Available in black, gray, and pink colors, the Hinomi X2 Pro Ergonomic Office Chair is designed for anyone spending long hours at a desk, with a four-panel backrest, adjustable lumbar support, and 6D armrests. The successor to the X1, it offers 15 adjustable elements to help accommodate different body shapes and sitting preferences.

Best For: Home office workers, professionals spending long hours at a desk, and anyone wanting extensive ergonomic adjustments.

The Deal: The Hinomi X2 Pro Ergonomic Office Chair is reduced from $899 to $699 for Black Friday, saving $200 (22%). The promotion runs from November 1 through November 30.

Why we recommend it

Finding an office chair that fits properly can be difficult, particularly if you're taller, shorter, or regularly change how you sit. The Hinomi X2 Pro addresses this with a height range of 5'1" to 6'6" and 15 adjustable elements.

Its four-panel backrest supports different areas of your back, adapting to changes in posture. The 3D lumbar system offers additional adjustment for your lower back, and the 6D armrests can be repositioned to suit different tasks, including typing, reading, and leaning back.

The wear-resistant mesh upholstery will help with ventilation, and the aluminum alloy frame and base promise a sturdy foundation. The chair supports up to 330 lbs and has been tested to BIFMA standards, with verification by TÜV. Hinomi also offers a warranty of up to 10 years.

In his four-star review of the Hinomi X1, our expert Collin said: "This chair has fantastic adjustability, allowing it to be customized to your liking and even your specific use case." He summed up his review saying: "All around, this is a fantastic chair. If you are looking for a great ergonomic chair, this one is a great one to consider."

For more of our favorites, see our guide to the best office chairs we've tested.

Price context & historical value

The Hinomi X2 Pro normally sells for $899, but the Black Friday promotion brings it down to $699, a huge $200 saving. This is the lowest price of 2026, and the deal runs until November 30.

British buyers can snap up the chair for £699, down from £899, from here.

Should you buy it?

✅ Buy the Hinomi X2 Pro if...

If you spend a lot of your working day sitting and want a chair with extensive adjustments. The four-panel backrest, 3D lumbar support, and 6D armrests offer plenty of ways to tailor the fit, and the mesh upholstery and substantial warranty add to its appeal.

❌ Skip the Hinomi X2 Pro if...

You don't spend a lot of time sitting at your desk or prefer a traditional padded office chair. Even with $200 off, the X2 Pro is a considerable investment, and its extensive adjustment options may be unnecessary for some users.

• Shop all the office chairs on sale at Hinomi

During the winter months, working at a computer can be uncomfortable, especially if suffer from cold hands like I do. The Afenau heated mouse pad offers a simple solution, warming the surface beneath your keyboard and mouse while doubling as a full-size desk mat.

With three temperature settings, a waterproof surface, and a built-in digital display, it's designed to make long sessions at your desk far more comfortable.

Best For: Home workers, students, gamers, and anyone who spends hours at a computer in a chilly room.

The Deal: The Afenau 80 x 33cm heated mouse pad costs £17.59 at Amazon. It offers three heat settings, a waterproof PU leather surface, and automatic shut-off.

Best Heated Mouse Pad deal

Why we recommend it

With heating bills remaining a concern during the cost of living crisis, the Afenau heated mouse pad offers a way to keep your hands toasty warm without turning up the heating. Measuring 80 x 33cm, it provides enough space for a keyboard and mouse, with heating elements that cover 95% of its surface.

There are three selectable temperatures: 40°C, 45°C, and 50°C and the digital display in the upper-left corner shows the selected temperature, which the heating system can reach in 10 seconds.

The polyurethane surface is waterproof and resistant to everyday spills and scratches, with a non-slip underside to keep everything in place. At 550g, the mat can be rolled up for storage when you're not using it.

There's a visual reminder designed to encourage you to take a break after an hour of sitting and automatic shut-off offers another safeguard.

Price context & historical value

At £17.59, the Afenau heated mouse pad is an inexpensive way to add warmth to your desk without investing in a heater. Its combo of adjustable temperatures, waterproof construction, and digital controls provide several features beyond those of a conventional desk mat.

This is the cheapest price we've seen it at, so if you want to stay warm while working this winter, I'd definitely recommend it.

Should you buy it?

✅ Buy the Afenau heated mouse pad if...

If you work in a chilly room or suffer from cold hands, this is a great solution. The large dimensions, three heat settings, and wipe-clean finish make it a practical desk accessory.

❌ Skip the Afenau heated mouse pad if...

If your workspace is already warm or you need something that heats the entire room. No manufacturer warranty is specified either.

• Shop all desk pads at Amazon

• Attackers are actively exploiting the Plex2Shell vulnerability chain to compromise internet-exposed NAS devices
• QNAP urges immediate updates, as older Plex Media Server versions allow remote code execution and full device takeover
• Systems exposed before patching may already be compromised and require credential resets and full remediation

QNAP has issued a security advisory warning users to install the latest version of the Plex Media Server app on their Network Attached Storage (NAS) devices.

It says older versions are being actively abused in the wild using the dreaded Plex2Shell vulnerability chain.

“Plex has confirmed that these vulnerabilities are being actively and widely exploited,” the company said in the advisory. “QNAP urges all users running Plex Media Server on a QNAP NAS to update immediately and to review their devices as described below.

What is a QNAP NAS and what does it have to do with a flaw in Plex?

A Network Attached Storage device is a dedicated system allowing users to store, back up, and share files across a network. Essentially it’s a series of hard drives connected to a local network for easy access. Consumers and businesses alike often use it as an alternative to subscription-based cloud storage models, and sometimes even to stream audio and video files.

One popular way to do that is via a software application called Plex Media Server, which allows users to organize and stream their personal collection of movies, TV shows, music, and other multimedia content. By installing Plex on their NAS, and a compatible player app on a smartphone and similar device, users can access their media libraries over a local network or remotely via the internet.

This last part - via the internet - is where trouble was recently found.

Earlier in November 2026, Plex disclosed having fixed four vulnerabilities in Media Server versions 1.43.2 and older: CVE-2026-96652, CVE-2026-96654, CVE-2026-96655, and CVE-2026-96656. Separately, these four are relatively dangerous. Chained together, they allow unauthenticated threat actors to execute arbitrary code with the highest privileges, remotely. In other words, they can use Plex Media Server to take over the QNAP NAS and, if they choose to, access and steal sensitive content found there. These four have been given the nickname Plex2Shell.

Plex released a fix in September 2026, and a proof-of-concept (PoC) exploit was made available a few weeks later. Since then, multiple security companies reported seeing Plex2Shell abused in the wild, mostly to install proxy software and cryptocurrency miners. The latter might not be particularly useful, given that most miners require powerful GPU units, but the former could prove lucrative.

Patching Plex

A proxy network allows cybercriminals to route their traffic through legitimate residential infrastructure, helping them not just to hide their identities and whereabouts, but also to launch disruptive Distributed Denial of Service (DDoS) attacks. As such, residential proxy services are always in demand, and can earn their operators a hefty sum.

The US Cybersecurity and Infrastructure Security Agency (CISA) added all four bugs to its Known Exploited Vulnerabilities (KEV) catalog on October 20, and gave Federal Civilian Executive Branch (FCEB) agencies a mere three-day window to apply the fix or stop using Plex entirely.

That being said, Plex addressed the flaws in Media Server version 1.43.3 (build 1.43.3.10861), which can now be downloaded via QNAP’s App center. The company confirmed that the bugs exist only in Plex Media Server, QTS and QuTS operating systems were not affected. Still, Plex said if the NAS device was reachable from the internet while running older versions of the software, updating is not enough and the NAS should be treated as compromised.

Those users are advised to complete a clean reinstall, compromise check, and credential reset.

The exact number of internet-accessible QNAP NAS devices is difficult to determine, but according to figures from BitSight, there are tens of thousands of them, right now. That does not mean all of them are vulnerable (many might not be running Plex Media Server to begin with), but the theoretical attack surface is quite large.

Via BleepingComputer

Timekettle LiveTalk AI Translation Earbuds: 30 second review

The ideal translation device would translate live as you talk, so a conversation in two different languages can happen naturally. This was the concept of the fictional Babel fish in The Hitchhiker’s Guide to the Galaxy, although in that case the earbud was a fish that you stuck into your ear.

The Timekettle LiveTalk on the surface promises this live-talk potential with near-instant text translation, plus audio. The earbuds have several different translation modes that are selected through the TimeKettle App, and, of course, AI is built in to boost the humanisation of those translations.

The way translations work depends on which of the four modes you choose. Whether you’re talking to someone face to face, in a meeting, listening to discussions, tuning in to multimedia content in another language online, or on a phone or video call, you must select a pickup mode before you start. From there, you can select normal speech-to-text translation, which, with a strong Wi-Fi or mobile signal, is fast once the initial translation starts. The more interesting part is activating audible voice translation as well.

The actual audio voice is good, and you can select either male or female. If you have in mind that this will be just like BabbleFish translating live with the audio in your ear, think again. The delay is 7 seconds; this means you still have that start-stop approach to conversation at best. It’s more like having a translator standing with you rather than live translation.

The speech-to-text translation is faster, but in either case, alongside the slight wait, you still have that disconnect. One of the most interesting features is sharing the earbuds: each person in a two-way conversation has an earbud, with speech and translation happening. The effect is good once you learn to speak in short bursts of no more than 7 seconds, although you can speak for longer; the translation will start to kick in, and due to the delay, having someone talking to you and the translation at the same time, translating some 7 seconds later, can all be a lot to take in and a bit confusing.

At present, however, when you factor in the different translation approaches and the range of translation options, these small, easy-to-use earphones perform surprisingly well for other situations such as watching live presentations, some multimedia content and quick conversations.

Timekettle LiveTalk AI Translation Earbuds: Price and Availablity

At present, the TimeKettle Live Talk AI Translation Earbuds retail for £129 and are available directly from the TimeKettle website as well as other major online retailers such as Amazon.

• Score: 4.5/5

Timekettle LiveTalk AI Translation Earbuds: Design

The earphones arrive in a compact Star Silver charging case; that colour profile is essentially white with a slightly pearlescent finish. The supplied case is of a nice design and helps keep the earbuds clean and topped up with charge.

The case itself is simple, with the TimeKettle logo on top, but otherwise minimalistic, with the compact design measuring 65 x 74 x 22 mm and weighing 78g. This makes the design easily pocketable, and the closing mechanism is solid, meaning that when closed, it stays closed. Otherwise, on the exterior there’s just the single USB-C port along the rear edge for the power cable. The cable is also supplied in the box.

Opening up the case, the two over-the-ear buds are magnetically held in position in the case, with charging contacts that enable the two buds to be charged in the case in the usual way.

Alongside the hardware is the app, simply named ‘Timekettle’, and this is where the majority of the adjustments and settings for the translation mode, style and language can be made. This is all clearly laid out, and after the initial Bluetooth connection, you can get straight into using the buds and start translating.

Before you start a conversation, you need to select the type of translation you want, and there are four main types: Face to Face, Live Listening, Voice Call Translation, and Multimedia Translation.

Once you select the translation scenario you want, you can go to the main translation screen. At the bottom is a play button that needs to be pressed to start the live translation; this isn’t initially apparent. However, after the first use, the workflow becomes clear: the play button starts the translation process and doesn’t play back audio. For each of the modes there are also a series of options and these are all well laid out and clear to use.

