when a network is being awkward or actively blocking VPNs, especially with Scramble turned on.

Apple has allowed Apple TV VPN apps for a few years now, but many providers still ship fairly basic living-room clients. Adding genuine protocol choice puts IPVanish a step ahead of rivals.

How to change protocols on IPvanish Apple TV app

There's no complicated setup involved. All existing and new IPVanish subscribers can access the protocols simply by updating to the latest version of the app from the tvOS App Store.

Once updated, open the app, head into its settings, and pick your protocol before connecting. New to the app entirely? Our guide to installing IPVanish on Apple TV walks you through it.

• Report claims 90% of NHS staff are using AI to assist with their work
• Heidi survey points to high AI use across healthcare
• AI looks to reduce the burden on healthcare professionals

NHS staff are increasingly using AI tools to improve workflows and handle admin tasks, and claim that patients are positive about the development, new research has claimed.

A survey of 1,000 healthcare professionals working in the NHS by Heidi found 90% of respondents revealing they are using AI in clinical work, with healthcare professionals driving the change, with nearly two-thirds (65%) adopting AI to assist in their workflow.

Rising administrative burdens in recent years may have contributed to the use of AI to assist in tasks, although it seems some AI use is happening regardless of official policies.

AI helps with the admin

Of those surveyed, 94% have increased their AI use at work in the past year, or kept it the same. Among hospital doctors, pharmacists, and mental health professionals, however, the figure is 96%.

The results of the survey clearly demonstrate a wide take-up of AI tools, no doubt driven by an increase of administrative tasks (experienced by 80% of respondents) which includes increased demand for documentation, particularly among nurses (61%), pharmacists (63%) any by GPs dealing with referrals and letters (52%).

While it is being used for drafting referrals and notes, AI is also being used to manage patient follow-ups (66%), and there is a belief that the technology is prolonging careers, by making the workload more manageable.

Dr Hannah Allen, Chief Medical Officer and GP at Heidi, said: "These findings reflect what we hear every day from patients and clinicians. Patients are ready for this, and healthcare professionals have already made AI part of how they manage a workload that has grown well beyond what most would call sustainable.”

Policies and oversight

Use of computers and patient data within the NHS has been closely monitored for years, and in recent years the challenges of AI have been highlighted, with various trusts implementing policies to handle generative AI use. Among these are the NHS AI Lab Code of Conduct, NHS England's Blueprint for AI in Health and Social Care, and the Information Governance (IG) Frameworks for handling patient data and other sensitive information.

So, the 35% expressing concern over patient privacy should be able to consult their local policies and procedures to ensure that their work doesn't infringe what has been put in place by the organization.

The march of AI across healthcare seems to be almost complete, and regardless of which tools are used, those governance policies should ensure admin is managed, data is kept private, and patient care continues to be the central focus.

Texas Governor Greg Abbott has paused new data center connections to the state’s grid pending audits on the requirements for new and proposed constructions. The audits will cover the revenue lost from data center tax exemptions, power usage and generation, infrastructure upgrades, water usage, and the impact on the local communities and environment.

Texans have seen their electricity and water bills increase significantly over the past five years. Data from Electric Choice shows the average residential electricity price has risen by over 25%, and data from the Texas Municipal League demonstrates the average residential water bill has risen by over 26%.

But the prices in Texas sit below the national average. So why then are they rising so fast, and what does it mean for other states in the US?

Prices rapidly rising

As new industries and houses are constructed, new connections need to be added. These connections are constructed by power grid operators, with the cost of upgrades generally passed on to consumers through utility transmission fees.

Infrastructural upgrades are also paid for by grid operators, with the costs of construction again passed back down to consumers through their bills.

The rapid increase in data center construction projects has been a particular issue in this regard. As data centers require enormous amounts of electricity, they require far more complex and expensive connections than are required of a typical residential connection.

But alongside the moratorium on new data center construction, Gov. Abbott has required data center projects that pass the states’ audit will be required to pay for their own connections and infrastructure. In a letter to the Public Utility Commission of Texas and the Electric Reliability Council of Texas, Abbot highlighted that 90% of new grid connections are data centers.

(Image credit: Electric Choice)

Electricity prices are also rising due to an increasingly unpredictable climate. Soaring temperatures place increased demand on electricity grids, especially as cooling systems for homes and businesses are switched on during peak times. The heat also causes electricity infrastructure to fail at a higher rate, causing additional costs as grids are repaired and replaced.

