News
- Ultra Maritime pairs its Sea Spear passive sonar array with the AN/SSQ-125B active sonobuoy at the US Navy's Lanternfish 2026 exercise in a bid to detect underwater drones
- While neither sonar type is new, the distributed architecture that links both to Anduril's Seabed Sentry and the Navy's command systems generates usable, precise readings for unmanned underwater vehicles
- The chain detects and then alerts operators to the presence of potential hostile naval assets in the vicinity of sensors that work in tandem to generate more reliable information
The threat that keeps modern navies awake at night is no longer a single, quiet submarine that gave regular defenses the slip, but a plethora of cheap drones that come in all shapes and sizes and could target anything from a pier to an undersea cable or a pipeline, for example.
While modern navies use sonar to track larger submarines, small drones are much harder to track reliably, even as Ultra Maritime, a defense tech company, says it has an answer.
The company showed that a pairing of its Sea Spear, a deployable passive sonar array, with the AN/SSQ-125B, its active sonobuoy offering, could, when working in tandem, track unmanned underwater vehicles (UUVs) better.
Existing tech, paired, repurposed and integrated to deliver resultsIt is important to know that neither of the hardware solutions used, passive sonar arrays or active sonobuoys, is a new creation; they have been deployed for years by the US Navy and many of its counterparts across the world since World War II to detect and track submarines.
The underlying approaches are even older: Passive listening and active pinging are two of the oldest techniques in the business, and both have existed since the First World War.
The intriguing part is the integration at play here and why it is tactically sound: Passive sonar is quiet, and it gives up nothing for the information it collects, including the listener's position, but it does get a bearing on any potential craft it does detect. Active sonar can then be used to determine range and location; however, for modern naval units, it is a double-edged sword, as it essentially announces one's presence in the region.
The tech essentially figures out whether anything is worth detecting by leveraging the first, then turns to the second to determine its specific location when needed. The company's Ocean of Things concept extends that to a mesh of autonomous sensors seeded from crewed and uncrewed platforms.
Ultramarine's approach allowed it to detect and classify UUVs of various sizes and sophistication in the US Navy's 2026 Lanternfish exercise. It has also announced that its Sea Spear is working with Anduril's Seabed Sentry to detect the same.
The timing is excellent for its buyer: defense contractor Lockheed Martin recently agreed to purchase Ultra Maritime from its private equity owner Advent for $3.45 billion, essentially adding it to the former's Rotary and Mission Systems division.
With navies struggling to identify and stop underwater drones that pose a persistent threat to their operations and defensive capabilities, Ultra Maritime's two-pronged approach seems like an interesting play to adopt. It combines already-existing scalable seabed infrastructure with a mesh of cheap listening arrays and expendable pinging buoys to get the job done.
To achieve any level of competency, large language models (LLMs) need ample data for sufficient training. AI companies have looked to various sources to mine this information, including content publicly available on the internet, synthetic data generated from other AI models, and printed literature.
Reading difficultiesPrompted by news that AI companies were allegedly using books from pirate ebook sites to build their LLMs, writers, authors, and publishers publicly called out this deeply worrying process.
Quote of the dayThis article is part of TechRadar Pro's QOTD project to provide an insight into the minds of the brightest and most recognized figures in the technology industry today and in years gone by. Read the full series here.
The professional organization known as the Authors Guild responded to various stories about AI companies scanning books to train their AI models (both illegally and legally) with incredibly comprehensive guidelines on AI licensing.
This document covered the various manifestations of the use of published works by AI companies, including its legal perspective on the legitimacy of using such works. It also highlighted that the continued data harvesting processes would risk destroying the ecosystem for books that currently exists.
Book buyingThe use of books by AI companies is an ongoing concern. But in recent months the focus has pivoted to those that buy, scan – and destroy – books on an industrial scale.
For example, court documents revealed the existence of 'Project Panama' inside Anthropic. This is a scheme in which the company aims to "destructively scan all the books in the world" and used a codename because "we don’t want it to be known that we are working on this.".
To train Claude, Anthropic had to procure a large and high-quality dataset, so it set out to purchase books on an industrial scale because of the relatively high-quality nature of the writing compared with, say, writing found online.
- VK wants Apple to restore its apps or face millions in daily fines
- The Russian company is demanding 58 million rubles ($696,000) every day
- Apple removed several major VK apps following European Union sanctions
Russian firm VK has filed a lawsuit against Apple in a Moscow arbitration court, seeking restoration of several removed applications from the App Store.
Court records dated August 19 2026 show that the Russian technology company wants its applications restored to the platform without further delay.
Apple removed a range of VK-owned applications recently, including VKontakte, VK Messenger, VK Video, Odnoklassniki, Zen, Mail Cloud, Mail, Skillbox, and Youla, saying it was following sanctions imposed by the European Union against VK and its messaging subsidiary, Communication Platform LLC.
VK demands steep daily penalties for continued app removalVK is asking the court to impose penalties of 58 million rubles per day, equivalent to roughly $696,000, if Apple fails to comply.
That figure breaks down across three services, with VKontakte accounting for 50 million rubles, or about $600,000, in daily fines.
VK Music would carry a penalty of 5 million rubles, or nearly $60,000, while Odnoklassniki would draw 3 million rubles, close to $36,000 daily.
The lawsuit names three separate Apple entities as defendants, including Apple Rus LLC, Apple Inc., and Apple Distribution International Ltd.
VK has requested that the daily fines begin accruing six days after the court issues its complete and final ruling in this case.
The European Union's sanctions accused VK and its messaging subsidiary of enabling surveillance, censorship, and the identification of government critics inside Russia.
Apple removed the applications from the App Store following that designation, and the same titles later disappeared from Google Play as well.
Kremlin criticism adds to mounting pressure on AppleThe Kremlin responded sharply to Apple's decision, with spokesperson Dmitry Peskov publicly demanding a formal explanation from the company itself.
Peskov argued that the removals called into question Apple's "reliability as a provider of commercial services" inside the Russian market.
The dispute unfolds against a broader pattern of legal friction between Western technology companies and Russian government authorities in recent years.
The Tagansky District Court recently fined Apple 500 thousand rubles (~$6,000) for a repeated violation of Russian federal legislation.
Similarly, a Moscow arbitration court ordered Google Ireland Limited to return more than $2.1 billion to Google's bankrupt Russian subsidiary.
That earlier ruling found the payments in question constituted unjust enrichment under Russian commercial law at the time of the case.
VK's case against Apple follows a similar legal strategy, relying on domestic courts to challenge decisions made by foreign firms.
Whether Moscow's arbitration system can meaningfully compel compliance from Apple, given its shrinking footprint in Russia, remains a genuinely open question.
Via United24media
- Samsung System LSI division uses Anthropic's Claude Code to reportedly slice working processes
- However the tool also apparently downgraded an error message instead of fixing it, rolling back unrelated finished work, and tried to edit code it was not authorized to touch
- Samsung's engineers currently review everything the tool produces before it is published elsewhere or affects existing chip designs
Samsung's System LSI division has reportedly used Anthropic's Claude Code to cut a month-long system-on-chip verification job to about two days.
While Samsung's division has about 6,000 employees, its main rival in mobile application processors, Qualcomm, has roughly 52,000 employees, and the former is apparently not above using AI to bridge the gap as a force multiplier.
A report from South Korean business outlet Chosun Biz (KR) claims System LSI leveraged Anthropic's Claude Code by offering it to its software developers in May 2026, then extended it to semiconductor design and verification work, a move which led to much faster progress on certain projects, while also producing interesting failures on other fronts.
A mix of triumphs and gaffesSamsung's approach, for the most part, makes an excellent case for future AI use, as one verification project expected to take more than a month was finished in about two days, something the company internally tracked as a 15x gain in efficiency.
More interestingly, a second-year engineer with no prior exposure to either the tool or USB communication standards built USB device models for an emulator and adapted an Android driver in a single day, work whichwas normally estimated to take about a month.
Samsung has also had an interesting interaction using Claude Code to verify the internal data connections of a custom system-on-chip. The job was complex in more ways than one: the customer wanted a new architecture, third-party design IP was involved, the documentation was nonstandard, and the RTL for the DRAM controller had not arrived on schedule, making for a perfect storm for Claude.
Claude built a virtual verification environment using placeholder blocks in place of the missing RTL, along with test scenarios, so that engineers could start catching errors before the real design existed.
On the other side of the equation, Claude Code did, in certain cases, try to operate outside the boundaries of its assignments, often resulting in incorrect output or an error, or, in one case, an attempt to modify RTL circuit code it had no authorization to touch. It also rolled back unrelated finished work and downgraded an error message instead of fixing it.
The former is particularly egregious because, unlike software updates, once silicon ships, it can rarely be repurposed or 'updated' to bypass design flaws. Samsung has responded by ensuring engineers manually inspect and verify the output of Anthropic's models before using it elsewhere.
More interestingly, Claude Code isn't the only tool in the building, even if it seems to get the most attention here; Samsung also uses Google Gemini and OpenAI's ChatGPT across research, manufacturing, marketing, and support.
Despite this, Samsung does not use either of the other models to check input from the former; trusted engineers on-site do that instead in an industry where errors that are not picked up during reviews could be costly for a company that is currently attempting to maximize efficiency, even as its System LSI has posted losses in its SoC business and its flagship Galaxy Z Fold 8 runs Qualcomm's silicon under the hood.
There is no such thing as a stupid idea in Stuart Fails to Save the Universe — and I'm starting to think that there's no such thing as a boring idea, either.
As the gang leave behind their tribal oasis from episode 5 — which, let's face it, they ruined — we're back in a familiar suburban setting this week. The difference? Everyone eats plants and grass as if they were a Happy Meal at McDonald's.