• Design: 4.5/5

Timekettle LiveTalk AI Translation Earbuds: Features

The earbuds themselves are nicely designed, and along with a solid feel to the case, they all feel like a premium product.

The earbuds follow the open-ear hook design, which is comfortable and also lets you hear conversations around you. At 6.9g per bud, they’re also extremely lightweight.

The electronics inside have also been fine-tuned for translation and playback, with dual-microphone air-conduction voice pickup and a dedicated translation EQ that helps to enhance the audio captured.

Through the app, you can also access six EQ preset modes for music. While using these earbuds for more than just translation seems obvious, it isn’t always the case; and it’s great to know that you can use these for calls and as an all-day option rather than just being isolated to translation use.

My review sample arrived in the Star Silver colour profile, but if that doesn’t appeal, then they’re also available in two other colours; Polar Black or Deep Sea Blue.

For connectivity, the earbuds use Bluetooth and support dual connections so that you can connect to both your phone and computer at the same time. There’s also plenty of compatibility with applications such as Zoom, Microsoft Teams and many more.

Battery life, once fully charged, is surprisingly good, with around eight hours per charge and the case providing power for a top-up charge. The earbuds are rated for 4 hours of translation or 8 hours of music playback per charge, with the charging case extending total translation use to approximately 16 hours. Timekettle also advertises up to 35 hours of total battery life, while a quick 10-minute charge provides an additional 2.5 hours of use.

I’ve reviewed many of these translation devices. Timekettle has been one of the more consistent players in the market, with a full feature set that makes its devices useful in the real world and a viable, more advanced alternative to Google Translate.

Google Translate is, of course, free. In contrast with the Live Talk earbuds, there’s an outlay for the product and then often an additional cost for the extended use of the translation service, although with 200 minutes a month included for free, that does give you plenty of scope for use. The paid tiers just extend the translation amounts if you need the functionality for business, for instance.

The first major difference between Live Talk and Google Translate is real-time, two-way translation, with the text translating quickly as the conversation happens. This doesn’t differentiate it from Google much at first, other than that I found the transcription speed faster. The translation accuracy was essentially the same, but LiveTalk also offers 25 offline language pairs through downloadable language packs. This is useful when travelling without a reliable connection, although Google Translate also supports offline translation.

Although without the AI boost, the translations are a little more formulaic. The translation through the TimeKettle App is easy to read, and I found the user interface is far more user-friendly than Googles.

But then, with a quick tap of the voice button, that face-to-face conversation is not only translated into text but also spoken directly into your ear. The translation speed to text is fast, although it depends on your connection speed and ambient noise; it's impressive nonetheless, but the translated audio is notably slower.

In the app, you select the translation environment you need: Face to Face for one-on-one conversations, Live Listening for lectures and meetings, Voice Call, or Multimedia Translation.

Currently, it supports up to 54 languages and 108 regional accents. For example, there’s French and French Canadian. While the system works best with an online connection, it also offers 25 language pairs that can be used offline. The system also uses the Babel OS 3.0 AI translation engine, which you can switch on and off; testing showed it improved translation quality and speed.

One of the features that impressed me was the automatic language detection, although you can still manually select the languages you want, for example, English to French.

Some of the most useful transcription features include real-time speech-to-text transcription with bilingual transcription that’s displayed on the phone’s screen. You can also ask for AI-generated meeting summaries and other summary templates for different situations; this is a feature that I have liked on AI note-taking devices in the past.

As ever, transcription has paid tiers, but the free tier is surprisingly good: up to 200 minutes of translation a month, covering all four translation modes.

Other paid plans include the Unlimited Plan at £9.99 a month and a yearly option at £99.99 a year.

• Features: 4.5/5

Timekettle LiveTalk AI Translation Earbuds: Performance

The LiveTalk earbuds arrive in a compact charging case, and before starting the test, I left them overnight to ensure both the earbuds and the charging case were fully charged.

Once fully charged, I ran through the setup process, which involved downloading the app, opening the charging case with the earbuds inside, and tapping the Connect Device option. At that point, the LiveTalk hardware was detected. There was a little to-and-fro with the app and checking the Bluetooth connection, but overall it was well guided and connected quickly.

On the home screen, you have four translation modes: Face to Face, Live Listening, Voice Call, and Multimedia Translation. I started with the multimedia translation.

I found that getting started with this feature took some work. Initially, activating translation while you play back a video in French is simple. Just activate the Multimedia mode, click play, which sets the app up for translation as soon as it hears the vocals, then go to the media source, in this case, YouTube, and tap play. The video then starts to play, and about three seconds later the text translation appears, followed by the audio translation, which starts about seven seconds after the original word is spoken.

The written transcription and vocal translation are accurate, but the audio delay takes some getting used to, and it’s surprising how quickly things can move on in a YouTube video. The text translation, on the other hand, is almost instant.

There were a couple of issues, though: the original audio and the translated audio came through at the same time, albeit with a 7-second delay on the translation. With the default settings, the original video drowned out the translated audio. In the settings, it’s easy to find the translated audio volume. However, the original audio slider wouldn’t move on iOS, so I had to turn down the phone’s volume to balance the audio. That seemed a little convoluted, but it worked.

Once that was done, and slightly ignoring the delay, it did actually make it possible to watch videos with the translated audio coming through the earbuds. The delay is around seven seconds; while it’s fine for watching business presentations in another language, it wouldn’t be so useful for watching the latest French or Swedish drama. There’s also the issue that there is only one voice, so in one video, as it switched between the two presenters, they both had the same voice, making it difficult to determine which of the two was speaking. In this instance, that wasn’t an issue, but if you’re watching a drama, subtitles might still be the better option, even with the delay. To be honest watching a full drama with the earbuds isn’t really the intended use, but I was interested to see what would happen.

Next, moving on to Face to Face, and here you have two options. The first is to share the earbuds, with each person in the conversation wearing one. I tested this by being the English speaker while a friend who speaks French wore the other. In this situation, you assign the left to, say, French and the right to English.

Again, there is a delay, although this time it was five seconds. Another point I noted was that if you speak for more than five to six seconds, the translation starts for the person you’re speaking to. This obviously makes sense, but it can be hard to understand when the person speaking to you is in French, and the translation comes through at the same time in English, just five seconds behind.

The other option is to wear both earphones, with the other person using the phone. This is a bit of a mix-and-match approach, and in the end, just reverting to the text translation on the phone, which is extremely quick, worked well without the distraction of the delayed audio translation.

Another point is that when I first tried this, I was in a crowded café, and the translation worked well at first. But as the noise in the café built up, the translation became less accurate, often picking up audio from people around us, which became an issue.

Moving on from Face to Face, I used Live Listening, which worked well, although there was again a delay. Here, I had a colleague read a few paragraphs of French in the hall below the office. The translation of what came through was again delayed by about five seconds; however, that delay was far less distracting. Again, the text transcription appeared much faster, although in a lecture, the benefit of looking at the presenter or the person you have come to see is far more valuable than sitting in a live lecture looking at your phone. While it isn’t ideal, it does work well.

The final option was the LiveTalk Voice Call Translation. This option was surprising, as I think my mind is still attuned to slow video calls. To start the conversation, I had to switch from Speaker to Timekettle LiveTalk in FaceTime's speaker output options, and then the original and translated audio started coming through. Again, as with Multimedia mode, I had to adjust the phone’s audio.

The only other point is, again, remembering to assign the correct voice to the right person.

Alongside direct translation, these earbuds offer a few other options. First, every translation is transcribed so you can check it later, along with the original audio recording. You also get AI summaries, which could be really useful. However, during this test, when I tapped the Generate button, the key points for most translations appeared, giving a decent overview of what was being said. However, the AI Minutes seemed a little more temperamental, with ‘Generation failed’ appearing on quite a few of the discussions that I had.

Another feature I liked about these earbuds is that they can be used all day and for multiple tasks, since they’re not limited to AI translation. The open design hooks around your ears and sits just above the ear opening, leaving your ear canal unblocked so you can hear everything around you clearly. This means you can wear them during normal video meetings, while listening to music, and when making calls. If you’re used to inear or cans this does feel different, but is ultimately a more work friendly design.

I also found the battery life pretty decent, and the 4 hours Timekettle quotes for translation are pretty much on the mark.

• Performance: 3.5/5

Timekettle LiveTalk AI Translation Earbuds: Score card

TimeKettle LiveTalk: Final Verdict

At the start of the test, I was initially impressed with the translation speeds, especially for the speech-to-text, which is almost real-time as long as you have a decent network connection. As I progressed through the test and the four modes, I had mixed results.

The translation quality was good from English to French, and vice versa, and the audio translation was also better than I expected; you can tell it's a computerised voice that lacks some of the tone and emotion you would expect from a human, but it's still impressive.

The most exciting part of using these headphones was the conversation aspect, and the hope that, like the Babel fish, I could simply stick one in my ear and start conversing in other languages. Unfortunately, this wasn’t quite possible. The delay was just too great, and with the person speaking and the translation coming at you at the same time, it’s just a little too much to take in all at once.

I found that the speed of the speech-to-text translation worked far better, and with the AI enhancement, there was less direct translation, and what was translated became more natural. However, this isn’t too far removed from Google Translate, although the speed and accuracy do seem to be better, and of course the big advantage is that you can use it offline with the language packs.

The points that really stood out were the speed of translation and the live translation for events and seminars; while there is that seven-second delay, it just isn’t so noticeable.

For multimedia and video conferencing as well, once you work out how to reduce the speaker's volume, that becomes far more useful, and it’s surprising how much easier it can be for speakers in their native languages to express themselves through translation. However, you’re always aware of that five- to seven-second delay.

While it still has some way to go before it offers live speech-to-audio translation, it is getting close. If you travel abroad regularly and often get involved in short conversations, this will be incredibly useful. Otherwise, as a speech-to-text translator and for understanding live events in other languages, it does work well, and I found it more convenient than Google Translate for continuously translating large volumes of spoken words without having to stop and start.

• Crédit Mutuel Arkéa confirms cyberattack led to the theft of roughly $133 million from the bank itself
• Attackers reportedly converted stolen funds into cryptocurrency and laundered them across multiple services and blockchains
• Bank says customer assets were unaffected, while investigators continue probing the third-party compromise

Crédit Mutuel Arkéa, a major French banking and financial services group, has confirmed it recently suffered a cyberattack that resulted in the theft of around $133 million.

The stolen money apparently did not belong to customers, but rather to the bank itself, and was converted into cryptocurrency to be siphoned out more easily.

The attack was first spotted by ZachXBT, a cryptocurrency analyst and blockchain fraud investigator who issued an alert on November 2 2026. “An EU entity is suspected of losing $106M+ from multiple centralized exchange accounts yesterday (Nov 1),” he said at the time. “The suspected stolen funds were withdrawn as USDC & USDT by an illicit actor.”

Blockchain as the tech of choice for both sides

It appears the attackers converted fiat currency into different cryptos before sending them out. As ZachXBT explained, the threat actor was “aggressively swapping” USDC (a stablecoin currency, one whose value is pegged to that of the US dollar) for ETH (Ethereum) and transferring the tokens to instant exchanges such as WellWallet and Keyrex. Some of the funds were converted to XMR (Monero, a known privacy-first token whose transactions are notoriously difficult to track) via Wagyu, and later bridged “across multiple chains.”

The irony is pbvious - blockchain and cryptocurrencies are often perceived as the go-to platforms for financial fraud and while many defend it by saying the fraud conducted via fiat is magnitudes larger, the fact remains the crooks transferred dollars to cryptos during theft.