As for water prices, Texas has been subject to a four year drought. Per Washington Post reporting, Texas has been seeking alternative sources of water to extend supply. The downside is that in one such project, the state ended up paying the contractor responsible for a new groundwater collection project an extra 40% on top of the originally proposed $500 million.

The increasingly unpredictable weather is also wreaking havoc on existing infrastructure, especially when there are short periods of torrential rainfall. Sudden downpours can quickly overwhelm water infrastructure, damaging it or washing it away. Water treatment plants can also become overwhelmed and damaged. The cost of repairing and replacing infrastructure, as well as funding the much needed projects to create new water sources, once again gets passed down to consumers.

Couple this with the rapid increase in data center projects, which requires water usage during construction and for cooling, and prices will further increase. Texas currently sits in the number two spot for active data centers, slightly behind Virginia, but the number of planned and approved projects for Texas means the Lone Star state could soon become the number one state for active data centers.

Lessons for the rest of the US

As with all new technology, the pace of regulation falls a few thousand steps behind.

Numerous states have already begun issuing moratoriums on tax exemptions for data centers as the actual loss of revenue far exceeds earlier predictions. In Ohio, the loss of revenue has been $1.6 billion - far higher than the projected $136 million.

The new regulations introduced in Texas requiring data centers to pass the state audit before being hooked up to the grid have presented a second problem. Data centers providing their own on-site power are not subject to new grid connections, and can therefore bypass the audit.

One of the most cost effective means for producing on-site power are gas burning turbine generators. The downside for local residents in the vicinity of these sites is that noise levels have been compared to living near an international airport, and there are under-studied phenomena surrounding the infra-sound produced by these power projects.

There are also the climate implications of these sites. Despite the name, natural gas is a highly polluting fuel source that distributes pollutants both into the local area and the atmosphere, causing damage to local livestock, fauna, and the rest of the world.

As soon as I heard that Gemini Spark was now part of the Chrome browser I had to try it for myself.

Gemini Spark is an AI agent designed to take on longer-running tasks that continue in the background. It's much smoother now thanks to an update that incorporates the platform directly into Google's Chrome browser. So now the AI can actually browse the web alongside you, doing its own tasks, instead of simply talking about it, even if you close your browser.

Before you can try Spark, you need the right ingredients. You will need the latest version of Google Chrome on Windows or macOS, a personal Google account, and either a Google AI Pro or Google AI Ultra subscription. With the right subscriptions, you just need to set Safe Browsing to either Standard Protection or Enhanced Protection before Spark becomes available.

With those requirements out of the way, click the three dots in the upper right corner of Chrome and choose Settings, then AI Innovations or Gemini in the Chrome menu, where you can navigate to the Permissions section and switch on the Let Gemini browse for you option.

Now you can open the Ask Gemini panel at the top of Chrome and give it a task that benefits from browser access. Spark will show you its proposed plan before doing anything, and the first time you use it, Chrome will ask whether you want to connect your browser to Spark. Click Allow or Connect, and from then on you can start handing Spark more ambitious jobs.

If something involves making a purchase, entering sensitive information, or confirming an important action, Spark pauses and asks for your approval before continuing.

The video below shows you exactly how Spark works:

Comparison shopping

(Image credit: Future)

I first decided to see how the AI did at the often time-consuming but important chore of comparison shopping. I asked Gemini using Spark to find a good deal for a TV.

Instead of asking which television I should buy, I gave Spark a proper assignment. I told it to compare prices for a 65-inch model at Amazon, Best Buy, Costco and Walmart, look for promo codes, and calculate the final price after discounts then prepare for checkout.

Spark didn’t just provide a summary. I could watch the AI navigate to different websites, try out different options, and work out which I might prefer.

When it found what it believed was the best option, it added the television to the cart and stopped, waiting for me to approve the purchase before doing anything involving payment.

Spark is happy to do the repetitive work, but it won’t spend your money without asking first. It feels like exactly the right balance between useful automation and common sense.

Planning a family day out

(Image credit: Future)

My second experiment was slightly more ambitious because it combined several different tasks into one. I asked Spark to plan a family day out for two adults and two toddlers.