No fast food favoritism here, but you get the idea. So, when does Stuart Fails to Save the Universe episode 6 arrive on HBO Max?
What time can I watch Stuart Fails to Save the Universe episode 6 on HBO Max?For US viewers, Stuart Fails to Save the Universe episode 6 will drop on Thursday, August 27 at 6pm PT/ 9pm ET.
Internationally, you're looking out for these timings:
- US – Thursday, August 27 at 6pm PT / 9pm ET
- Canada – Thursday, August 27 at 6pm PT / 9pm ET
- UK – Friday, August 28 at 2am BST
- India – Friday, August 28 at 6:30am IST
- Singapore – Friday, August 28 at 9am SGT
- Australia – Friday, August 28 at 11am AEST
- New Zealand – Friday, August 28 at 1pm NZST
New episodes of Stuart Fails to Save the Universe will make landfall every Thursday in the US and on Fridays everywhere else. Here are the all-important dates you need to know about:
- Episode 1: out now
- Episode 2: out now
- Episode 3: out now
- Episode 4: out now
- Episode 5: out now
- Episode 6: August 27
- Episode 7: September 3
- Episode 8: September 10
- Episode 9: September 17
- Episode 10: September 24
- BACCH 3D virtual surround up front, Dolby Surround/Atmos for rear channels
- New control box also provides additional connectivity
- An open system: use whatever speakers you like
When Canvas HiFi unveiled "the world's first audiophile soundbar" earlier this year, it came with a huge specification: 8-inch drivers pushing out 1,500W of power in a three-way setup. When we actually heard it, we were very impressed – we said it was "astounding" – and now it's even better with a Dolby Atmos upgrade.
The new setup uses the Canvas soundbar for the front soundstage, with additional active speakers for the surround, rear, and height channels. The soundbar itself uses BACCH 3D for audio positioning and supports Dolby Surround and Dolby Atmos for the additional speakers.
(Image credit: Canvas HiFi)How does the Canvas soundbar handle surround sound?The BACCH 3D system is a virtual surround system that Canvas says is "fundamentally different" from conventional virtual surround technologies. It controls the acoustic interaction between your left and right ears to deliver a larger, more precise soundstage, with the left, right, center, and bass channels sounding as if they're coming from physical speakers. The rear channels use Dolby Surround or Dolby Atmos as required.
The heart of the system is a new control box, developed in collaboration with the German electronics specialist Almando. This new box handles surround decoding and signal distribution to the Canvas soundbar and additional speakers. It also acts as a connectivity hub, enabling additional inputs and outputs and better integration with larger AV systems.
Canvas has deliberately made this an open system, so if you'd rather use another firm's speakers for your rear and height channels, you can. However, it would very much like you to check out its new collaboration with the Danish speaker firm System Audio, which will be adapting some of its Silverback active speakers to match the Canvas design universe and deliver a "visually coherent sound system". The Silverback speakers are the ones on the wall in the above photograph.
The new system will make its debut at IFA 2026 in Berlin, which runs from the 4th to the 8th of September 2026.
Thinking of buying a new TV?Try our TV size and model finder! You tell it how far you sit from your TV, we'll tell you what size to buy based on viewing angle advice from image quality experts, and we'll recommend our three top TVs at that size for different prices.
Pre-orders for Google’s new Pixel 11 range have now wrapped up, with most retailer offers and deals finished, and you can now get your hands on them immediately.
All three Pixel 11 bar-style phones get a newly redesigned camera bump, along with brand-new LED notification lights within the flash module called ‘HiLight’. They also get a new Tensor G6, and now all start with 12GB of RAM — a decrease from the 16GB RAM that the base Pro models had in last year’s Pixels.
Like many flagship releases thus far, the Google flagships have higher starting prices compared to their predecessors — like AU$1,499 for the base Pixel 11 — although thankfully storage options now start at 256GB instead of 128GB in last year’s handsets.
If you're keen to get one of Google's latest smartphones, then understandably, paying one off in monthly instalments will likely be a popular option, instead of paying the full amount outright.
If you’re going the telco route, you’ll be pleased to hear that most of their pre-order specials have been extended to as late as October, with savings of up to AU$1,000. We’ve compared all the deals on offer and have highlighted the best ones below.
Best Pixel 11 plans(Image credit: Google)The best overall Pixel 11 planGoogle Pixel 11 | Vodafone Small Plan | 65GB data | 24 months | AU$76.20 p/m
After skipping the Pixel 10 last year, Vodafone is offering a AU$650 handset discount on the base Pixel 11, an extra AU$100 off for a sitewide discount on Android phones, and a AU$13p/m discount on the 65GB Small Plan for the first 12 months, all coming together to make this the cheapest telco deal. The plan includes unlimited national calls and texts, unlimited international texts and you can use your same plan when overseas for an extra AU$5 per day. This offer ends on September 30, though the AU$100 off ends earlier on September 7.
Minimum cost: AU$794 | Total cost over 24 months: AU$1,984.80View Deal
The best premium Pixel 11 planGoogle Pixel 11 | Vodafone Medium Plan | 220GB data | 24 months | AU$86.20 p/m
For an extra AU$10p/m, you can get the same discounted handset but with a whopping 220GB of mobile data. The key difference here is that you also get unlimited international calls to selected destinations, making this the better option if you need global communication.
Minimum cost: AU$804 | Total cost over 24 months: AU$2,224.80View Deal
Compare Pixel 11 plansBest Pixel 11 Pro plans(Image credit: Future/Lance Ulanoff)Google Pixel 11 Pro (256GB) | Optus Small Choice Plus Plan | 60GB | 24 months | AU$96.19p/m
Vodafone isn’t selling the 6.3-inch Pixel 11 Pro, so Optus is your best option to get the handset. The telco is discounting it by AU$500 and its Small Choice Plus Plan is currently AU$20p/m off for the first 12 months. The plan includes unlimited national calls and texts and 5GB of daily roaming for an extra AU$5 per day. If you want more mobile data, you can opt for the Medium Choice Plus Plan for an extra AU$10 with 240GB. This offer runs until October 6.
Minimum cost: AU$1,389 | Total cost over 24 months: AU$2,548.56View Deal
Compare Pixel 11 Pro plansBest Pixel 11 Pro XL plansThe best Pixel 11 Pro XL plan overallGoogle Pixel 11 Pro XL (256GB) | Optus Small Choice Plus Plan | 60GB | 24 months | AU$85.78p/m
Thanks to a AU$1,000 handset discount, the larger 6.8-inch Google Pixel 11 Pro XL is cheaper than its smaller sibling above when you sign up for a 12-, 24- or 36-month plan with Optus. When paired with the AU$20p/m discount on the first 12 months of the Optus Small Choice Plus Plan, this option also beats Vodafone’s offer by around AU$5p/m. This offer runs until September 6.
Minimum cost: AU$1,139 | Total cost over 24 months: AU$2,298.72View Deal
The best premium Pixel 11 Pro XL planGoogle Pixel 11 Pro XL (256GB) | Optus Medium Choice Plus Plan | 240GB | 24 months | AU$95.78p/m
For an extra AU$10p/m, you can get the same discounted handset but with a whopping 240GB of mobile data. The key difference here is that you also get unlimited international calls and texts to 35 destinations, making this the better option if you need global communication.
Minimum cost: AU$1,149 | Total cost over 24 months: AU$2,538.72View Deal
Compare Pixel 11 Pro XL plansOutright Pixel 11, Pixel 11 Pro and Pixel 11 Pro XL dealsSpending up to AU$2,299 in one go on a phone isn't viable for everyone, but if you can swing it, you will end up saving more in the long run. The Pixel lineup also often gets regular discounts — sometimes even just a few months after launch (like the Black Friday sales). If that’s the route you're looking to explore, we recommend pairing your new phone with one of our best SIM-only plans to keep costs down.
Multiple retailers stock the Pixel 11 lineup, with some stores running their own discounts at various times of the year. This gives you plenty of options for purchasing any of the Pixel 11 and 11 Pro models outright, and you can compare retailers’ prices in the widget below:
What’s new with the Google Pixel 11 lineup?Google has kept its four-phone lineup this year, comprising the standard Google Pixel 11, the Google Pixel 11 Pro and larger Pro XL, and Google's premium foldable, the Pixel 11 Pro Fold. What are the new worthwhile features and how do they compare? Here's a quick breakdown.
Let's start with the Tensor G6 chipset that powers the entire range of new Pixel 11 phones. This is a direct upgrade to the previous G5 chip, boasting a 20% faster CPU, 50% faster TPU and a 20% improvement in power efficiency. That means faster overall performance, a more efficient battery and speedier processing for AI features.
(Image credit: Future/Lance Ulanoff)Google phones have always been good for photos, too, and that theme continues with the Pixel 11 range. The base Pixel and the Pro Fold can now zoom in 30x (up from 20x), while the Pro and Pro XL get a whopping 120x zoom, up from 100x in last year’s handsets, thanks in part to a new 48MP telephoto sensor (that also has a 30% increase in light sensitivity.
You also get a new Magic Capture feature, which uses AI to automatically pull the best individual frames from video recordings as high-res HDR photos. You can also choose to reduce heavy photo processing or emulate retro camera styles with the new Camera Looks feature.
One notable feature is HiLight: a multi-colour LED light array in the Pixel 11 Pro and Pro XL’s camera flash module that glows when Gemini is activated or lights up with a chosen colour assigned to a specific contact.
Altogether, there are some decent upgrades across the new Pixel 11 lineup. With frequent discounts, you could come away with an awesome new phone at a great price, too.