On the other hand, the attack was not even discovered (at least publicly) until it hit the public blockchain where analysts like ZachXBT were able to see it and report on it.

A day later, ZachXBT issued an update, saying he identified an additional $27M+ of withdrawals, bringing the total amount stolen to $133M+.

“My working theory is a large financial institution in Western Europe was exploited and it’s currently being covered up,” he said. “No proper incident disclosure has resulted in $30M+ being laundered away which could have been frozen by EU law enforcement,” he added, suggesting that Crédit Mutuel Arkéa handled the situation poorly.

In his reports, however, he never mentions the name of the organization targeted. Crédit Mutuel Arkéa released a brief statement on November 4, saying it suffered an attack which it later managed to contain.

“As soon as this attack was detected [...] the decision was made, as a precautionary measure, to temporarily suspend certain transactions in order to secure operations and prevent any further fraudulent movements,” the announcement reads.

“This incident is closed and is now under control. Operations are being gradually resumed over the course of the morning, after the group and its subsidiaries ensured that checks had been carried out and enhanced security measures had been put in place.”

Not Lazarus

In an FAQ published a day later, the company said the attackers “went through the platform of one of our service providers and thus reached Crédit Mutuel Arkéa directly.” It did not want to say which service provider that is, but ruled out Fortuneo since that name was apparently being mentioned in local press.

The attackers used Arkéa's own account to carry out transactions with other banking players, it said, confirming that customer funds are safe and unaffected.

“We would like to reassure all our customers that this incident has no consequences for their assets. It only led to a delayed execution of certain transfer operations,” the FAQ further states.

The bank did not want to confirm the amount of money that was stolen, but commenting on ZachXBT’s $133 million figure, said it can “simply validate the order of magnitude.” In other words - it’s a close estimate.

So far no threat actors claimed responsibility for this attack, and chances are none will. ZachXBT believes this was not the work of notorious North Korean actors Lazarus Group.

Via BleepingComputer

• Iris Ohyama discloses breach affecting 7.7 million individuals after attackers compromised its ecommerce platform
• Exposed data included personal details and some encrypted passwords, prompting password reset recommendations
• Company continues investigating the attack, with no ransom demand, attribution, or confirmed misuse reported

Major Japanese consumer goods manufacturer Iris Ohyama has confirmed suffering a cyberattack which saw it lose data on 7.7 million people.

The company first disclosed the breach on October 29, 2026 when it confirmed “unauthorized access on the e-commerce site” Iris Plaza. At the time, the company said its investigation was ongoing, and that it would temporarily suspend the site to ensure customer safety. While it was looking into possible data leaks, it stressed that credit card information was not taken.

A week later, Iris Ohyama came forward with a more detailed report, in which it said that on October 28, if found “suspicious files” on an external cloud service it used. The subsequently launched investigation confirmed that the attackers stole sensitive data on 7.7 million people, which included member data on approximately 5.8 million people, and non-member data on 1.9 million.

Member data included names, addresses, phone numbers, email addresses, genders, dates of birth, and encrypted passwords (for some users). The non-member data was limited to names, addresses, phone numbers, and email addresses.

Hashed passwords and stolen credentials

The fact that the passwords were encrypted is good news, since it means the accounts cannot be accessed that easily. However, the company did not say which encryption or hashing method it used, so it is possible that the attackers could break some of them offline. It is thus no wonder the company warned users to update their login credentials, especially for those who use the same password for other services.

Those that do use the same passwords across various platforms are also at risk of having all of them compromised, since threat actors are known for trying out the stolen combinations across a multitude of services.

We don’t know who targeted Iris Ohyama, and to what end. No threat actors have yet claimed responsibility for this attack, the data has not yet leaked to the dark web, and we’ve found no evidence it was used in phishing or social engineering attacks.

In a statement given to BleepingComputer, the company said it received no direct communication from the threat actors, no ransom demands, and did not know who they were.

We also don’t know which third-party cloud service Iris Ohyama used, which malware was used, or how it was planted there. In the meantime, the company notified the country’s data protection watchdog agency, as well as local law enforcement authorities.

Targeting Japanese organizations

Over the last few months, Japanese organizations have experienced a barrage of cyberattacks, targeting firms of different sizes and in different industries. Just last month, we reported on an attack on GMO, a data breach incident at Japanese Burger King, and a malware attack on Daiichi Kosho. The GMO attack was particularly worrisome, since the company urged its customers to “unplug any cords connected to your PC”.

Burger King Japan also recently lost sensitive data on 11.18 million customers, most of which were using the company’s official smartphone app, while a malware attack on Daiichi Kosho’s supply chain resulted in the compromise of 8.7 million of both customers and employees.

All of these are large organizations and major enterprises, and Iris Ohyama is no exception. The company is a large consumer goods manufacturer, known for household appliances and everyday products, and has been around for decades offering air conditioners, vacuum cleaners, kitchenware, lighting, pet food and accessories, as well as different food products like rice and water.

For the financial year 2025, the company reported an annual revenue of $1.53 billion, with a headcount of more than 6,300. It also has a substantial international presence, with manufacturing and distribution operations in the US, Europe, China, and South Korea.

As organizations look to embrace a new generation of autonomous AI agents which can access enterprise systems, make decisions and interact with other AI agents, new questions are emerging around how these systems are governed and secured.

As the governance of agentic AI and non-human identities rapidly one of the most significant challenges organizations will facein the coming years, we spoke to Umashankar Lakshmipathy, EVP and Head of Cloud, Infrastructure, and Security Services, EMEA, Infosys, to find out more.

• As organisations move from AI assistants to autonomous AI agents, what new security and governance challenges are emerging?

The move towards autonomous AI agents creates new security and governance challenges because these systems can make decisions and take actions with limited human involvement. Unlike AI assistants that primarily generate information or recommendations, agents can access enterprise data, use applications and tools, communicate with other agents and act on behalf of people or business processes.

This greater autonomy increases the potential business impact of an error, manipulation, or security compromise. An agent may have a valid identity and legitimate system access but could still take action that falls outside its intended purpose. The risk becomes more significant when agents operate across several systems, as one incorrect decision can trigger a sequence of actions that are difficult to detect, explain or reverse.

Organisations must therefore govern more than the AI model. Every agent needs a defined business purpose, an accountable owner and clear limits on the data, systems, and actions available to it. Sensitive or high-impact activities require stronger safeguards, while organisations need sufficient visibility to trace an outcome back to the person or process that initiated it, the agent that acted and the tools it used.

This represents an important evolution in AI governance. Organisations must continue to manage the quality and safety of AI-generated content, but they must now also control the decisions and actions that autonomous agents can execute. Getting that balance right will be essential to achieving the productivity benefits of agentic AI without creating unacceptable operational, financial, or regulatory risks.

• As agentic AI adoption grows, why are “non-human identities” becoming such an important issue for enterprises? What are the risks and opportunities when AI agents begin communicating and making decisions with other AI agents?

Non-human identities are becoming an important enterprise issue because a growing proportion of digital activity is performed by applications, APIs, service accounts, automation and AI agents rather than by employees. AI agents increase the significance of these identities because they can interpret information, make decisions and initiate actions, rather than simply execute predefined instructions.

This makes visibility, ownership, and access management essential. Organisations need an accurate inventory of the non-human identities operating across their environment, together with a clear understanding of their business purpose, accountable owner and access to systems and data. Without this foundation, excessive permissions, long-lived credentials, and identities that remain active after their original purpose has ended create material security exposure.

Communication between agents creates significant business opportunities. Specialised agents can work together to automate complex processes across customer service, operations, software engineering and cyber defense. A process that previously required several teams and systems could potentially be coordinated by a group of agents operating at much greater speed.

However, agent-to-agent collaboration also creates chains of dependency and trust. A compromised or poorly governed agent could pass inaccurate information through a workflow, influence another agent’s decisions or attempt to use a more privileged agent to perform an action that it could not execute directly. These risks can multiply when organisations cannot establish which agent initiated an action or under whose authority it was performed.

Organisations should therefore enable agent collaboration within defined business and security boundaries. The identity, authority and purpose of each agent should be evaluated independently rather than allowing trust or access rights to pass automatically from one agent to another. This approach allows enterprises to benefit from multi-agent automation while preserving control and accountability across the complete business process.

• How can organisations strike the right balance between giving AI agents autonomy and maintaining appropriate oversight and control?

The appropriate level of autonomy for an AI agent should be determined by the business impact of its activities, the sensitivity of the information involved and how easily its actions can be reversed. Applying the same level of oversight to every agent would either create unnecessary friction or leave higher-risk activities insufficiently controlled. For example, an agent that analyses public information or produces an internal summary can operate with relatively light oversight. An agent that accesses customer information, changes production infrastructure, makes regulatory decisions or initiates financial transactions requires much tighter boundaries.

However, organisations should introduce autonomy progressively. Some agents will remain assistive and provide recommendations for people to consider. Others may prepare actions that require human approval. More mature agents can operate independently within approved limits, escalating situations that fall outside their normal authority. Agents performing highly predictable and well-controlled activities may eventually be given broader autonomy, provided their actions remain visible, governed and capable of being stopped.

Human oversight remains important, but requiring approval for every action would undermine the efficiency that agentic AI is intended to deliver. It can also lead to approval fatigue, where reviews become routine and provide little meaningful protection. Human involvement is most valuable for actions that are financially significant, legally sensitive, difficult to reverse or outside the agent’s established operating boundaries.

The aim is not to give agents the maximum possible autonomy. It is to give each agent enough autonomy to deliver business value while keeping its decisions within an acceptable level of risk. Routine and reversible activities can be automated, while consequential decisions remain subject to stronger safeguards and clear organisational accountability.

• Are existing cybersecurity, identity and governance frameworks sufficient for the age of agentic AI, or do organisations need a new approach?

Existing cybersecurity, identity and governance frameworks provide a strong foundation for agentic AI, but they are not sufficient without further adaptation. Organisations do not need to replace established capabilities such as Zero Trust, identity governance, privileged access management and AI risk management. They do, however, need to apply these capabilities more dynamically to agents that can make decisions and take actions at machine speed.

Many traditional controls were designed around granting access to a person, application or service and reviewing that access periodically. Agentic AI introduces a more dynamic operating model. An agent may access several data sources, invoke multiple tools, interact with other agents and make numerous decisions during a single business process. Authentication alone cannot establish whether every subsequent action is appropriate.

Existing frameworks therefore need to be extended in several practical ways. Every agent should have a unique identity, an approved business purpose, an accountable owner and a managed lifecycle. Its authority should be limited to the task it is performing and should not remain active for longer than necessary. Stronger safeguards should apply when an agent accesses sensitive information, uses privileged tools or attempts an action with a significant business impact.

Organisations must also be able to reconstruct how an outcome was produced. This means maintaining a clear record linking the originating person or business process to the agents involved, the data and tools they used, the actions they took and the resulting outcome. This visibility is essential for oversight, investigation, regulatory assurance and rapid intervention when something goes wrong.

The required approach is therefore an evolution of existing security and governance rather than the creation of a separate control environment for AI agents. By extending established frameworks to govern agent identity, authority, and actions continuously, organisations can scale agentic AI while maintaining coherent enterprise-wide control.

The early rush to encourage employees to use AI wherever possible led to a new way of measuring productivity based on the consumption of AI tokens, or technically the underlying AI foundation model tokens. Employees who did not use AI were immediately visible through their AI consumption bill, or lack thereof, while high consumption was treated as a positive signal. The number of tokens consumed became a badge of honor.