Normally that would have meant switching constantly between Google Maps, museum websites, restaurant reviews and booking pages. Spark simply got on with it. It compared opening hours, checked travel times, built a schedule that actually flowed logically through the day, found a restaurant with online reservations and reserved it, then prepared the museum ticket purchase and before asking me to approve the bookings.

AI for tedious tasks

Spark takes the tedium out of a library card application. (Image credit: Future)

Google claims Spark is great at filling out paperwork, especially using information from your own Google accounts. As my kid is getting to the right age for it, I asked Spark to fill out his library card application.

After checking that it had the right information about my address and other details, Spark opened up my library's website and went to work. It filled in my contact information, mailing address and other saved details. When it reached the final submission page, it stopped and waited for my approval instead of clicking the button itself.

It’s not an incredibly long form, but it’s easy to see how Spark could save quite a lot of time on the more complex medical or insurance papers. It’s a lot faster to review and make sure the AI got it right than to write it all out yourself.

Using Spark highlighted how different it feels from regular Gemini. Spark shifts the workload because it can actually interact with the browser instead of simply describing what I should do next.

Gemini Spark is one of the more compelling AI features Google has introduced in quite some time. It won’t replace every online task, but it can quietly eliminate a surprising amount of clicking, tab juggling and repetitive typing.

• Intel shared rare x86 chip design access with a brand-new startup
• RosaicLabs can now build custom processors using licensed Atom architecture
• Intel shifted its low-power strategy from Atom towards newer E-Core designs

Intel has given RosaicLabs access to part of its Atom processor technology in a rare move involving the company's x86 intellectual property.

Reports from Reuters claim the agreement involves register-transfer level, or RTL, code that describes processor functions before they are converted into physical silicon during manufacturing.

Atom was designed for low-power computing, making the technology suitable for systems requiring efficient performance without high energy consumption or excessive heat generation.

Why Atom technology fits the reported agreement

Intel's Atom processors have historically powered entry-level systems, networking equipment, embedded devices, and other products where power efficiency matters more than maximum performance.

The processor family runs on the x86 architecture and was developed to provide Intel-based computing for smaller and lower-power devices.

RosaicLabs is expected to receive RTL code for Atom technology, which could allow it to create custom processor designs using Intel's existing architecture.

A veteran semiconductor executive said such access provides "comprehensive exposure" to Intel's intellectual property, giving customers the ability to develop their own silicon based on licensed designs.

Providing Rosaic access to Atom technology is unusual because Intel has traditionally kept key parts of its x86 intellectual property under tighter control rather than widely licensing processor designs.

However, Intel's Atom portfolio has become smaller as the company shifted its low-power processor strategy toward E-Cores, which succeeded Atom-based designs in newer products.

E-Cores use newer microarchitectures such as Gracemont, meaning Intel may view selected Atom technology as suitable for external licensing while keeping its latest processor designs within its own roadmap.

The exact Atom technology Rosaic will receive remains unclear, although the startup could potentially gain access to Tremont, one of Intel's final Atom microarchitectures.

Tremont was used in products such as Elkhart Lake and Jasper Lake, which supported embedded systems, low-power laptops, and Chromebooks.

Rosaic has some connections with Intel

Rosaic is a startup incorporated in Delaware in May 2026, but details about the company remain limited beyond its reported agreement with Intel over Atom processor technology.

An amended corporate filing dated July 24 shows the company can pursue a $10 million seed funding round while approving capital expenditures below $5 million without investor or board approval.

The startup's founding team reportedly includes former Rivos employees, linking Rosaic with a semiconductor company that Meta acquired for roughly $2 billion last year.

Rosaic's connection with Intel also extends to its leadership because chief executive Amarjit Gill previously helped assemble Rivos' founding team alongside Intel chief executive Lip-Bu Tan, who chaired that company.

Gill and Tan also shared an investment history, making early bets on Nuvia before Qualcomm acquired the startup, adding another link between Rosaic's leadership and Intel's current chief executive.

These professional relationships have drawn attention to Rosaic, although neither company has publicly explained whether they influenced Intel's decision to share Atom processor technology.

After the announcement, Intel shares rose 12%, although no evidence directly linked those market gains with the reported licensing arrangement.

This agreement suggests Intel may see continued value in Atom's low-power x86 design, but its broader intentions remain uncertain until Rosaic reveals its future processor plans.

Apple is also considering an all-glass look for the front display.