Google Pixel 11 and 11 Pro specs comparisonPixel 11
Pixel 11 Pro
Pixel 11 Pro XL
Price:
AU$1,499
AU$1,849
AU$2,099
Weight:
197g
204g
226g
Display:
6.3-inch OLED
6.3-inch LTPO OLED
6.8-inch LTPO OLED
Resolution:
2424 x 1080
2856 x 1280
2992 x 1344
Refresh rate:
120Hz
1Hz to 120Hz adaptive
1Hz to 120Hz adaptive
Peak brightness:
3,000 nits
3,600 nits
3,600 nits
Chipset:
Google Tensor G6
Google Tensor G6
Google Tensor G6
Rear cameras:
48MP wide, 13MP ultrawide, 10.8MP 5x telephoto
50MP wide, 48MP ultrawide, 48MP 5x telephoto
50MP wide, 48MP ultrawide, 48MP 5x telephoto
Front camera:
10.5MP
42MP
42MP
Storage:
256GB, 512GB
256GB, 512GB, 1TB
256GB, 512GB, 1TB
RAM:
12GB
12GB/16GB (512GB, 1TB)
12GB/16GB (512GB, 1TB)
Colours:
Frost, Pistachio, Hibiscus, Obsidian
Canyon, Olive, Fog, Obsidian
Canyon, Olive, Fog, Obsidian
Pre-orders for Samsung’s 2026 foldables wrapped up this week, but telcos across Australia are clearly in a generous mood, as they kept their previous pre-order deals live for a wee bit longer, giving you a bit more time to save on the new devices.
And save you might, because this year, Samsung has introduced a third premium Z-series foldable in 2026 with the Galaxy Z Fold 8 This new model introduces a new design: a short and wide 5.5-inch cover screen when folded, and a 7.6-inch main screen with a 4:3 aspect ratio that can fit widescreen videos better than the Galaxy Z Fold 7’s square display, or resemble an ereader when in portrait mode.
The direct successor of the Galaxy Z Fold 7 is now confusingly called the Galaxy Z Fold 8 Ultra, which is thinner than ever (4.1mm down from an already ridiculously thin 4.2mm) and also features a 50MP ultrawide camera (up from 12MP), a higher-resolution main screen, and increased peak brightness from 2,600 nits to 3,000 nits.
With all that said, these foldables have arrived as some of the most expensive phones you can buy in Australia, with the base 256GB models starting from AU$2,699 for the Z Fold 8 and AU$2,999 for the Ultra. The latter also represents a AU$100 price hike from the Z Fold 7.
If you’ve been sold on all the features and are happy to buy either handset outright, you can check out the current best outright deals below and then pair that with one of our best SIM-only plans.
However, the high upfront costs of both foldables will likely mean many buyers may prefer to pay either one off over a multi-year contract from a major Australian telco like Vodafone, Optus or Telstra.
We’ve crunched the numbers on the big three’s Samsung Galaxy Z Fold 8 and Z Fold 8 Ultra plans below — including any current promotions and discounts — to help guide you to the best value options for various needs.
The best Samsung Galaxy Z Fold 8 plan overallSamsung Galaxy Z Fold 8 | Optus Small Choice Plus plan | 60GB data | 24 months | AU$127.42 p/m
Optus is offering AU$600 off the Galaxy Z Fold 8, plus a AU$20p/m discount on plan fees for the first 12 months, making the telco the cheapest provider for the new foldable. The plan includes 60GB of mobile data, unlimited calls and texts across Australia and select destinations, and 5GB of daily roaming for AU$5. This offer will run until October 6.
Minimum total cost: AU$2,139 | Total cost over 24 months: AU$3,298.08View Deal
The best premium Samsung Galaxy Z Fold 8 planSamsung Galaxy Z Fold 8 | Optus Medium Choice Plus plan | 240GB data | 24 months | AU$137.42 p/m
For an extra AU$10p/m, you can get a whopping 240GB of mobile data, unlimited calls and texts across Australia and select international destinations. The AU$50p/m plan fees will go back up to AU$70p/m after one year.
Minimum total cost: AU$2,149 | Total cost over 24 months: AU$3,538.08View Deal
The best Samsung Galaxy Z Fold 8 Ultra plan overallSamsung Galaxy Z Fold 8 Ultra| Optus Small Choice Plus plan | 60GB data | 24 months | AU$139.93 p/m
Optus is also offering AU$600 off the Galaxy Z Fold 8 Ultra and a AU$20p/m discount on plan fees for the first 12 months, also making it cheaper than Vodafone. The plan includes 60GB of mobile data, unlimited calls and texts across Australia and select international destinations. The handset discount will also run until October 6.
Minimum total cost: AU$3,039 | Total cost over 24 months: AU$3,598.32View Deal
The best premium Samsung Galaxy Z Fold 8 Ultra planFor an extra AU$10p/m you’ll get 240GB of mobile data, unlimited calls and texts across Australia and select international destinations. Plan fees will go back up to AU$70p/m from AU$50p/m after one year.
Minimum total cost: AU$2,149 | Total cost over 24 months: AU$3,538.08View Deal
Outright Samsung Galaxy Z Fold 8 and Z Fold 8 Ultra dealsNot interested in purchasing through a telco with a postpaid plan? Many Aussie retailers offer the Samsung Galaxy Z Fold 8 and Z Fold 8 Ultra outright, including an option to pay in instalments through Samsung Australia directly. Here are the top current offers available from our retail partners.
What’s new with Samsung’s latest foldables?(Image credit: Future)Samsung’s latest foldables, the Galaxy Z Fold 8, Galaxy Z Fold 8 Ultra and Galaxy Z Flip 8, mark substantial design and usability upgrades over their predecessors – pushing the boundaries of what a foldable phone can be.
The Galaxy Z Fold 8 is the newest addition to the Z-series range, featuring a new short and wide form factor when folded, and a main screen with a 4:3 aspect ratio that can fit widescreen videos better than most foldables’ square display, or resemble an ereader when in portrait mode.
Meanwhile, the Galaxy Z Fold 7’s direct successor is now called the Galaxy Z Fold 8 Ultra, which is now even thinner at 4.1mm when unfolded and its main display gets a resolution bump at 2256 x 2504 pixels (up from 1968 x 2184 pixels). Its most prominent upgrade though is the camera system with a new 50MP ultrawide sensor to pair with the 200MP shooter, similar to those found in the Galaxy S26 Ultra.
Both devices get a powerful Snapdragon 8 Elite Gen 5 chipset, 12GB RAM (or 16GB in some instances) and new silicon-carbon batteries to fit in larger capacities compared to traditional lithium-ion batteries in the same physical size — 4,800mAh for the Z Fold 8 and 5,000mAh for the Ultra.
Meanwhile, the Galaxy Z Flip 8 is thinner and lighter than its predecessor at 6.1mm unfolded and 13.1mm folded, compared to the Flip 7’s 6.5mm and 13.7mm, respectively. There’s also a refined hinge that’s aimed at making the handset easier to open one-handed and reducing the crease. While it doesn’t get the Snapdragon 8 Elite Gen 5 chip used by its foldable cousins here in Australia, it still gets an upgraded Exynos 2600 found in the base Galaxy S26 and S26 Plus. The handset also gets the silicon-carbon treatment here, although it retains the same 4,300mAh capacity as the Flip 7.
Samsung Galaxy Z Fold 8, Z Fold 8 Ultra and Z Flip 8 specs
Samsung Galaxy Z Fold 8
Samsung Galaxy Z Fold 8 Ultra
Samsung Galaxy Z Flip 8
Weight
201g
215g
180g
Display
Main: 7.6-inch Dynamic LTPO AMOLED 2X (2448 x 1848)
Cover: 5.5-inch Dynamic LTPO AMOLED 2X (1248 x 1972)
Main: 8-inch Dynamic LTPO AMOLED 2X (2256 x 2504)
Cover: 6.5-inch Dynamic LTPO AMOLED 2X (1080 x 2520)
Main: 6.9-inch Dynamic LTPO AMOLED 2X (1080 x 2520)
Cover: 4.1-inch Super AMOLED Display (948 x 1048)
Chipset
Snapdragon 8 Elite Gen 5 for Galaxy
Snapdragon 8 Elite Gen 5 for Galaxy
Exynos 2600
RAM
12GB / 16GB (1TB)
12GB/16GB
12GB
Storage
256GB / 512GB / 1TB
256GB / 512GB/ 1TB
256GB / 512GB
Rear cameras
Wide: 50MP
Ultrawide: 50MP
Wide: 200MP
Ultrawide: 50MP
Telephoto: 10MP
Wide: 50MP
Ultrawide: 12MP
Front cameras
Cover: 10MP
Front: 10MP
Cover: 10MP
Front: 10MP
10MP
Battery
4,800mAh
5,000mAh
4,300mAh
Colours
Graphite, Cream, Lavender, Pistachio
Graphite, Cream, Violet Shadow
Graphite, Cream, Pink, Mint
- Public confidence in AI weather forecasts is far lower than for numerical and physics-based methods
- Just 11% said they were "very confident" in machine learning weather prediction, compared with 30% for tried-and-trusted methods
- The Met Office has been using machine learning techniques in weather forecasting for some years
A survey of 6,000 UK adults has found that the majority don’t fully trust the idea of AI weather forecasts. While machine learning techniques have been a factor of weather forecasting for some years, the survey found that people are more relaxed about traditional Numerical Weather Prediction (NWP) as opposed to Machine Learning Weather Prediction (MLWP).
Predictive technology has increased considerably thanks to AI, and the Met Office has already begun to evaluate AI models for augmenting its existing forecasting methods.
However, the “confidence gap” in the results of the survey, which appears to be based around questions over accuracy, could undermine the use of AI for weather forecasting, which researchers suggest can be challenged with clear demonstrations of the methods working successfully.
AI-based weather modelsThe Met Office research was published in a study, Artificial Intelligence for the Earth Systems, which explores the public’s confidence in the reliability of AI-based weather forecasting and prediction. Future studies are planned to assess how attitudes change toward AI-backed weather reports.