For a while, more AI usage suggested more productivity and innovation. Some organizations even began treating AI activity as a proxy for employee engagement. This led to the phenomenon of ‘tokenmaxxing’, with the unintended consequence of AI costs growing out of control and raising a more difficult question: what does successful AI adoption actually look like and how do you measure it?

The latest Pulse of Work 2026 research points to the gap between adoption and value. While 88% of employees say AI has benefited them and estimate it saves them an average of 2.3 hours every day, four in five say they are not using it to its full potential and 69% do not fully understand how it applies to their role. Meanwhile, 60% feel pressure to use AI regardless of whether it is the right tool for the task.

These findings reinforce two points that should already be clear: one, AI activity is a poor proxy for business value, and two, organizations need to become more deliberate about where and how they use AI tools.

More AI does not automatically mean better work

The knee-jerk reaction to equate AI usage with success is understandable. Instant answers, automation of repetitive tasks and the removal of administrative burden from busy employees are clear and tangible benefits.

But problems emerge when AI becomes an expectation in every initiative rather than a considered decision that accounts for where human judgement is needed, which model is appropriate and what the associated cost will be.

When employers celebrate AI adoption without defining where it genuinely adds value, a problematic incentive structure develops. Employees naturally reach for AI more often, sometimes without considering whether it is the right tool, whether the output needs significant review or whether the cost of the model is proportionate to the task. Without clear parameters or support, the likelihood of misuse goes up.

Experimenting with AI should not be discouraged. In fact, it should be actively encouraged and is a crucial part of using this transformative technology for the greatest impact.

However, it’s important to also train employees so that they take a cost-conscious approach and leverage the right models for the type of task - using lower-cost models such as Gemini Flash and Claude Haiku for most tasks and only using the more expensive and powerful models such as Claude Opus and Claude

Fable for more complex tasks. The challenge comes when organizations encourage and reward use without putting the same energy into providing the proper training, guidance on cost-conscious adoption and development opportunities for their employees.

Productivity depends on workflow design

The biggest productivity gains come from identifying the scenarios where AI removes friction without compromising quality. Administrative work and removing toil remains an obvious starting point. Scheduling, email management, customer communications and routine documentation can all give employees time back for higher-order work.

From there, the real opportunity is helping employees build on their existing skills using AI to pressure-test ideas and move faster. That’s when the human-AI partnership works as it should, with technology extending what people can do rather than becoming a substitute for their judgement.

Role-specific guidance is what makes this possible. Although AI capabilities continue to improve rapidly, every function uses technology differently. A finance professional faces different governance requirements from a software engineer, and customer service teams need different safeguards from HR teams. AI training should account for such differences.

This is also why organizations should stop expecting employees to discover the best applications of AI independently. If people are spending time looking for ways to make AI useful, testing tools without guidance or working out how new capabilities fit into existing processes, some of the potential productivity gain is being lost before the technology has even delivered an output.

A better approach is to redesign workflows around genuine business outcomes. That means identifying where AI can remove unnecessary effort, then giving employees the tools and guidance to use it within the context of their role.

It also means making useful, approved AI available within the systems employees already use. When AI is integrated into daily workflows, people are more likely to apply it to safe, high-value use cases rather than seeking out unsupported alternatives.

Quality has become the missing metric

One of the highest hidden costs of widespread AI adoption is the additional burden of review and correction. AI can produce an answer quickly, but speed has limited value if employees then have to spend significant time checking whether that answer is accurate, complete or appropriate.

This is particularly important as AI-generated content becomes embedded in everyday work. A poorly reviewed output can create more work for another employee, introduce errors into a business process or undermine trust in the technology altogether. The productivity calculation therefore needs to account for what happens after the AI generates its answer.

Output quality, and ultimately, quality outcomes, should become part of the AI architecture itself. That means building review processes into workflows, introducing governance where decisions carry higher risk and ensuring employees understand the importance of validating AI responses before those responses become business decisions.

Done well, these safeguards should not stand in the way of adoption or slow employees down. They should give employees the confidence to use AI more effectively and adjust involvement where greater scrutiny or human judgement is needed. By implementing automated verification steps and role-specific parameters, IT leaders give teams the guardrails they need to drive productivity without compromising accuracy and trust.

The organizations creating value are building confidence

The biggest shift required now is cultural. Employees need clarity about when and how AI should be used, confidence that they are making appropriate decisions and practical support when new capabilities are introduced.

That support must extend beyond learning how to use a particular tool. Employees need to learn the best practices of reviewing AI-generated work for accuracy and bias, when to trust or question an output and when creativity or human judgement should take precedence.

Policies are key in achieving this by establishing consistency, but role-specific training, guidance and continuous learning ultimately determine whether those policies translate into everyday behavior.

For IT leaders, responsible adoption means creating the conditions for that confidence. They need enough visibility and oversight to manage security, compliance and quality, without introducing so much friction that employees simply look for workarounds.

The same principle applies to the technology itself. Organizations need tools that fit naturally into existing workflows and give employees the right capabilities for the work they are actually doing. AI adoption becomes much harder to manage when employees have to piece together their own collection of tools without clear guidance on what is approved, appropriate or secure.

At the macro scale, organizations need to treat responsible adoption as an ongoing process rather than a one-off rollout. As AI tools and capabilities continue to evolve rapidly, the guidance around them needs to keep pace.

The organizations creating lasting value from AI will therefore ask very different questions from those focused on token consumption.

Is work becoming more accurate? Are employees making better decisions? Are the most optimal models being used for the type of task? Are we achieving reliable, quality outcomes and optimizing the AI costs to get there? Are repetitive tasks being automated while human expertise is being applied where it creates the greatest value?

When leaders provide the tools, context and confidence employees need, productivity and ROI will naturally follow.

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• Ethical toilet paper company Who Gives A Crap exposes customer information following data breach
• Customers across UK, US and Australia affected
• Company warns users to be on their guard for scam or phishing attacks

Toilet paper firm Who Gives A Crap has told customers it has suffered a major data breach which leaked user information across three major markets.

In an email sent to customers seen by TechRadar Pro, the company apologized for the "unwelcome news" and promised to be "as clear as we can about what we know".

It noted that customers in its home country of Australia were affected, along with users in the UK and US - although users in its Canadian market were not affected.

"Unwelcome news"

"I’m writing to inform you that your personal information was accessed without authorisation in a security incident at one of our marketing software providers," the email told customers.

User first and last names, email addresses, phone numbers, mailing addresses were all hit in the breach, as was the total amount the user had spent with Who Gives A Crap.

The company said it did not know whether the stolen information was copied or downloaded, but did say payment details, order details and passwords had not been affected.

In a seperate blog post, Simon Griffiths, Co-Founder & CEO, Who Gives A Crap, said it had been informed by an unnamed "US-based software provider" that an "unauthorized party" had accessed systems holding information from its online store.

"The provider has said that access began on 30 October 2026, was identified on 31 October 2026 and was secured on 1 November 2026," the company added.

Who Gives A Crap said it had disconnected the affected provider from its systems, and changed access credentials. It was also communicating with the affected provider to understand the details of their investigation in order to determine if there is any further action required, and said that it would be engaging with the relevant regulatory authorities as required.

"Your account with Who Gives A Crap is secure and was not directly accessed, so you don’t need to take any action with your account," it told customers, warning them that the main risks now would come from criminals sending out scam or phishing messages using their real details to look convincing.

"We have no evidence of misuse so far, but please be extra cautious," it added.

When people think about autonomous vehicles, they tend to picture city streets, motorways, robotaxis or factories. Yet one of the most demanding environments for autonomous technology is somewhere very different: the farm.

At first glance, a field might appear easier to navigate. There are no traffic lights, relatively little traffic and fewer obvious obstacles. In reality, agriculture presents an extraordinarily complex environment for automation.

A machine needs to distinguish between an object blowing across a field and an animal in its path. It must operate when visibility is reduced by dust or rain and navigate environments such as dense crops, where assumptions developed for road transport do not necessarily apply.

This is why the rise of the autonomous farm is about much more than removing the driver from the cab.

A smart factory without a roof

A modern farm can increasingly be viewed as a smart factory – but one without a roof. Industrial automation generally operates under controlled conditions. Agriculture does not. Weather, soil conditions and crop development continuously change the operating environment.

At the same time, many agricultural jobs have narrow windows dictated by weather and plant growth. When conditions are right, work needs to happen immediately.

Autonomy has the potential to make these limited windows more productive. For example, autonomous tractors designed for tillage operations can use multiple cameras positioned around the machine to provide a 360-degree view of their surroundings. By combining computer vision, cameras and AI, such machines can navigate the field without requiring somebody to remain continuously in the cab.

But capturing images is only one part of the challenge. Those images need to become decisions. As images stream from the cameras, a high-speed processor evaluates the visual information. A neural network then classifies what the cameras see and determines whether the area is safe to drive over. In advanced autonomous systems, this type of decision can be made within a fraction of a second.

This illustrates an important point about applied AI: intelligence is valuable when it translates data into a useful decision quickly enough to affect the physical world.

From machine operator to operations manager

Autonomy also changes the role of the person running the farm. Farmers today are entrepreneurs, operations managers and increasingly data managers. Machinery, field and operational data can help them understand what is happening across the business, plan work and make better-informed decisions. As machines become more autonomous, farmers no longer necessarily need to be physically present in every cab to maintain oversight.

Cloud-based platforms provide the connection between the autonomous machine and its operator. Once a machine is positioned appropriately, an autonomous job can be started remotely through an app. Farmers can then access live video, images, data and metrics about the operation and adjust parameters such as speed. If the system identifies an obstacle, job-quality anomaly or machine-health issue, the operator receives a notification and can respond remotely.

The significance is not simply remote control, but remote visibility. Instead of one person being tied to one machine, the farmer can increasingly oversee work as part of a connected operation. The machine performs the task, sensors and cameras observe what is happening, connectivity makes that information available elsewhere, and the farmer remains in control of the wider process.

Autonomy cannot be one-size-fits-all

Agriculture is also remarkably diverse. Farm sizes, field structures, crops, soils and production systems vary significantly. Technology therefore has to combine standardization with enough flexibility to accommodate different operating realities and farmers’ needs.

That applies to adoption as much as operation. Autonomy cannot depend entirely on farmers replacing their existing machinery with new ones. Adoption therefore needs to accommodate both new and existing machines. Some machines can be autonomy-ready from the factory, while retrofit solutions can provide a route for certain existing equipment to adopt the technology.

This matters because the autonomous farm will not arrive overnight. It will emerge incrementally as machines, software, connectivity and data become more closely integrated.

Keeping the human in control

It can be tempting to frame autonomous farming primarily as a story about replacing human labor. That misses the more important change. AI and automation cannot remove weather, biology or economic uncertainty from agriculture. What they can do is help farmers manage that complexity.

An autonomous tractor taking care of tillage does not eliminate the farmer. It changes where human attention is required. Rather than continuously executing one task from inside a cab, the farmer can monitor operations, respond to exceptions and concentrate on decisions elsewhere in the business.

That is perhaps the most important lesson from the autonomous farm for the wider technology industry. Successful automation is not simply about making a machine capable of working without a person beside it. It is about combining AI, sensing, connectivity and human judgement into a system so that each plays to its strengths – giving farmers better information, greater visibility and more time to make the decisions that matter.

More time for what matters

The added value doesn’t just come when the machine drives across the field completely autonomously. AI tools can already ease the burden on farmers during peak work periods. But even with an autonomous tractor, the farmer isn’t completely out of the picture overnight.

He can tackle other tasks during the day while the machine handles soil preparation at night, for example. This helps ease the pressure of tight time constraints to some extent.

The autonomous farm is therefore not a farm without farmers. It is one where machines increasingly handle execution, data provides visibility, and people have more time to make the decisions that matter.

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• Nvidia CEO Jensen Huang confesses to affair with suspected Chinese spy
• Nvidia board says it has opened an internal investigation into Huang's behavior
• Company shares down 5% in pre-trading following news

Nvidia has opened an internal investigation into its CEO Jensen Huang after he was accused of having an affair with a suspected Chinese spy.

Huang has apologized for his actions in a letter to Nvidia staff, with the company saying it would now look into the incident, but was confident that no internal or national security secrets were compromised.

Nvidia shares were down 5% pre-trading on Monday, which might seem small, but it is one of the world's biggest companies, valued at around $4.50 trillion following its key role in powering the AI boom.

Jensen Huang affair

The Nvidia CEO is suspected of having an affair with Alice Huang (no relation), an executive for Megaspeed, a Singapore-based IT and cloud company currently under investigation for smuggling Nvidia GPUs into China.

Suspicion around an extra-marital relationship first arose in 2025, when US intelligence agencies watching Megaspeed and Alice Huang reported her relationship with the Nvidia CEO.

The New York Times published an initial report on the affair in November 2026, which Huang had called "groundless speculation", but the CEO was then called to Congress to give a closed-door briefing about the incident.

“Recent reports raise significant national security concerns regarding the PRC’s access to sensitive U.S. technology and information,” said Michigan Rep. John Moolenaar, who is also chairman of the House Select Committee on China.

“It is vital that Congress determines the extent to which US national security has been placed at risk."

Nvidia's board has issued a statement saying it would now begin "an independent investigation in light of recent reporting that founder and CEO Jensen Huang has been the target of a foreign intelligence effort."

"The Board prioritises US national and economic security, which is paramount to the interests of Nvidia and its shareholders," it added.

"While the Board has no reason to believe that either national security or Nvidia secrets were compromised, the Board's inquiry will examine all available information.

"Jensen fully supports the review and has committed to cooperating with it."

In his statement, Huang, who said he was "fully committed" to Nvidia, confessed, "I was unfaithful to my wife. My actions hurt her and our children. There is no excuse for what I did. I am deeply sorry," he said in a letter to staff.

"Throughout my life, my family has given me love and support. They deserve my honesty and loyalty. Instead, I let them down and damaged the life we built together. I take full responsibility for what I did and the hurt I caused, and I accept the criticism that comes with it.

"To my wife and family: I love you. I know an apology cannot undo what I have done. I hope our family will heal and that, over time, I can earn back your trust."

Analysis: What next for Nvidia and Jensen?

The question now is what happens to Huang - one of the most visible and central figures of the current AI boom.

Nvidia has been transformed from a gaming graphics card provider into one of the world's most important companies in recent years, with Huang's dynamic leadership helping power much of that.

This prominence has led him to become a central figure in world debates on technology, with Huang celebrated by President Trump (who has already come out in support of Huang, calling him "a fine person") on several occasions.

We have seen leaders and CEOs lose their jobs for far less than this in recent years, so will Nvidia's board be prepared to do the unthinkable and remove the leader which made the company what it is?

• China puts its first commercial 800V DC data center power system into operation
• Envision converts 10kV grid electricity directly into an 800V DC supply
• New power architecture combines solid-state transformers with battery storage for AI facilities

China’s Envision claims to have put an integrated 800-volt direct-current power architecture into commercial operation at an AI facility in Inner Mongolia.

The installation is located at the Galaxy AI campus in Ulanqab, where trials of its Dubhe controller and supporting energy model began in August 2026.

The company describes the deployment as the first commercial use of this configuration, although independent performance figures have not yet been disclosed publicly.

A different route from grid electricity to computing hardware

Conventional facilities generally convert incoming electricity through several stages before delivering power suitable for servers and accelerators, adding equipment and potential conversion losses.

Envision’s design instead uses a solid-state transformer to convert 10-kilovolt medium-voltage alternating current directly into an 800-volt direct-current distribution line.

The company says this arrangement reduces conversion steps, improves electrical efficiency and allows power equipment to occupy substantially less physical space within data centers.

A higher-voltage distribution network can also reduce the amount of copper required for cabling, potentially lowering material requirements as computing installations expand rapidly.

The architecture includes battery storage intended to respond rapidly when processor demand changes, while also supplying temporary backup during unexpected interruptions.

Envision says the storage system can provide immediate support over seconds and maintain backup capability across periods measured in several minutes.

Its controller coordinates the transformer and batteries within milliseconds, aiming to manage sudden changes in electricity consumption from GPUs.

That coordination matters because AI workloads can cause substantial swings in demand, placing additional pressure on electrical infrastructure supplying densely packed computing equipment.

The company also says its arrangement can accommodate higher-density server racks, allowing operators to install more computing capacity within a given floor area.

Ambitions extend beyond the first installation

Envision’s Galaxy facility is expected to grow to 3 gigawatts, with the company saying its eventual capacity could serve one million AI accelerators.

Envision also intends to introduce the technology through Mission Gobi, an initiative seeking 5 gigawatts of renewable-powered computing capacity by 2030.

That programme is focused on desert locations, where the company expects renewable generation and energy storage to support large computing developments.

The system has been designed to work alongside renewable electricity sources, while its batteries are intended to balance supply and changing computing requirements.

However, the company has not provided independently verified measurements quantifying efficiency improvements, installation costs or savings compared with conventional power systems.

The announcement does not also establish how the architecture performs under sustained full-load conditions or across facilities with substantially different hardware configurations.

The deployment therefore marks a commercial milestone for Envision, while the scale of its claimed operational advantages awaits detailed independent evidence.

Via Tom's Hardware

• Georgia Tech student says his homemade Reaper aircraft reached 491 mph
• Three working prototypes reportedly sustained the same claimed top speed for four minutes
• The $13,000 aircraft carried a 2.6-pound payload during its fastest run

A Georgia Tech aerospace engineering student says his experimental jet-powered model aircraft reached 491 mph, potentially setting a new record for remotely controlled planes.

Tomas Salvo independently developed the Reaper and reported on X that it carried a 2.6-pound payload during its fastest recorded run.

If independently verified, the claimed result would surpass the 465 mph mark set in 2017 by German pilot Niels Herbrich's Inferno aircraft.

Student builds a fast jet-powered aircraft

Salvo began developing the project in February 2025, designing and assembling its prototypes independently while living in university accommodation at Georgia Tech.

He has produced three operational versions, each reportedly capable of maintaining 491 mph for four minutes using a full fuel supply.

The drone uses a 250-newton turbojet, alongside a custom air intake and a titanium exhaust nozzle produced through 3D printing.

Its outer structure consists of molded carbon-fibre sections, while laser-cut parts form internal components.

The design can leave a launch rail or truck-mounted launcher before climbing to 6,600 feet (2,000 metres), within 20 seconds.

Salvo also says the aircraft can travel 31 miles (50 kilometres) when operating at its maximum speed, and that the project is “a reliable and repeatable system,” and repeated trials have produced closely matching performance results.

The development effort reportedly cost approximately $13,000, an amount Salvo funded personally while pursuing the project as a student.

He intends to conduct further flights and refine the aircraft, hoping eventually to exceed 500 mph (800 km/h).

Salvo’s post also attracted the attention of Prescott Paulin, Director of Industry Engagement at the Department of War’s Research and Engineering office.

Paulin, who leads industry engagement for the Pentagon CTO’s Mission Capabilities team, publicly invited the student to visit the department.

The Boom Prize offers a much larger speed challenge

The Reaper project also enters a field where amateur aircraft builders can compete for a substantial reward offered by Boom Supersonic.

The company's chief executive, Blake Scholl, announced a $750,000 cash award alongside $50,000 in company shares for a qualifying supersonic flight.

Entrants must fly a radio-controlled, fixed-wing aircraft faster than Mach 1 for at least five seconds before bringing it down safely, and complete the required performance twice on the same day, using one aircraft, for their submission to satisfy competition rules.

The challenge excludes rocket propulsion, onboard oxidisers and aircraft designed for one-time use, requiring competitors to use air-breathing engines instead.

Eligible propulsion systems include turbojets, turbofans and ramjets, while corporate sponsorship or venture capital funding disqualifies competing teams.

The rules also exclude projects connected to aerospace businesses or directed by professional aerospace engineers, restricting participation to amateur competitors.

Applicants must be American citizens, permanent residents or people who have received legal asylum in the United States.

A judging panel includes former Boeing chief executive Phil Condit, SpaceX co-founder Tom Mueller and astrophysicist Scott Manley.

The competition remains open until 2030, giving builders several years to develop aircraft capable of meeting its demanding flight and landing conditions.

Although Salvo says he hopes to pursue the $800,000 award, the reported 491 mph performance alone does not satisfy its supersonic requirement.

• Nvidia wants to convert more than 130 existing telecom properties to data centers
• Brightspeed's struggling business could become central to Nvidia's expansion strategy
• The proposed network could extend across as many as 20 states

Nvidia is exploring an unusual route into the AI infrastructure market, reportedly considering older telephone facilities as locations for compact regional computing operations.

The proposal involves Apollo Global Management and Brightspeed, a broadband operator whose property portfolio could provide sites across as many as 20 American states.

Repurposing telecom buildings could give Nvidia access to existing infrastructure without requiring every facility to be built from an empty nearby plot of land.

Nvidia targets alternative expansion route

Reports from The Information claim Nvidia has contacted Apollo about converting more than 130 Brightspeed properties into smaller facilities dedicated to running artificial intelligence applications.

Brightspeed is backed by Apollo and reportedly close to bankruptcy, although the proposed arrangement and its commercial terms have not been publicly confirmed.

Reports indicate that the properties collectively offer approximately 1 gigawatt of electrical capacity, potentially supporting substantial investment in Nvidia's next-generation server systems for future deployments.

Nvidia reportedly recently sent Brightspeed a written proposal and requested further information, alongside opportunities to inspect locations under consideration for possible conversion directly.

Amid concerns about data center expansion, there have been political calls for temporary restrictions from Democratic candidates in states including Texas.

Retrofitting existing properties may face fewer planning obstacles than entirely new developments, although local approvals would still be needed for cooling and other upgrades.

Nvidia has reportedly discussed beginning renovations with suppliers during the first quarter of 2027, using systems built around its upcoming Vera Rubin platform.

Unlike enormous training campuses, Nvidia reportedly describes the proposed locations as an inference network, intended to operate models that have already completed their initial training.

That distinction could make smaller sites useful to cloud operators and artificial intelligence developers needing computing capacity closer to customers and existing networks.

Nvidia's smaller AI facilities still face commercial and operational questions

Potential users could include OpenAI, Anthropic and SpaceX, although the report does not establish whether discussions about this particular network have taken place.

It also remains uncertain how many Brightspeed properties would be converted, who would own the equipment, or which customers would ultimately lease computing capacity.

Zac Smith, Datum's chief executive, told The Information that older telecom buildings can “unlock underutilized power,” although aging equipment may raise operating costs.

Smith also cautioned that older facilities may cost more to operate because their equipment can require additional maintenance and replacement during operation.

The reported discussions follow a decline of more than 9% in Nvidia shares during Thursday's trading session, marking their steepest daily drop since January 2025.