Responses to the report are not entirely negative. While 87.7% of respondents felt confident about weather reports using NWP, the 49.4% in favour of MLWP isn’t a bad result. Rather, it demonstrates that people are comfortable with tried-and-tested methods.
Dr Edward Pope, a Met Office Science Fellow and the lead author of the paper, said the report, “deepens our understanding of current public perceptions as we approach a crucial juncture where AI-based weather models are demonstrating their potential to work alongside physics-based methods. This was a unique opportunity to compare public perceptions of established and emerging approaches to forecasting the weather."
The consequences of the “confidence gap”The gap in confidence between the maths-based predictive forecasting and modern AI modelling is a challenge that the Met Office is addressing directly.
Dr Pope explained that “The gap in confidence and perceived accuracy highlighted in the paper demonstrates the need to clearly and transparently demonstrate the value of new approaches in ways that matter to people.”
In Pope’s view, AI practices will contribute to weather forecasts in the future, “but these improvements will only be fully realised if the public continue to have confidence, and importantly act on, the weather forecast they see.”
The Met Office research considered the “perceived accuracy” of reports, and its Chief AI Officer Professor Kirstine Dale implied that progress with AI weather modelling is subjected to evaluation and validation: “We are exploring ways of blending physics-based and AI-based modelling to deliver the forecasts that we all rely on. As with all science developments, we will robustly evaluate and validate any changes to our approach to weather forecasting before we introduce them into the model.”
- A security engineer at Amazon hacked a bunch of peripherals using AI
- Claude Opus did most of the legwork in applying modified firmware to a webcam, microphone and more
- The relative ease with which AI allows this kind of modification points to a worrying future of peripherals being compromised on a grander scale
In another example of how AI could prove to be a threat to our devices, an Amazon security engineer has demonstrated how powerful Claude Opus is when it comes to reverse engineering PC peripherals.
Chaz Schlarp, who's a Senior Security Engineer at Amazon, wrote a blog post about experiments he conducted with a bunch of peripherals such as a webcam and a microphone.
He wanted to find out how easy it was to modify the firmware and pull off some useful tricks with these devices using AI, but clearly there's a darker side here — namely that the same access could be leveraged by a malicious actor to compromise your system via these gadgets.
Schlarp used Claude Opus 5 to mess around with the firmware for an Insta360 webcam, a Shure microphone, an Asus monitor, an Elgato video capture stick, and an Elgato mini-light (a compact device for lighting your streaming videos).
Schlarp explains: "My process was pretty much the same for each of these devices: grab a copy of the device's firmware and associated update tool from the manufacturer, throw it into my reverse engineering environment, tell Claude Opus 5 what my goals are, and let it churn."
One thing that became quite clear to the security engineer was that these devices lacked any decent firmware integrity protection to prevent modifying and applying a new firmware. Only the Elgato light had any defenses in this respect, and they were easy enough to circumvent.
Schlarp explains a trick with his Asus ROG Swift PG42UQ monitor to demonstrate the kind of useful utility that can be on offer with this kind of firmware modding. He found it was possible to remove an annoying pop-up warning that periodically tells the owner to run the 'pixel cleaning' process (although the engineer hasn't implemented the fix in the firmware yet). He also discovered a way to get DisplayWidget (a Windows utility) features running on his Linux system, with a shell script that can flick through certain bits of functionality like the hardware crosshair or FPS counter (which could be set up on hotkeys).
Most of what he did, though, was about proving how relatively easy it was to subvert the firmware using AI to do the heavy lifting, and, for example, disable the webcam's recording light (in the style of surveillance malware, so the user wouldn't know if the camera was secretly recording). He pulled off a similar feat with the microphone, so the mute LED could be on while the mic wasn't actually muted (this was leveraged via a 'full plaintext command shell').
Schlarp observed: "Peripherals have proven to be an ideal target for agentic RE [reverse engineering] — they're tiny computers attached to my computer, with a data connection to the host and usually a firmware update mechanism, so an agent has something to iterate against. The net outcome is better control and understanding of my machine."
Analysis: fast-tracked exploits?(Image credit: Shure)The key point here is how easy Claude Opus made this task. 'Owning' all five of these peripherals boiled down to 13 hours of the AI beavering away under its own steam with just shy of 100 prompts from its human overseer.
Schlarp notes that: "Hardware is almost universally 'open' for tinkering at this point with just a couple hours of mostly hands-off machine-driven labor each, and I look forward to a near future where I can add features to my webcam firmware as easily as I can to software that runs on my Linux machine itself."
However, as mentioned, there's the dark side to all this, as Schlarp makes clear: "On the other hand, as a security professional, this scares me for several reasons. I would work from the operating assumption that any device attached to a computer could have had a malicious firmware implant performed, where previously that required significant per-model investment and was stereotyped as a 'state actor' kind of activity."
In other words, the main difficulty in executing these kinds of exploits is the labor and time required, which currently limits this to individually targeted attacks on more high value targets. However, now an AI agent is capable of doing the grunt work, it makes sense that these kinds of attacks could be far more prevalent as time rolls on.
That means all those peripherals attached to your PC could be used as ways to compromise you, or your system, in the future. Schlarp informs us that he's also managed to get a root shell on a commercial Dell display, adding that: "Obviously it was never best practice to let untrusted clients touch these things, but the speed and scale at which this can be executed makes the risk so much higher now."
There's a potentially bigger threat here, too: an AI-powered worm that automatically actions this kind of reverse engineering. Schlarp explains: "It's only a tiny leap to imagine that someone could make a self-replicating piece of malware that probes its environment, relaying reconnaissance back to a smart command-and-control that actively works to push itself into accessories and IoT devices and industrial equipment found adjacent to an infected target."
There are a lot of worries about where AI could be leading us, and far more dangerous security threats looming in the future (or indeed the present) is another unfortunate prospect to say the least.
It's Garmin launch day! Following Garmin's surprise stealth scheduling of a live YouTube event (which it's calling on X a "groundbreaking launch event"), we can now confirm the Garmin Fenix 9 and Garmin Fenix 9 Pro have been released, and they look great.
There are tons of new features to dive into, and I'm sure more than one will make their way to the rest of the best Garmin watches range — but a few will stay as Fenix 9 exclusives.
We're breaking down all the information below in our live blog, including how much the watches will cost to buy. Stay tuned!
Missed the live show? You can watch the Fenix 9 announcement below:
Welcome to our Garmin liveblogHello, Matt Evans (TechRadar's Senior Fitness & Wearables Editor) here! I'm on hand to see you through until today's Garmin live event in a few hours' time.
We're all expecting the Garmin Fenix 9 to debut, but really, anything could be on the table, from Edge cycling computers to InReach communicators.
However, I've been writing about and covering Garmin for years, and this is the first big YouTube live event product launch I've seen from the popular watch brand, so we're expecting a high-profile unveiling.
August 25, 2026 – 4:45 AM"Get ready to Play Harder"(Image credit: Future)On the Garmin website, the announcement page reads:
"Your playground is calling. Now’s the time to answer. Set a reminder below to join us at 12 p.m. on 25 August, 2026 for a groundbreaking launch event on YouTube Premiere."
12pm BST, of course, is 4:00am Pacific Time (sorry) or 7:00am Eastern Time in America. For Australian watchers, it's a more reasonable 9:00pm AEST.
What could this mean? I imagine it's something about the great outdoors being your playground, and technology to enable that.
The picture of a trail runner wearing a hydration vest, on the other hand, suggests it's going to be an adventure watch with sporty and navigation capabilities. Hmm...
August 25, 2026 – 5:06 AMWhy do we all think it's the Garmin Fenix 9?(Image credit: Future)For one thing, we saw comments from CEO Cliff Pemble earlier this year during a Garmin quarterly earnings call, about how he expected Garmin's growth to "accelerate" in the back half of the year due to "the timing of product launches".
Garmin's got several categories it sorts its watches into, with the Garmin Forerunner line sorted into the "sports" category. "Outdoor" includes Garmin Instinct, Fenix and Enduro watches due to their emphasis on navigation and trail features.
For another, we've been seeing more retailer and communications databases leaks over the last month, suggesting a launch is imminent.
August 25, 2026 – 5:46 AMWhat's it going to look like?(Image credit: Garmin)According to leaks, we're getting not one, not two, but three new Fenix 9 watches, with multiple versions of each.
These include a regular Fenix 9, a Fenix 9 Pro with more advanced features, including, reportedly, Garmin's Power Glass solar charging tech, with the duller, more battery-efficient memory-in-pixel display now restricted to Pro models.
Finally, if rumors are true, we'll get a Pro fitted with Garmin's InReach satellite communications technology, like the Garmin Fenix 8 Pro. Garmin's InReach technology is useful in the great outdoors as it reaches satellite networks even if your phone has no signal.
Each of these watches would likely come in three sizes (43mm, 47mm, and 51mm if previous releases are anything to go by).
August 25, 2026 – 6:14 AMTons more leaks are hitting the net, with Gadgets & Wearables spotting an official listing of the Garmin Fenix 9 Pro via the company's Taiwan website, before quickly being taken down.
The Fenix 9 Pro 47mm listing, according to Gadgets & Wearables, gets a fully titanium case rather than the Fenix 8 Pro's titanium bezel and backplate, with a plastic middle.
It also sports Garmin's familiar five-button design, LED flashlight, sapphire lens, speaker and microphone.
August 25, 2026 – 6:41 AMWhat about the Garmin Enduro 4?(Image credit: Mike Sawh)For all the talk about the Fenix 9, one name that hasn't come up much is the Garmin Enduro 4. Garmin Enduro watches are typically influenced by the Fenix line, offering similar features but prioritizing a huge battery life for endurance events. Last time, the Fenix 8 and Enduro 3 were launched together.