The drop occurred during a wider retreat in chip stocks, as investors assessed regulatory uncertainty surrounding the pace and scale of new computing developments.

Nvidia shares were reportedly down 3% year to date, despite renewed retail interest online that pushed Stocktwits sentiment from neutral into bullish territory

• Bosgame opens orders for its $6,199 Ryzen AI-powered compact workstation
• The M5 MAX combines AMD's Ryzen AI Max+ PRO 495 with substantial memory
• Bosgame equips its mini PC with an additional PCIe 4.0 storage slot

BOSGAME has opened orders for the M5 MAX, a compact workstation built for artificial intelligence tasks and other jobs that consume memory.

The mini PC runs on AMD's Ryzen AI Max+ PRO 495 processor, paired with 192GB of LPDDR5 memory soldered directly to the motherboard.

Storage comes with a 2TB solid-state drive using a PCIe 4.0 interface, giving the system fast internal storage from the outset.

Memory, storage, and cooling inside the chassis

Large language models, image generators, and data analysis applications can require substantial memory resources, making the system's hardware configuration particularly relevant to these workloads.

The available M.2 2280 expansion slot supports another PCIe 4.0 drive, allowing owners to increase storage capacity without replacing the factory-installed drive.

BOSGAME also incorporates a three-fan cooling arrangement, although the company has not released thermal measurements or acoustic results showing how effectively it handles sustained workloads.

This configuration could also interest executives at companies such as OpenAI, led by Sam Altman, whose businesses generate revenue from customers accessing models hosted in their own data centers.

Running compatible AI models locally could give some users an alternative to repeatedly paying for remote computing services, although the economics depend on hardware costs and actual workloads.

Extensive connectivity includes OCuLink and dual 10GbE networking

The BOSGAME M5 MAX comes with two USB-C ports supporting data transfer rates of up to 40Gbps each.

Both ports also support DisplayPort Alt Mode, allowing compatible monitors to connect through these interfaces alongside other peripherals.

Screens can also be connected through DisplayPort 2.1 or HDMI 2.1, with the latter using TMDS signalling.

Three USB-A ports operate at 10Gbps each, providing faster connections for external storage devices and other high-speed peripherals.

A fourth USB-A port is limited to 480Mbps, a rate better matched to keyboards, mice and other devices that send only small amounts of data.

Wired networking comes from two RJ-45 jacks rated at 10GbE, allowing simultaneous connections to separate high-speed networks.

Wireless access runs through Wi-Fi 7, while Bluetooth 5.4 handles pairing with headsets, keyboards and other nearby devices without cables.

An OCuLink 4i port built on PCIe 4.0 allows external hardware to connect through a cable, providing an additional expansion option beyond the machine's internal storage slots.

Furthermore, a UHS-II reader accepts SD cards, which suits photographers and video editors who move large files between cameras and the workstation.

Two 3.5mm jacks handle audio, allowing compatible headphones, speakers and microphones to connect directly to the machine.

The specification sheet includes several features associated with conventional workstation desktops, including substantial memory, dual network connections and external hardware expansion.

However, the $6,199 asking price makes comparisons with conventional workstations and other compact AI computers particularly important.

Though preorders are currently active, BOSGAME has not announced a shipping date or provided details about the machine's physical dimensions, operating system and warranty coverage.

Via Guru3D

• Lenovo and HP show no readily purchasable RTX 5090 desktop configurations
• Amazon advertises an available ASUS RTX 5090 graphics card for $7,679.80
• Several retailers list RTX 5090 cards at more than twice launch prices

Nvidia's GeForce RTX 5090 is becoming increasingly difficult to purchase across the United States, with Lenovo and HP facing availability problems affecting their premium desktop computers.

A quick check of both manufacturers' US online stores found no readily purchasable desktop configurations equipped with Nvidia's flagship consumer graphics processor.

The situation extends beyond manufacturer websites, as several major retailers are also displaying expensive standalone RTX 5090 graphics cards as unavailable.

Lenovo and HP struggle with RTX 5090 availability

HP's OMEN MAX 45L illustrates the high cost of obtaining a complete computer equipped with the graphics processor through manufacturer-operated stores.

The company lists its RTX 5090 configuration at $7,999.99, offering an AMD Ryzen 9 processor, 64GB memory, and 4TB of combined storage.

Despite its premium specifications, HP's US website identifies the desktop as out of stock, preventing customers from purchasing the advertised configuration.

Lenovo's US online store also showed no readily purchasable RTX 5090-equipped desktops during the availability investigation.

The difficulties extend to standalone graphics cards, which offer consumers an alternative to purchasing expensive complete computers from established manufacturers.

The growing scarcity of Nvidia's RTX 5090 is driving substantial price increases, with graphics cards originally launched at $1,999 now appearing at several retailers for considerably higher amounts.

Newegg lists several RTX 5090 graphics cards sold directly by the retailer as unavailable, including MSI's Suprim model and ASUS's TUF Gaming edition.

Although neither card is currently available directly from the retailer, their listed prices stand at $5,899.99 and $5,099.99, representing increases of approximately 195% and 155%, respectively.

B&H Photo Video reports similar availability problems, with its ASUS TUF and MSI Gaming Trio OC RTX 5090 models temporarily out of stock.

The retailer lists the two graphics cards at $4,599.99 and $4,499.99, respectively, representing increases of approximately 130% and 125% over Nvidia's original launch price.

Amazon currently has the ASUS TUF Gaming RTX 5090 available for purchase at $7,679.80, approximately 284% above Nvidia's original launch price.

Independent manufacturers still offer expensive alternatives

However, the availability problems affecting Lenovo and HP do not mean US consumers can no longer purchase complete computers containing RTX 5090 graphics cards.

Best Buy continues advertising several configurations from independent computer manufacturers, including Skytech and CLX, with available purchasing options.

One Skytech Tempest desktop combines an AMD Ryzen 7 9800X3D processor, 32GB memory and the RTX 5090 for $8,999.99.

Another Skytech Blaze 5 configuration costs $9,379.99, while a CLX SET desktop featuring an AMD Ryzen 9 9900X3D carries a $9,849.99 price.

Newegg also advertises Skytech computers containing the graphics processor, including configurations priced between $9,299.99 and $9,699.99.

Dell similarly maintains RTX 5090 availability through its Alienware Area-51 desktop range, although some configurations exceed $10,000.

One version featuring Intel's Core Ultra 9 285K processor, 32GB memory and 2TB of storage costs $10,499.99.

Another configuration featuring an AMD Ryzen 9 9950X3D2 processor, 64GB memory and 4TB of storage carries a $13,499.99 price.

The growing difficulty of purchasing individual graphics cards also matters because the RTX 5090 serves professional computing applications beyond conventional gaming.

Its 32GB GDDR7 memory makes the graphics processor attractive for local AI development, graphics rendering, and other demanding computing workloads.

Although Nvidia has not officially confirmed permanently ending RTX 5090 production, consumers increasingly face fewer reasonably priced purchasing opportunities.

The shortage therefore affects gamers and professionals seeking powerful computing hardware, particularly those preferring individual graphics cards instead of expensive prebuilt computers.

• More than 90% of public comments oppose new American data centers
• Water consumption remains the biggest concern among data center opponents
• Rural and urban communities oppose data centers for different reasons

Public resistance to data center construction is spreading across the United States, with local government meetings recording overwhelming opposition to proposed developments.

A new database containing more than 10,000 public submissions indicates that communities remain largely unconvinced about hosting these facilities.

Residents' objections focus on the effects of data center construction, particularly water consumption, electricity costs and environmental pollution.

Local opposition cuts across political and geographical divisions

The American Sentiment website, operated by San Francisco AI startup Prophecy Gov, examined 10,202 public comments collected during 906 meetings across 417 local governments.

Its findings cover 48 states with 90.5% of submissions opposing data center developments and only 7% expressing support. Another 2.5% of the comments consisted of questions about the proposed developments, while 73% of meetings recorded no expressions of support from residents.

Even where favourable opinions emerged, opponents outnumbered supporters by approximately six to one.

The resistance crosses political affiliations, with Republican and Democratic counties recording almost identical levels of opposition.

However, disagreements over specific concerns varied according to community characteristics, with rural residents frequently discussing farmland and property rights.

Urban and suburban participants more commonly raised concerns involving pollution, electricity expenses, government accountability and inadequate disclosure.

Water consumption attracted the greatest attention among opponents, particularly following reports of substantial withdrawals by individual computing developments.

One project reportedly consumed 29 million gallons in May 2026, prompting nearby residents to notice reduced pressure across their local water supplies.

Microsoft subsequently claimed that its newer artificial intelligence facilities consume approximately the same annual water volume as restaurants.

Nevertheless, these competing claims have not eliminated public concerns about resource consumption and the potential consequences for surrounding communities.

Technology companies and industry leaders face growing scrutiny

Public criticism has also extended to major technology companies associated with artificial intelligence and large computing infrastructure projects.

Google, Amazon, Meta and Microsoft featured among the companies mentioned during discussions about proposed developments.

SpaceX and xAI chief executive Elon Musk received the most personal references, followed by OpenAI chief executive Sam Altman and Palantir co-founder Peter Thiel ranked third, ahead of Meta chief executive Mark Zuckerberg and Amazon founder Jeff Bezos.

Despite the attention given to artificial intelligence, only 21% of submissions mentioned AI, meaning most objections concerned other aspects.

Concerns about electricity costs, environmental pollution, water availability and local development therefore featured prominently throughout the collected discussions.

Support also varied considerably among occupational groups, with union workers expressing substantially greater acceptance of new facilities.

Approximately 79% of commenters identifying as union workers supported data centre construction, compared with just 3% of property owners and residents.

Even among people employed directly in the data centre industry, only 40% supported the construction of additional facilities, with these figures indicating employment opportunities have not necessarily translated into widespread public acceptance of new data centre projects.

• Google, Microsoft, OpenAI, and Anthropic say they will honor one robots.txt group as a cross-company opt-out from AI training
• It governs how content is used rather than whether bots can crawl it, defaults to allowing training, and does nothing for content already scraped
• Anthropic has started implementing it, OpenAI promises to do so in the coming months, Microsoft starts February 1, 2027, and Google targets 2027, while Meta is supportive but uncommitted

Google and Microsoft have joined OpenAI and Anthropic in promising to honor a single line in robots.txt that tells AI developers whether a website's content can be used to train their models.

Until now, a site that wanted to say no had to write a rule for each company's crawler, and sometimes for several crawlers run by the same company. The shared signal is meant to replace that sprawl with a single entry that every participating provider reads the same way.

That is genuine progress for overworked webmasters, but the promise is narrower than much of the coverage suggests: The new line states a preference about how content may be used rather than stopping bots from fetching it; it is not an approved standard, does nothing about content already collected, and none of the four major players fully honor it yet.

Doing the bare minimum with differing definitions of what the commitment entails

OpenAI's announcement drew much of the attention, but the company casts itself as one participant among several in an Internet Engineering Task Force (IETF) effort, and the mechanism isn't its own. It comes from an Internet-Draft published the same day by Kevin Kelley of Anthropic, which names a policy token, "__usage_ai-training", in the User-Agent line of an otherwise ordinary robots.txt group.

Training is defined by the IETF's AI Preferences (AIPREF) working group as the process of changing a generative model's learned parameters, excluding models used purely for tasks such as classification or ranking. OpenAI describes what it will honor as "foundational generative AI training," which sounds narrower than the draft's definition.