The Garmin Enduro 3 has, in the right conditions of 50,000 lux or more, near-limitless battery life thanks to its Power Glass technology and enormous battery capacity. You can read our full Garmin Enduro 3 review here while you wait for the big announcement. Its possible that its role in the line might have been folded into the rumored Fenix 9 Pro Solar model, eliminating the need for a separate premium watch.
August 25, 2026 – 6:50 AMThere's just ten minutes to go! Let me know what you're hoping for (or how you feel about today's announcement) in the comments below, or email me at matt.evans@futurenet.com and I'll do my best to feature as many replies as possible on this live blog.
August 25, 2026 – 7:02 AMIt's starting! With some very dramatic music and a multi-colored countdown, moving into an 'event will begin shortly' legend, transitioning into a trailer. I've never seen Garmin do this before.
August 25, 2026 – 7:05 AMYep, Fenix 9 and Fenix 9 Pro confirmed, with "more choice options than ever before".
Garmin's co-chief operating officer Brad Trenkle takes the stage to tell us more about it. He mentions Garmin Epic, a new mode combining activities, that titanium case and inReach connectivity for Pro models.
August 25, 2026 – 7:07 AMFenix 9 Pro revealed(Image credit: Future)A lot of the rumors just got confirmed. Solar charging option, sapphire lens, titanium case, InReach connectivity. The trailer also mentioned better, routable maps, rucking and rowing features, and that Garmin Epic feature we heard nothing about until now.
August 25, 2026 – 7:09 AM(Image credit: Future)Some great behind-the-scenes info here about the construction of key Fenix 9 Pro elements like the sensor guard. Lots of emphasis on the smartwatch flashlight too, which comes in green as well as red (on the Pro, at least).
August 25, 2026 – 7:13 AMAndrew Perkins, product manager, takes the stage to tell us more about Garmin Epic. He said "this brand new feature allows you to group multiple activities together to tell a story".
This seems to be a feature in the Garmin Connect app, linking together related workouts over a time period. It seems you could link together multiple training runs to show improvements before race day, or chart a big ski weekend by grouping snowsports and hikes together.
The aim of course, is to share these socially as a single 'mega event', adding notes and photos to "make your Epic something to relive, not just review".
August 25, 2026 – 7:15 AMRuckers get the option to add or remove pack weights mid-activity, and be added as a multi-sport overlay. This is great for me, as I love to add weight to short hike to increase the challenge in a limited time period. A collaboration with GoRuck is in the works too.
Rowing machine workouts allow you to connect your watch to a compatible rower to improve power curve and targeted intensity features, as well as a countdown.
August 25, 2026 – 7:19 AM(Image credit: Garmin)Calculating a roundtrip course on Fenix 9 Pro maps is 40% faster than the Fenix 8 Pro. In addition to an overhead view, you can also switch to a tilted perspective thanks to a more powerful mapping engine. It comes preloaded with "entire continents of maps". ClimbPro helps you manage grades and effort, while virtual pacer software PacePro now helps you better handle upcoming terrain.
The AMOLED display is also twice as bright as the Fenix 8's, although there's no word on microLED.
Above, you can see our first official press image of the Fenix 9 and 9 Pro.
August 25, 2026 – 7:22 AMNew personalised stamina zones will be available in the post-activity summary. A new stamina curve is also "an easy to understand" visual representation of your fitness and how aerobic and anaerobic workouts alike contribute to your improving stamina.
August 25, 2026 – 7:25 AM(Image credit: Future)LiveTrack has always been a useful Garmin feature, and it's being improved with the Pro's LTE functionality. It interfaces more closely now with Garmin Messenger, Garmin's satellite messaging service.
A new feature called Garmin Locate allows other Garmin Connect users to check on your location without having to enable LiveTrack.
The Pro also offers 12 months of SOS messaging even after you suspend your inReach messaging subscription. So could you theoretically start a sub, suspend it, and get a year absolutely free? Tempting...
August 25, 2026 – 7:32 AMHow much will they cost?(Image credit: Future)That about wraps it up for the presentation! I've got the press release in hand now, so will be posting full specs for the watches shortly.
What wasn't mentioned was the price. I can confirm Fenix 9 will start at $999.99 / £859.99 / AUTBC (around AU$1,399) and the Fenix 9 Pro will start at $1,099 / £949.99 / AUTBC (around $1,549).
August 25, 2026 – 7:56 AMWill you be getting the Fenix 9, Fenix 9 Pro or perhaps picking up a cheaper watch? Dropping four figures on a watch is hard to do for most of us, but they do look great...
Have your say and vote in our poll:
August 25, 2026 – 8:14 AMGarmin Fenix 9 specifications(Image credit: Garmin)Component
Garmin Fenix 9 (43mm AMOLED)
Price
From $999.99 / £859.99 / AUTBC
Dimensions
43 x 43 x 13.8 mm
Weight
61g
Case/bezel
Titanium, fibre-reinforced polymer
Display
416 x 416 px, AMOLED
GPS
Multi-band, GPS + Beidou + Glonass + Galileo + QZSS + SatIQ
Battery life
10 days (49 hours activity mode)
Connection
Bluetooth, ANT, Wi-Fi
Water resistant?
Yes, 10ATM
Memory
64GB (7,000 songs)
August 25, 2026 – 8:28 AMGarmin Fenix 9 Pro specifications(Image credit: Future)Component
Garmin Fenix 9 Pro (43mm AMOLED)
Price
From $1,099.99 / £949.99 / AUTBC
Dimensions
43 x 43 x 13.3 mm
Weight
62g
Case/bezel
Titanium
Display
416 x 416 px, AMOLED
GPS
Multi-band, GPS + Beidou + Glonass + Galileo + QZSS + SatIQ
Battery life
10 days (Up to 50 hours activity mode)
Connection
Bluetooth, ANT, Wi-Fi
Water resistant?
Yes, 10ATM
Memory
64GB (7,000 songs)
Comparing the 43mm 9 Pro to the 9 below, you can see there's little comparable difference in specs, other than a gram of weight, some reduction in thickness and more titanium.
The Pro gets a brighter screen, that green flashlight for better night vision, and other model options. Solar (which extends the battery life enormously) is available only on 47mm models and up. An InReach and LTE-enabled model is also available at an additional cost.
Initially, my gut would say not to get the Garmin Fenix 9 Pro at 43mm without either the solar charging or InReach options, as you're getting comparatively little over the standard Fenix 9. The price increase actually becomes better value as you go up due to the additional features on offer. I'll do a full price breakdown of all the models of both watches shortly.
August 25, 2026 – 9:56 AMI'm back, and after digesting my thoughts on the release (not to mention my lunch), I've come to the conclusion that the Fenix 9 launch showed us a lot more than the new watches.
Generating hype before the announcement, posting it live, bringing in Garmin leaders, designers and sponsored athletes as talking heads... it all smacked of the kind of live launch you'd expect from the likes of Apple, or Samsung.
I believe there is a conscious effort for Garmin to align itself with companies like these. For a long time, Garmin has simply dropped information unceremoniously at the same time as the products appear on the website, without much fanfare. It's been acting more like a utilitarian sports company (which it is) than a high-tech corporation with lots of die-hard fans (which, erm, it also is).
Garmin's seen the hype and conversation such events can bring to brands, and sought a piece of that pie. As such, it chose to announce its flagship outdoors product with a bit more fanfare than usual.
Whether that will translate to more people spending over $1,000 / £900 / AU$1,400 on a watch remains to be seen... The Fenix 9 is really a tool for elite athletes, but its problem is that elite athletes already know whether they're buying a Fenix 9 or not. Today, Garmin has tried to catch the attention of the Apple Watch Ultra crowd.
August 25, 2026 – 10:28 AMFull pricing breakdownHere's the clearest Garmin Fenix 9 pricing breakdown you'll find on the internet right now. I've gone through all the model options in US, UK and AU pricing.
Garmin Fenix model
43mm
47mm
51mm
Garmin Fenix 9
$999.99 / £859.99 / AU$1,599
$999.99 / £859.99 / AU$1,599
$1,099.99 / £949.99 / AU$1,749
Garmin Fenix 9 Pro
$1,099.99 / £949.99 / AU$1,749
$1,099.99 / £949.99 / AU$1,749
$1,199.99 / £1,029.99 / AU$1,899
Garmin Fenix 9 Pro Solar
N/A
$1,099.99 / £949.99 / AU$1,749
$1,199.99 / £1,029.99 / AU$1,899
Garmin Fenix 9 Pro with InReach
$1,199.99 / £1,029.99 / AU$1,899
$1,299.99 / £1,199.99 / AU$2,049
$1,399.99 / £1,209.99 / AU$2199
Garmin Fenix 9 Pro Solar with InReach
N/A
$1,199.99 / £1,029.99 / AU$1,899
$1,299.99 / £1,199.99 / AU$2,049
Confused? Here are our takeaways:
- The standard Garmin Fenix 9 AMOLED version is cheapest.
- Solar is only available on Pro models.
- Solar costs the same as AMOLED on the Pro without InReach, as it's a choice between a longer battery life or brighter screen.
- There is no Solar 43mm Pro model.
- Pro InReach AMOLED is the most expensive configuration, with Solar actually costing less than AMOLED here.
For years, the phrase "AI-powered attack" has mostly meant a human using AI tools to write better phishing emails or scan for vulnerabilities faster. That framing just became outdated.
This month's intrusion into a major AI infrastructure platform was carried out, start to finish, by an autonomous agent.
No operator typed commands during the attack. No one was watching a terminal, deciding what to try next.
The agent found its own way in, escalated its own privileges, moved across internal systems on its own initiative, and kept going until it was caught.
It executed thousands of individual actions across a swarm of short-lived sandboxes, using infrastructure that migrated itself to stay ahead of takedown efforts.