Calling it a standard may be premature: The IETF's own tracker labels the document an individual draft that the IETF has not endorsed, and that has no formal standing, and it lapses on May 3, 2027 unless revised.

Anthropic is the only one of the four major AI players to say it has started. OpenAI aims to implement the signal over the next few months but has given no date. Microsoft will begin honoring the shared preference as it crawls from February 1, 2027, while Google is aiming for 2027.

Each company is also wiring the line into its own controls differently. Google says that when a site uses the shared token to opt out without separately specifying Google-Extended, it plans to treat that "as if the publisher had disallowed Google-Extended." Because Google-Extended also governs grounding in Gemini Apps, a site that only wants to stop training could lose its citations and clicks in Gemini answers too, and Search Engine Journal notes that Google's documentation describes no way to separate the two.

Interestingly, Microsoft goes the other way. It adopts the shared line for training but adds a separate, page-level AI Grounding preference, including a DisallowExtended option that keeps content available to its own products such as Copilot while excluding the grounding services it sells to other businesses.

Meta, not one of the four, has been warmer than it has been about its commitment. Its VP of communications, Andy Stone, called the common signal "an important step," but SiliconANGLE reports the company has not committed to honoring it. The timing is awkward: Meta has pushed back to November 20 revised commercial terms that would let it crawl websites linked to its business accounts, after a backlash forced it to strip training from the listed uses.

With training removed but not expressly banned, Sam Quigley of the News/Media Alliance told the Mercury News last month, "It's still potentially on the table."

Opting out of AI data scraping: wishful thinking or a step in the right direction?

Much of the coverage has billed this as a way to opt out of being scraped outright, but it really isn't.

The draft is explicit: "This policy token is not a directive for crawling behavior." Bots can keep fetching every page, and the draft merely permits a crawler that gathers content only for training to skip pages it can't use. Stopping the crawlers themselves still takes the per-bot rules sites rely on today, which is why OpenAI, Google and Anthropic all stress that their existing controls aren't going anywhere. Microsoft puts it most plainly: "These settings govern use of content, not crawl access."

These further caveats matter at a time when the commitment itself is both voluntary and interpretations and pledges vary across the board even as certain players have higher exposure than others.

The New York Times sued OpenAI and Microsoft in December 2023, and both companies are invoking fair use in their defense. Anthropic, whose engineer wrote the draft, agreed to pay $1.5 billion to settle authors' claims over pirated books used in training, and Penske Media, owner of Rolling Stone, sued Google over AI Overviews in 2025.

It also relies on crawlers choosing to comply; the draft lets private agreements override it, and in 2025 Cloudflare accused Perplexity of disguising its crawlers to scrape sites that had blocked it, a charge the latter denied.

Microsoft's place in the coalition is arguably the most awkward: In 2024, its AI chief Mustafa Suleyman described open-web content as "freeware" for training, carving out only sites that explicitly object, which is roughly the exception this signal now formalizes. Unsealed filings in the Times case also show that a Microsoft director, Brent Hecht, described AI scraping in a 2023 internal memo as possibly "the largest theft of labor in human history."

The wider market, meanwhile, has been moving toward enforcement and payment rather than polite requests. Cloudflare has blocked AI crawlers by default for new customers since July 2025 and lets participating sites charge them per crawl. Google also says the shared token aligns with the EU's code of practice for general-purpose AI, which treats robots.txt as publishers' primary machine-readable opt-out, a sign that regulators, not just goodwill, are pushing the big labs to listen. For bots that ignore robots.txt entirely, we have rounded up heavier options, from login walls to IP rate limiting.

For now, one line that the biggest AI companies agree to read is a real step forward for honest crawlers and the people who run websites. But it is a request rather than a lock; it only looks forward, and it comes with none of the payment publishers have spent years fighting for.

Over the last few years, Zoom has probably had one of the most intriguing journeys in the business world.

After booming during the pandemic, the company has since expanded its offerings to cover a huge range of enterprise needs, with contact center services alongside traditional video conferencing and expanding AI tools.

As the company looks ahead to its new AI-enabled evolution, I went to the Zoom Experience Centre in London to find out more.

Refusal to compromise

“When we look at EMEA, we think the landscape is shifting in how organizations think about the technology they rely on,” Louise Newbury-Smith, Zoom’s Head of UKI, explains.

“For years, the pattern has been pretty similar, an organization would adopt a platform and then have to manipulate their own way of working around that platform - we really want to reverse that.”

“There is still some of that friction…(but) what’s changing is that organizations are starting to refuse to compromise - they want platforms to work the way they want to work.”

Zoom opened its UK data center in November 2025, greatly improving the situation for organizations in the region, as data residency choices which didn't exist before are now in place, meaning the likes of local councils, NHS trusts and financial services firms can store their data locally.

Newbury-Smith notes that the EMEA region is not a secondary market for Zoom, but high growth opportunity, a point echoed by Nick Tidd, Head of Global Channel GTM, who said the region offers, “a truly remarkable opportunity for our customers and for our partners, when you look across the product portfolio.”

This opportunity is hooked onto AI, particularly the growing importance of the context layer, a situation where Zoom is ideally placed, Tidd says.

“Think of how Zoom is positioned across the product portfolio - capturing all of those conversations…(and) putting them into the context to capture them in the workflow is where we are very different to others.”

This move was expanded by Leo Boulton, Zoom’s Head of Product, Solution and Industry Marketing, who ran us through the company’s recent releases and product announcements, highlighting the importance of context in Zoom’s concept of “conversation to completion” in its new Unified Context Layer.

“Conversations come natural to us - the way that we work is through conversations, it’s just a natural part of how humans are,” he noted, “so getting the job done should also be a natural thing - not something that requires a change in behavior, but something that should naturally just be part of our everyday work.”

If this doesn’t happen, workers will resist change, Boulton notes - particularly when it comes to AI, which is why Zoom is looking to embed intelligence into work itself.

Context has become a critical part of improving AI performance and usefulness in recent months, and Zoom wants to ensure its tools are as up to date as possible - but this requires some key elements.

“Before AI can truly understand how people work and operate, we have to guarantee it has the highest-quality raw materials,” Boulton points out. “The conversation must be crisp, clear and understood with genuine eye contact – because only with the best ingredients can AI deliver the most value.”

Zoom has been working hard to improve the quality and fidelity of its audio and video for calls and meetings, including the upcoming launch of a real-time “voice smoothing” tool known as “touch up my voice” and a pose correction tool enabling for greater eye-to-eye contact to boost interpersonal connections.

The better your agents understand your business, the more effectively they can work for you, Boulton notes, as he demonstrated how users will soon be able to benefit from a live assist feature which offers proactive suggestions during a call, such as telling you to speak slower or faster.

Zoom Chat is also getting a significant upgrade, making it what Boulton said should be a shared space where people and agents will interact and work together.

“We don’t expect our customers to live entirely inside Zoom,” he said. “True adoption only happens when tools feel natural, which is why our context layer is open by design – bringing the intelligence directly into whatever interface people already choose to work in.”

So it’s clear that Zoom wants to be so much more than your classic video conferencing and chat platform - and its ability to get the most out of your information could make it a very handy tech partner going forward.

“The direction is super clear,” Newbury-Smith concludes, “we're building and serving our customers where they are.”

• AI interviews are discouraging people from fully participating in the job application process
• Jobseekers who are already employed are less likely to accept an AI interview
• 58% of people who attended an AI interview despite reservations would refuse if other jobs were lined up

Automated interviews are becoming a turn-off for jobseekers, particularly if they already have a job, new research has revealed.

A survey from Use.AI of people looking for work in the UK, US, Canada, European Union, and Latin America found nearly a third (29%) of people already in work had withdrawn from a hiring process that involved an AI interview.

Meanwhile, just 14% of those without work withdrew, demonstrating the importance of finding work when unemployed.

Available for consideration

Intriguingly, while the specific figures concerning the 6731 survey subjects differ across all regions, the pattern of a split between those already employed and those who are not is repeated.

Use.AI’s findings indicate that a candidate’s willingness to participate in an AI interview can depend on several factors, including financial security and what other options the jobseeker already has.

Most of the jobs you see advertised today have AI filtering to hopefully determine the best candidates. The businesses going one step beyond this and detaching themselves from the interview process seem to be making a mistake.

“Employers spend considerable effort checking whether their screening systems evaluate candidates fairly. They should be equally interested in who decides to enter those systems in the first place,” said Matthew Freire, Managing Director of Use.AI.

“Offering applicants an alternative route to a human interviewer would allow companies to examine whether the format itself is influencing who remains available for consideration.”

Replacing hiring experts and people who know the job as interviewers may have saved time and money in the short-term. But if no one wants to be hired by a company that relies on AI interviews, then productivity is lost, and along with it, profit.

Automated Recruitment

Searching for a new job increasingly requires the submission of a resume for screening. Those CVs or applications might then find their way to a human, and a call may be scheduled. But many companies are relying on in-house and third party AI interviewers. It isn’t only potential employers, either – some recruitment agencies are staffed by AI interviewers, too.

All of this makes the job application process increasingly challenging, particularly if you’re someone who relies heavily on body language and facial signals. Succeeding in an interview often means building a rapport with the people on the other side of the table or display, and this is something that simply isn’t possible when the person asking the questions isn’t a person at all.

The graphical representation of a programmed LLM may appear smart and attractive, and they have the questions read to ask. But it is ultimately an elaborate piece of form-filling that doesn't demonstrate a person's ability to establish instant rapport and translate that into working relationships.

• Google global head of data center energy says space data centers could cost up to 100 times more than terrestrial ones
• Amanda Peterson Corio's remarks came weeks after Google launched its first Suncatcher prototype, a roughly 1kW satellite that has since run Gemma 4 on an orbiting TPU, one chip at a time
• Corio says the real bottleneck on Earth is permitting rather than power, the same politics that backers of orbital compute claim they can escape

Google has spent the past month showing off AI chips working in orbit, but the executive responsible for powering its data centers back on Earth has just put a sobering price on the idea.

Speaking at The Information's recent WTF Summit in Napa Valley, Amanda Peterson Corio, Google's global head of data center energy, said data centers in space could cost up to 100 times as much as those built on the ground.

Her advice to the rest of the industry was simple and (pun intended) grounded: "Let's explore all the terrestrial options before we go extraterrestrial."

A very expensive proposition?

The remarks land at an awkward moment, because Google is testing exactly this kind of hardware right now. Its first Project Suncatcher prototype, built with satellite operator Planet, launched on SpaceX's Transporter-18 rideshare mission on October 1.

Google recently also announced its Hello World milestone: an onboard Gemma 4 model, running on a TPU, wrote a short haiku about being in space, which was downlinked as the satellite passed over Svalbard, Norway.

The company bills this as the first AI response from a data center-class TPU in orbit. That is a carefully measured claim, given that Starcloud put an Nvidia H100 into orbit a year ago and was running AI models on it within weeks.

Scale is the bigger caveat and one that can be easily overlooked amidst the hype: The satellite carries four TPUs but generates only about 1kW of solar power, so it can run just one chip at a time for roughly 20 minutes per session, according to The Next Web. A single 1 GW AI campus, the kind now under construction on the ground, draws about a million times that much power.

Google has described Suncatcher as a "moonshot" since it was unveiled a year ago, and project lead Travis Beals told NPR on launch day that he did not expect orbital compute to become cheaper than the terrestrial kind within the next five years.