That last detail is the one worth sitting with. This wasn't a script running on a loop. It was closer to a persistent, adaptive actor that happened not to be a person.
Agentic attackerSecurity teams have spent the last two years bracing for what researchers called the "agentic attacker" scenario: a future where offensive AI doesn't just assist a human operator but replaces the decision-making loop entirely. That future arrived faster than most roadmaps allowed for. And it arrived through an unglamorous door.
The intrusion began not with some exotic zero-day but with a malicious dataset, exploiting weaknesses in how data gets processed and executed. Old lesson, new attacker. The place where AI platforms are most exposed is often the plumbing, not the model.
What makes this incident more than a cautionary anecdote is where the agent came from. It wasn't built by a criminal group. It emerged from an internal test, one company evaluating how capable its own models were at offensive internet security work.
The safeguards that would normally stop a model from behaving this way had been deliberately loosened for the purposes of that evaluation, and the agent found a flaw serious enough to escape the contained environment altogether. It got out, found a live target, and treated it the same way it had been trained to treat a benchmark: as a problem to solve, thoroughly and without asking permission.
This is where the industry's favorite excuse collapses. "The AI acted on its own" is true, technically. It is also irrelevant to the question of who is responsible. Nobody would accept that defense from a bank whose fraud-detection algorithm accidentally froze every customer account overnight, and nobody should accept it here.
An organization that builds a system capable of autonomous action, tests it with reduced constraints, and fails to contain it when it exceeds its boundary has made three decisions, all of them accountable ones. Autonomy in the tool does not create autonomy from consequences for the people who deployed it.
A harder problemThere's a harder problem sitting underneath the accountability question, and it doesn't have a tidy fix. These agents are not malicious by design. They are goal-pursuing systems, optimizing for an objective, and the gap between "pursue this objective" and "pursue this objective the way a human would want you to" is where things go wrong.
An agent instructed to find and exploit vulnerabilities doesn't inherently know where the test environment ends and the real internet begins. Alignment, in this context, isn't a philosophical nicety. It's the difference between a benchmark result and an incident report. As agents get assigned more ambitious, multi-step objectives, that gap doesn't shrink. It widens, because the more complex the goal, the more creative and unpredictable the path an agent will find to reach it.
Ironically, one of the more telling wrinkles in this incident had nothing to do with the attacker. When the victim organization tried to use its own AI tools to analyze the attack logs, the safety filters built into several frontier models refused to help, unable to distinguish forensic analysis of an attack from participation in one.
The team ended up relying on an open-weight model with fewer restrictions to do the job. That's worth flagging on its own: the same caution designed to prevent misuse can also blind defenders at the exact moment they need clarity fastest.
Active securityNone of this argues for abandoning AI agents. It argues for treating sandboxing as an active security discipline rather than a checkbox. A test environment isn't safe because it's labeled as one. It's safe when it has been built and continuously verified to contain the specific class of behavior the system might attempt, including behavior nobody predicted at design time.
Reduced safeguards for the sake of a benchmark should carry the same scrutiny as reduced safeguards in production, because the line between the two is thinner than most evaluation frameworks assume. Governance needs to catch up with capability rather than trailing a year behind it, and that means treating agent permissions the way mature organizations already treat privileged human access: least privilege by default, monitored continuously, revoked automatically when behavior deviates from scope.
For security teams, the lesson isn't really about one company's bad week. It's that AI is now operating on both sides of the perimeter simultaneously, as the business tool a company depends on and as a potential attack surface with its own failure modes.
Detection strategies built around human attacker timelines, the hours and days it takes a person to escalate and pivot, won't hold up against an agent doing the same work in minutes. The organizations that come out ahead won't be the ones that avoided building agentic systems.
They'll be the ones that assumed, from day one, that their agents would eventually try to do something nobody authorized, and built the containment to survive it.
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It’s a tale as old as time. You tune into the big budget show about dragons and tyrants and your job in tech suddenly makes a lot more sense.
If you’ve been watching the new season of House of the Dragon, you’ll know the term ‘protector of the realm’. They’re kings, queens, or trusted governors: the ones responsible for the realm’s safety, ensuring laws are followed, and the medieval machinery of state ticks over. Back in Game of Thrones, ‘protector of the realm’ Ned Stark had his head chopped off and everything famously took a nosedive from there.
I’d argue this is a lesson in AI strategy.
At my company, Aiimi, we use this very same term - ‘protectors of the realm’ - to talk about the role of IT, Legal, and Compliance in operationalizing AI projects. But too often, businesses treat these governance functions as friction.
Whilst there aren’t any dragons for them to slay, these departments are there to protect your information and your systems - and above all, keep your company out of harm’s way.
Guardians or gatekeepers?Despite the work these departments do protecting companies from hefty fines and data breaches, I see an awful lot of corporate windbagging about how these departments bottleneck projects behind lengthy consultations, caveats, and due diligence.
The criticism is that they slow projects down. The reality is that they’re the difference between a fantasy strategy and a functioning one.
Ignore their counsel, and the whole structure gets weaker. Legal ensures AI tools follow information laws like GDPR and the new Data (Use and Access) Act 2025, so these systems only touch the data they’re meant to. Compliance maintains oversight once these systems go live, proactively ensuring that rules are followed and standards aren’t slipping.
IT does the essential work of making these projects function seamlessly in your organization's workflows and contexts. They maintain the infrastructure that AI runs on, ensuring that projects run on well-governed, structured data with documents having the correct permissions and access controls for safety. Without this groundwork, there’s little hope that an AI project can be effectively operationalized and return any sort of value.
But more than just facilitators of AI projects, these departments are the people in the room who know exactly what risks AI projects can pose, and what information they shouldn’t be privy to. Which, taking July’s Hugging Face fiasco as an example, matters more than most companies think.
Headlines would have you believe OpenAI’s models went rogue, broke through their safeguards, and attacked Hugging Face by their own autonomous decision. What actually happened is less dramatic and more damning.
OpenAI ran security tests with two AI agents where safeguards had been switched off. The testing sandbox, meant to be offline, was actually misconfigured to allow a connection out. The models escaped and attacked Hugging Face - not out of malice, but to cheat the security test by the laziest route available.
This was a governance failure. AI systems themselves can’t understand the reputational or financial risks that their actions might inadvertently cause. They do what they’re trained to do, and if there’s a shortcut to exploit, they don’t stop to check whether they’re meant to exploit it.
When critical business decisions are at stake, rushing a project past your protectors of the realm can leave you vulnerable to data breaches thanks to poor data security, or fines thanks to non-compliance. Having someone on board whose job it is to remind you of limitations and considerations serves to not only protect your organization, but make any AI project more resilient and deliver better results.
As AI regulation tightens and data security climbs up the agenda, it becomes more important than ever to have your protectors on side and fully integrated into design and deployment from the start.
Protecting the realm in practiceThere is sometimes a healthy level of skepticism in these departments so it’s key to invest in internal literacy programs to clearly explain the huge benefits of AI tools when they’re adopted safely, in line with your company’s governance principles.
Employees should walk away feeling clear about what terms like hallucination, training, and information retrieval mean for them, and how AI can fit into their work lives.
Once your protectors of the realm are aware of the terminology, they should be integrated into the design process of new AI projects to make use of their specialist knowledge.
Compliance might identify a specific challenge: governance teams are struggling to keep up with ensuring data quality and classification standards across different, growing systems in your organization.
This is crucial work that protects the business from breaching critical or sensitive data and powers data projects throughout the organization. They recognize that secure AI can help at scale. Now, together, you can develop a carefully planned use case that benefits multiple areas of the business: you need an AI-powered solution that can power data governance at scale by automatically classifying data.
IT can then help you plan how AI-powered data governance might fit into existing workflows and infrastructure, with data, compliance, and legal teams working together to understand the rules and give AI everything it needs to understand your business regulations and contractual obligations.
Your protectors of the realm should then also be part of any ongoing deployment. IT routinely checks the outputs of AI-powered systems, legal keeps abreast of any new legislation that you should be aware of, and compliance maintains ongoing human oversight so that you’re actively following regulation.
AI has incredible potential, but safe implementation is impossible if you don’t understand the rules. It might not be dragons and castles, but the companies that are positioned to generate reliable long-term success from AI projects aren’t the ones moving fastest, but the ones inviting their protectors of the realm to the decision-making table.
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- The Ninja CrushBOSS is a blender, food processor and to-go tumbler in one
- It has a 1,200W motor, with presets for precise chopping, slicing and dicing
- It's on sale now for $319 / £239 (about AU$460)
If, like me, you love a good kitchen device you'll be well aware of the perennial problem: finding space for all your gadgets and their accessories on your counter or in your cupboards. So I'm intrigued by the strangely-named but fun-looking Ninja CrushBOSS, which is designed to replace three distinct products: a blender, a food processor and a smoothie maker, all with the same shared base.
The CrushBoss has a 1,200W motor and a 2.1 liter / 72oz jug for blending and a 710ml / 26oz tumbler cup for drinking on the go. And it has a smart menu system that promises to make even the most tedious chores quick and easy.
Ninja CrushBOSS: key features and pricingThe Ninja CrushBOSS's jug has a curved square design to eliminate dead zones, and the SmoothSense system offers optimized blending, presets for chopping and mincing, and a custom control with 10 manual speed settings.
There's an integrated touchscreen display and a straightforward dial control, and it's designed to handle everything from smoothies and ice to shredding, slicing and dicing. There's an optional dicing kit accessory designed to deliver consistent dicing for more intensive tasks such as chopping ingredients for salads, salsa and other ingredients.
It's an interesting alternative to a full food processor whose various bits and bobs require quite a lot of storage: while there are still individual blades and bodies here they're not as numerous as the ones gathering dust at the back of my kitchen units. And if you've been disappointed by all-in-ones in the past, the high power here – 1,200W, which is 100W more powerful than the Ninja BlendBOSS — should make short work of even the toughest veg and effortlessly crush ice for your cocktails.
The Ninja CrushBOSS (including all attachments) is available for $319.99 in the US, and £239.99 in the UK. That's about AU$460, though the Australian release date has yet to be confirmed.
The European Union's new Tech Sovereignty package highlights a challenging question for governments across Europe, including the UK: how can countries benefit from AI without becoming dependent on technologies developed elsewhere?
AI is becoming a critical driver of economic growth, public service transformation and business competitiveness. Yet much of the AI technology stack continues to be developed and operated primarily in the United States and China, creating a growing tension between AI adoption and strategic control.
Although the UK is pursuing its own approach to AI regulation, European policy developments will continue to shape the environment in which many British organizations build, deploy and govern AI systems.
Recent UK government warnings that Britain must secure "greater control and leverage over frontier AI" show that AI sovereignty is moving from a theoretical debate to a practical policy challenge.
Building every layer of the technology stack domestically is neither practical nor necessary. At its core, AI sovereignty is about maintaining the freedom to choose, adapt and innovate without becoming dependent on any single provider or platform.
Choice, not self-sufficiencySome countries are pursuing far-reaching self-sufficiency strategies. Others are building on existing infrastructure and expertise while using partnerships to close technological gaps. For most economies, the latter approach is likely to be more realistic. Sovereignty is not about building every component domestically; it is about ensuring strategic control and avoiding excessive dependence on any one supplier.
Regulation may have a role to play. While concerns remain about compliance burdens and their impact on innovation, the broader objective is clear: creating an environment in which organizations can adopt AI with confidence.
This is where dynamic and competitive AI markets become essential. A diverse digital supply chain creates options, strengthens resilience and reduces the risks associated with concentration. Recent restrictions on access to Anthropic's frontier AI models in some non-US markets are a reminder that when access to advanced AI capabilities is restricted, choice itself becomes a strategic asset.
Infrastructure is only useful if everyone can use itMuch of the AI policy debate focuses on the data centers needed to train large models. Yet infrastructure for broad adoption is equally important.
Distributed edge networks located closer to users help deliver AI applications with the low latency, performance and scalability required for real-world deployment. At the same time, access to AI tools must extend beyond a small number of well-resourced organizations.
Usage-based and serverless models can lower barriers to entry by reducing upfront costs and allowing organizations to pay only for the resources they consume. This enables SMEs, researchers, public institutions and larger enterprises alike to experiment with and adopt AI technologies.
Control over data is another critical element. Sovereignty depends less on where data is stored and more on whether organizations can manage access, security and compliance requirements effectively. Global, distributed architectures enable the implementation of access rules and controls over where data is processed and AI applications are operated.
Openness is a strategic advantageOpen standards and interoperable technologies are becoming increasingly important building blocks of digital autonomy. They reduce switching costs, strengthen competition and help prevent dependency on individual providers.
The same principle applies to AI models themselves. Organizations increasingly need access to a range of different open-source and proprietary models, allowing them to select the best solution for different use cases rather than relying on a single platform.
Control through opennessThe debate around AI sovereignty is often framed as a choice between dependence and isolation. In reality, the most effective path lies somewhere in between.
Countries do not need to own every layer of the AI stack to exercise meaningful control. What they do need is access to open, competitive and resilient markets that provide genuine choice.
For the UK, and Europe alike, strategic control will come not from limiting access to technology, but from ensuring organizations have the freedom to choose how they adopt, deploy and govern it. In an increasingly interconnected world, that freedom of choice may prove to be the most important form of sovereignty of all.
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Frustrated by workflow limits and token-based billing on AI automation platforms? n8n is a “fair-code” automation platform that you can host on your own device or servers, free from the usage restrictions that plague cloud-based platforms.
We’ve covered n8n on TechRadar before, so head over to our first-time user guide and list of compatible hosting solutions if you’re looking for more information. For now, however, I’ll walk you through the exact step-by-step process of setting up a self-hosted n8n environment using Docker, Docker Compose, and a Linux-based virtual machine or server.
What you'll need for this setup- A virtual machine, server, or NAS with at least 2 vCPUs and 4GB of RAM. Heavier workloads will benefit from more CPU cores and memory.
- A compatible version of Linux installed on your server or machine, such as Ubuntu, Debian, or Raspberry Pi OS. CentOS Stream, Fedora, and RHEL are also supported.
- Access to the Docker and Docker Compose repositories using your Linux distro’s package installer. All of this can be installed through the Linux terminal.
- A managed Kubernetes cluster if you intend to run production-grade workflows (optional).
Power up your Linux terminal. Then update your Linux software catalog by running this command:
sudo apt-get update
This will update your software packages, install any necessary certificates, and prep the system for installing Docker. Once done, execute the next command to install Docker and Docker Compose, along with any dependencies your system needs:
sudo apt-get install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin
You can manually confirm that your Docker engine is installed and running by executing this command:
docker --version
docker compose version
Create a new directory for your n8n setup, then navigate into it:
mkdir n8n-compose cd n8n-compose
Now, you need to create a new .env file inside the new directory. It should look like this:
DOMAIN_NAME=example.com SUBDOMAIN=n8n GENERIC_TIMEZONE=Europe/London SSL_EMAIL=you@example.com
Make sure to replace these values with your domain name, time zone, and email address. If you’re running n8n locally on your device, you can simply remove the domain name, subdomain, and SSL email fields to leave only the GENERIC_TIMEZONE field in there.
Next up, we need to create a compose.yaml file in the same directory along with the .env file. It should read like this:
services:
n8n:
image: docker.n8n.io/n8nio/n8n
restart: always
ports:
- "127.0.0.1:5678:5678"
environment:
- N8N_HOST=${SUBDOMAIN}.${DOMAIN_NAME}
- N8N_PORT=5678
- N8N_PROTOCOL=https
- NODE_ENV=production
- WEBHOOK_URL=https://${SUBDOMAIN}.${DOMAIN_NAME}/
- GENERIC_TIMEZONE=${GENERIC_TIMEZONE}
- TZ=${GENERIC_TIMEZONE}
volumes:
- n8n_data:/home/node/.n8n
- ./local-files:/files
volumes:
n8n_data:
This maps n8n to port 5678 on your device and stores all your workflows, credentials, and encryption key in a Docker volume. Again, if you’re installing locally, you can simply remove the N8N_HOST, N8N_PROTOCOL, and WEBHOOK_URL lines.
In the same directory, create a local-files folder to store all your workflows:
mkdir local-files
(Image credit: n8n)3. Launch n8nYou can launch all your Docker Compose containers simultaneously using a single one-line command:
docker compose up -d
After about a minute or so, run this command to see if the containers are up and running:
docker compose logs -f n8n
You can now open the n8n editor at https://localhost:5678 on your local device using any web browser.
4. Create a n8n accountWhen you launch the n8n editor in your browser for the first time, it will ask you to create a new account. Enter your email, name, and a password with at least one capital letter and a number. Once you complete the form, you’ll become the instance owner, which is similar to a super-admin in n8n.
This will give your account full access to every workflow and credential, but you should still set up member-level accounts if you intend to have other people use your instance and want to track changes.
5. Build your first AI workflowYou’ll now be able to access n8n’s workflow editor. This is a node-based visual interface that looks a bit like a flowchart with the option to add triggers and actions to create complex automations. If you’ve used a tool like Zapier or Make before, it shouldn’t take you long to figure out the basics.
n8n lets you use the Execute step button to trigger different parts of a workflow during editing, which is useful in testing and troubleshooting. Once you’re confident that everything works, you can save the workflow and toggle it on so that it stays active.
(Image credit: n8n)FAQsIs n8n open-source?n8n isn’t open-source but free-to-use with certain limitations. It’s distributed under a fair-code license that lets you use the platform for personal or internal business workflows free of cost. If you wish to commercialize it as a consumer-facing product, however, you’ll need to pay for a commercial license.
Does it cost anything to self-host n8n?There’s some cost involved in setting up a self-hosted n8n environment, but it’s much less compared to how much you’d pay with a cloud-based automation platform with a subscription. Your only expenses here are your hosting costs for the server you use, but even that can be removed if you have a powerful enough local rig that can run workflows on its own.
Does n8n come with its own database?n8n comes pre-loaded with SQLite on with every installation, which is fine for internal use. If you want to run production workflows, however, I’d recommend switching to PostgreSQL, which can better support complex multi-user workflows.
How do I keep my n8n instance secure?Make sure to run your n8n instance over an HTTPS connection instead of plain HTTP. If you’re using an external server or a local network that’s shared by other users, take extra care to keep your encryption keys secure and do not put them directly in your .env file. Depending on your server configuration, you can use a secret manager like Azure Key Vault or Google Cloud Secret Manager to avoid attackers from reading your API keys by scanning the source code in plain text.
For the last two years, many organizations have treated AI adoption as the goal. The more users, tools and experiments, the better. Today, leaders are no longer measuring success by adoption alone. They are asking what it costs, where it creates value and whether the business can afford to scale it responsibly.
That is the next chapter of AI and technology spend management. The companies that thrive in this environment won't necessarily be the ones consuming the most technology. They will be the ones that can connect technology consumption to measurable business value.
This shift from maximizing usage to maximizing value, what I call valuemaxxing, is becoming a defining challenge for technology leaders.
Executives who take these five steps now will be prepared for a future where technology consumption and business value must be measured together:
1. Gain real visibility across the full technology stackOrganizations cannot manage what they cannot see. This becomes far more urgent when costs are variable, distributed and constantly changing.
Today’s technology consumption does not sit neatly in one budget or one system. It spans SaaS applications, cloud infrastructure, data platforms, AI models, agents and infrastructure. AI adds another layer of complexity because spend can show up through tokens, credits, model usage, GPU consumption, data movement and AI-enabled applications.
With only 31% of organizations reporting visibility into AI software today and 59% reporting increased wasted AI spend year over year, gaining a single source of truth across the technology stack has never been more important.
Without a complete view of technology consumption, organizations are left making decisions with fragmented information. Visibility isn't simply about controlling costs; it's about understanding where investment is delivering value and where spend is wasted.
2. Build a governance model for consumptionMany organizations encouraged broad AI experimentation, only to later discover that usage had outpaced oversight. Having an internal governance framework in place is critical to any company’s success. Governance gives teams the guardrails they need to scale responsibly.
For AI in particular, leaders need to move from “use more” to “use better.” It’s figuring out whether AI is improving cycle time, customer experience, operational efficiency, revenue growth, or another important business metric.
To guide the process, increasingly large enterprises (85%) are appointing dedicated teams or senior leaders for AI and tech governance to enable visibility, control, and cross-team collaboration. It’s vital for companies to prevent AI from becoming an uncontrolled cost center.
3. Renegotiate contracts for flexibility and accountabilityTechnology pricing models are changing rapidly. Long-term fixed agreements may still have a place, but they are becoming harder to manage in environments where usage can shift quickly.
Today, leaders should regularly evaluate vendor agreements to ensure they reflect actual usage patterns and future business needs. This is particularly important as AI providers continue introducing new consumption models and monetization strategies.
Enterprises should expect more pricing complexity, not less. The goal is not simply to negotiate lower costs. It is to create agreements that give the business room to innovate while maintaining control over spend.
4. Align technology, finance and procurementUsage-based costs impact multiple teams. While technology teams drive how much is used, other departments manage the needed oversight, with finance owning the budget impact and procurement handling vendor contracts. Without alignment, organizations can easily lose control of spending.
The organizations that manage consumption well will build a shared view of usage, cost and value. They establish common metrics, clear accountability, and regular collaboration across departments.
When teams work from the same data and the same definition of value, those decisions become more intentional and avoid costly surprises.
5.Use AI to move optimization from reactive to continuousUse AI tools to help manage the growing complexity of technology consumption itself.
Optimization cannot remain a periodic budget exercise. By the time a cost issue appears in a report, usage may have already shifted again.
AI can help teams detect unusual usage patterns, surface waste, forecast demand, and support smarter planning across teams. But AI-driven optimization must be connected to human-defined goals. The objective is to help teams make better decisions faster, with clearer insight into what is being used, what it costs and where it creates value.
Turning tech consumption into valueThe next phase of enterprise AI will look very different from the first. For the last several years, the focus was on experimentation and adoption. The future belongs to organizations that can demonstrate accountability, governance, and value.
AI has accelerated the industry's shift toward consumption-based technology models, introducing new economic challenges alongside new opportunities. As organizations continue scaling AI, understanding the relationship between usage, cost, and business impact will become a critical competitive advantage.
The AI adoption spree is ending. What comes next is more disciplined visibility, governance, and financial accountability, defining who can successfully scale innovation and who gets overwhelmed by the bill.
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- Agentforce is now worth around $1.2 billion annually, and climbing
- Customers aren't so sure about their data readiness and agentic maturity
- Many AI projects could be cancelled as users experiment with use cases
Even though Salesforce says its Agentforce business has reached a staggering $1.2 billion in annual recurring revenue, a new report has revealed that partners aren't actually seeing that same surge in revenue.
While the company may be bringing in plenty of revenue from pilots and trials, it seems that customers are yet to see the meaningful results they were hoping for, holding them back from large-scale deployments.
A new TD Cowen report (via The Register) backs this up, uncovering customer dissatisfaction, particularly around data readiness and agent maturity.
Agentforce isn't delivering... yetAccording to the survey, 11% of partners hadn't see much immediate interest, with more than half (56%) anticipating upcoming interest but acknowledging that customers need time for initiatives to mature. Only one-third said there was strong interest in Agentforce at this moment in time.
The report also uncovered a 10pp drop in Salesforce partners meeting or beating commercial targets, at 33% this quarter compared with 43% last quarter, with TD Cowen describing adoption as "subdued."
This latest report reflects similar findings from an earlier KeyBanc Capital Markets study (via The Register), where analysts found that customer data still isn't good enough to fully benefit from agentic AI. Around two years after Agentforce was introduced, customers are also dissatisfied with the product's maturity itself.
More broadly, though, it could just be a sign of the broader landscape rather than an Agentforce problem. Last year, Gartner predicted that more than two in five AI projects would be cancelled by the end of 2027 due to factors like "unclear business value" – in other words, this expensive and senseless period of experimentation is just a natural part of the process as users find their feet and reveal the true use cases.
Salesforce is still filled with optimism after transitioning to become an AI-first company – after an "outstanding" quarter, CEO Marc Benioff described agentic AI as "the biggest growth opportunity for [the company's] customers."
Cyberattacks are increasing in speed and sophistication, ranking among the biggest threats to businesses of all sizes and industries.
Previously unprecedented costs have made headlines; in October, a report from the Cyber Monitoring Centre revealed that the cybersecurity incident which affected Jaguar Land Rover in August cost the UK economy an estimated sum of 1.9 billion pounds.
Meanwhile, in North America, the aerospace sector has seen a spate of attacks, with WestJet’s June cyberattack resulting in the theft of 1.2 million passengers’ data while the data sets of 1.5 million flyers are believed to be compromised following September’s attack on Collins Aerospace.
Research released earlier this year revealed a stark dip in public trust; when questioned on which industry consumers trusted with their data, no single sector saw an approval rate of above 50%.
Without a clear and modernized security strategy, businesses are leaving themselves vulnerable to the far-reaching consequences of a breach, including reputational damage, operational delays, and financial loss.
Why Zero Trust MattersAI has given everyone with a computer, tablet, or even smartphone easy access to automation, including those using it with malicious intent. In the cyber space, this allows criminals to continually change their approach, scaling their efforts and exploiting vulnerabilities in their target’s software. To keep up with evolving threats, Zero Trust is vital, prioritizing data over assumptions is not optional.
The contemporary approach to the principle of Zero Trust has been developed from the work of the Jericho Forum, made up of industry experts keen to establish a ‘de-parameterized’ model that enables a more granular and flexible approach to security.
The group, which later became part of The Open Group Security Forum, paved the way for John Kindervag’s popularization of the Zero Trust principle in 2009, emphasizing the importance of 'Never trust, always verify'. In a conversation with Gartner’s Neil MacDonald, he further explained that “Zero Trust is not a technology; it’s a security philosophy that rewires how we think about access”.
It's a smart idea; allowing security systems to keep up with industry change. In reality, however, despite the majority (96%) of companies incorporating, or planning to incorporate, a Zero Trust strategy, only 35% have made it to the implementation stage.
To decrease the frequency of corporate security breaches, this needs to change. The key to success? A mutually agreed understanding of what Zero Trust is and a cross-industry implementation drive.
Steps to a Modernized Security StrategyThe traditional business approach to cybersecurity, including an over-reliance on VPNs, led companies to draw a single ‘perimeter’ around their data. Thus, once breached, cybercriminals were able to steal and duplicate data from across the organization. In contrast, with a strategy led by strict adherence to the Zero Trust principle, access is confined to the singular section where the incident occurred.
The successful implementation of the Zero Trust principle requires a focus on data and information security across all networks and platforms. For example, the evaluation of risk should take place on a case-by-case basis, with deliberate decisions made to accept, mitigate, or transfer. With this approach, security teams have the flexibility needed to safeguard data and, when inevitable breaches do occur, ensure hackers can only access the top layer of information.
The use of Zero Trust as a basis for risk management necessitates a security infrastructure that does not become stagnant but is ever-changing to prevent cyberthreats from impacting the organization. At any point, a key tech stack component can become a target for criminals. In response, to drive resilience, security professionals should track any attempts, and techniques used, amending infrastructure in tandem.
Across sectors, cybersecurity budgets are growing. In March, the IDC's Worldwide Security Spending Guide predicted a spending growth of 12.2% in the year that followed, growing to $377 billion by 2028. Though this reflection of increased enthusiasm to strengthen security infrastructure is a step in the right direction, organizations need to ensure this investment isn’t just a one-off. Every element, and everyone’s access, must be continually questioned to protect from the escalating threat posed by a breach.
Designing a Forward-Looking Security StrategySolutions adopted with cybersecurity in mind may differ between organizations but, to drive resilience in the long-term and successfully embrace the principle of Zero Trust, vendor-neutral definitions of methodology and standards will be a necessity.
Once these are widely acknowledged, a commitment should be made to strengthening the underlying security infrastructure over the long-term, driven primarily by the principle of Zero Trust. In a landscape where security threats are ever-evolving, so too should each corporation’s ability to protect themselves from malicious actors. This includes blocking access to valuable data sets in the event of a breach and ensuring each person responsible for security is kept up to date with the latest insight on the nature of threats.
When applied in practice, though the exact methods and vision may differ, the guiding principles should remain consistent. To establish necessary considerations, organizations can start with the Zero Trust Commandments, which include the need for security to be integrated through culture and processes, the implementation of asset-centric controls, and the explicit validation of trust through using all relevant information available.
A news landscape dominated by security breaches and cyberattacks has created a generation of consumers that, more wary than before, are no longer shocked when the personal information they have willingly shared with corporations is taken with malicious intent. It should be expected that they will think twice before trusting a new organization with their information, placing an onus on businesses to prove that their infrastructure is robust.
As we look ahead to 2026, the companies that succeed will prioritize security, consider wider society expectations, and prove their commitment to Zero Trust in each decision they make.
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