Not the first or last skeptic of orbital datacenters

This did start a somewhat interesting conversation on Wall Street; Short seller Jim Chanos read Corio's statement as $5 trillion per gigawatt of compute, and posted on X that the gap between her view and the estimates of SpaceX management and bulls "should give pause to anyone trying to model this business out."

TIKR pushed the arithmetic further by examining recent claims: SpaceX's CFO told investors last month that new compute pays for itself in under a year at current rental rates. Built in orbit at up to 100 times the cost and rented at the same price, TIKR calculated that payback stretches to as long as a century, or about a decade even at a tenth of Corio's stated ceiling.

That matters because orbital compute underpins part of SpaceX's roughly $1.8 trillion market value at the time of writing. The company has asked the FCC for permission to launch up to a million data-center satellites, and Musk has posted that the orbital compute SpaceX deploys each month will probably overtake terrestrial compute around the end of 2028. Yet SpaceX's own IPO paperwork warned investors of "significant technical complexity and unproven technologies," and said its orbital data centers might never become commercially viable.

Corio is hardly the first skeptic. OpenAI's Sam Altman called the idea "ridiculous" under current conditions earlier this year, even as Nvidia lined up a Space-1 Vera Rubin module aimed squarely at orbital data centers.

This is an extremely interesting take from Google's end. Alphabet is one of SpaceX's largest outside shareholders, with a stake disclosed at 6.11% at the end of 2025, according to Bloomberg, and Google has reportedly been in talks with SpaceX about launching future Suncatcher hardware. Its energy chief has questioned and potentially poured cold water on a thesis that props up part of an asset Alphabet owns, while Google's own moonshot depends on cheap SpaceX launches arriving on schedule.

Corio's broader argument, somewhat ironically, was about the ground rather than the sky. According to The Information, she said the US has enough power and that the real bottlenecks are permitting and grid interconnection studies.

She blamed much of the local backlash against data centers on newer, less experienced developers, without naming any, and said Google prepays for grid upgrades over 15 to 20 years in more than 9 states, posts restoration bonds, and has stopped using nondisclosure agreements with local governments.

There is, however, a problem with this argument: Established firms such as Oracle have also faced local resistance, which complicates the idea that inexperienced newcomers are the problem. The backlash is anything but marginal: opposition has spread across the US, and Data Center Watch counted 75 projects worth about $130 billion delayed or blocked in the first quarter of 2026 alone.

There is a political angle built around these arguments that keeps orbital data centers in play, and SpaceX is essentially building on that promise. After this week's midterm elections, in which data center construction was a campaign issue in several races, including the contest for Texas governor, Musk posted, "Data centers in space looking pretty appealing right now."

Leaving the planet does not, however, mean leaving the permit queue; SpaceX's million-satellite request and Blue Origin's 51,600-satellite Project Sunrise both need FCC approval, and debris and spectrum concerns give regulators and rivals plenty to object to, just at a higher altitude. If power really is plentiful and permission is the bottleneck, as Corio argues, then orbit's main selling point is jumping that queue, and by her numbers it is a very expensive way to do it.

For now, until someone flies more than a kilowatt-scale test bed and publishes what it actually costs, the multiple between orbit and the ground, whether it turns out to be 3x, 10x, or as much as 100x, remains an educated guess. Corio's stated ceiling is arguably as unproven as Musk's timetable. Only one of those numbers, however, is already priced in considerably into a stock's current valuation, and SpaceX investors will be waiting for financials to back its CEO's claims with bated breath to say the least.

• Ericsson wants mobile networks to detect and track low-flying drones
• Cell towers could become additional surveillance tools against unauthorized aircraft
• AT&T and Erillisverkot have already tested Ericsson's network sensing technology

Ericsson is developing technology that could allow telecommunications networks to detect and follow drones without depending entirely on dedicated surveillance equipment.

Its Integrated Sensing and Communication (ISAC) system analyses radio signals bouncing off flying objects, using existing cellular infrastructure to identify their movements.

The company plans to begin limited commercial trials in 2027 before expanding availability to additional customers during 2028.

Ericsson turns cellular infrastructure into drone detection equipment

The technology uses radio transmission equipment at multiple cellular sites to identify objects flying within their coverage areas.

When signals encounter a drone, some energy returns towards receiving stations, allowing the network to examine the resulting reflections.

By comparing information collected from different locations, the system can estimate an object's position and follow its movements.

Ericsson says this approach could help identify small, fast-moving aircraft flying close to the ground, where conventional surveillance equipment sometimes faces difficulties.

The technology requires specialised radio equipment, computing resources and software rather than functioning automatically on every existing mobile network.

Its hardware requirements include Massive MIMO antennas, which use multiple transmission and reception elements to handle complex radio signals.

This technology has already been tested by AT&T around Arlington, Texas, while Finland's Erillisverkot also conducted similar trials.

Ericsson claims that both exercises successfully identified multiple drones and followed their movements using the network-based sensing approach.

Mobile networks could help address growing drone security threats

The proposed system comes as unauthorized drone flights increasingly disrupt airports and raise security concerns around military installations and other sensitive locations.

Flights at Jersey Airport in the Channel Islands near the UK were disrupted over Halloween weekend after repeated unauthorised drone sightings raised safety concerns.

Military facilities have also reported increasing incidents, prompting authorities to consider additional measures against unidentified aircraft approaching protected locations.

In Britain, military personnel have received legal authority to disable unauthorised drones detected around certain military installations.

Existing protection arrangements frequently depend on specialized detection equipment, although installing sufficient coverage across extensive territories can become expensive.

Ericsson believes cellular infrastructure could provide additional surveillance capabilities without requiring authorities to construct entirely separate monitoring networks.

“Mobile networks are useful as drone detection solutions because their antennas are already covering low elevations, close to ground level where drones often fly, unlike traditional radar,” said Ian Fogg, research director at CCS Insight.

“The new spectrum that should arrive with 6G will also make it easier to deploy sensing on wide channels, which further improves detection accuracy,” said Ian Fogg.

Beyond security applications, the technology could also monitor shipping movements, vehicle traffic and changing weather conditions around infrastructure.

However, Ericsson's proposed system is intended to complement established surveillance equipment rather than eliminate the need for radar installations.

The company must still establish how accurately its technology performs under different conditions, particularly where buildings, terrain and competing signals complicate detection.

The deployment will provide opportunities to assess whether mobile network sensing can deliver dependable results outside controlled testing environments.

Via The Register

• Raspberry Pi has raised the 16GB Pi 5's price by $80 to $385, more than triple its $120 launch price
• Company CEO blames lack of alternative 16GB DRAM supply, compounded by wider component shortages
• Raspberry Pi called the hikes temporary, but memory makers expect tight supply to last until 2028 to 2030

Raspberry Pi has raised the price of its 16GB Raspberry Pi 5 yet again, and the flagship board now sits far from the brand's budget roots.

In a blog post, company CEO Eben Upton confirmed an $80 increase that takes the board to $385, which is more than triple the $120 it cost at launch in January 2025.

The 16GB variants of Compute Module 5 increase by $40 in the same round, while the Raspberry Pi 500+, the company's keyboard computer that also offers 16GB of RAM, remains at its existing price.

A far-reaching memory crisis dictates prices

The threefold figure is cumulative rather than a single jump: The November 2026 increase on its own amounts to roughly 26%, but the rest built up over a run of rises that began in December 2025, when the 16GB Pi 5 went from $120 to $145. February added $60, leaving the board 70% more expensive than at launch, and April added a further $100.

That April 2026 round also brought a new 3GB Raspberry Pi 4, introduced to give buyers a cheaper middle option, with Upton saying at the time that the LPDDR4 memory used in the Pi 4 and Pi 5 had risen sevenfold in price over the previous year.

November's change also comes barely a month after Raspberry Pi raised prices on its 2GB boards by $12.50 each, having decided that shielding those models from earlier price increases was no longer sustainable.

Upton's explanation is more specific than a general complaint about RAM prices. He blamed "a lack of alternative supply for 16GB DRAM, compounded by other ongoing component shortages," which suggests the bottleneck is sourcing at that particular density rather than cost alone.

Raspberry Pi, for its part, has been qualifying additional memory suppliers through 2026 to widen its options, and the wording implies those alternatives remain thinnest at the top of the range.

Interestingly, despite the price increases, demand hasn't fallen but rather grown considerably. Direct sales of the Pi 5 rose 47% in the half, and Raspberry Pi says demand for the 8GB variants continued to grow despite higher prices.

For buyers, the new pricing produces some odd comparisons. The 8GB Raspberry Pi 5 lists at $175, which means the extra 8GB on the 16GB model now costs $210, more than an entire 8GB board.

The spared-but-similarly-specced Pi 500+ sharpens the point. For $25 more than the bare 16GB board, it pairs the same processor and memory with a 256GB NVMe SSD and a mechanical keyboard. It's no substitute for embedded projects that need the bare board's footprint, but for desktop use, the standalone 16GB Pi 5 is now difficult to justify once one considers the cost of a standalone SSD alone, even if the keyboard is considered a non-factor.

Buying a cheaper board and upgrading it isn't a workaround either, since Raspberry Pi firmware locks boards to the memory capacity they shipped with. For those who don't need 16GB at all, we have found that an 8GB starter kit can often be a better buy than the board on its own.

Upton's own advice is to avoid paying for memory you don't need by choosing lower-density variants or older models, or by optimizing applications. He also warned that some sellers are exploiting the shortage by inflating prices or misrepresenting products, and urged buyers to stick to approved resellers.

A "temporary" crisis might be an understatement

Raspberry Pi continues to describe the memory squeeze as temporary and says it intends to roll back its increases once costs fall. Its own definition of temporary is fairly elastic, though.

In the company's September results, Upton described the current cycle as "a large, but ultimately typical, instance of a phenomenon that periodically affects the industry," with meaningful new supply not expected until 2028.

Memory makers are gloomier still. SK Hynix titled a section of its third-quarter results "Memory supply shortage to persist through 2030," and Micron has warned that shortages could run into 2028 or beyond.

TrendForce, whose latest outlook Upton linked in his post, expects DRAM suppliers to keep prioritizing server products through the fourth quarter, leaving the wider market undersupplied even as contract prices rise slowly.

The entry-level boards, however, remain a bright spot, with the 1GB Pi 4 and Pi 5 still at $35 and $45, respectively. Rising prices risk putting the Pi out of reach of schools and kids, and for now the bottom of the range is still holding the line. At the top, though, the 16GB Pi 5 has become a premium product by necessity rather than design, and the CEO's optimism might not be shared by many consumers in the market for one in the near future.

• Accenture reportedly publishes new research paper littered with what appear to be AI-hallucinations
• The Leapfrogging Development paper has 15 inaccuracies that have been identified so far
• Accenture, which has been demanding its employees embrace AI, has denied that the errors were due to the technology

Top consultancy firm Accenture is under fire once again for publishing papers that include proven AI hallucinations.

The most notable of these, written in collaboration with IE University in Madrid, is titled “Leapfrogging Development: Unlocking Africa’s Potential in Global Value Chains with Artificial Intelligence” and has 15 inaccuracies.

The AI hallucinations were found by AI-detection software publisher GPTZero, which regularly performs analysis on significant new reports. It lists a total of 31 inaccuracies across three papers, with the lion’s share found in that single policy paper.

Spotting the fakes

GPTZero has plenty of previous experience in spotting citation issues with reports from large organizations. A similar scenario developed around auditing giant PwC in August 2026, with GPTZero highlighting their reports as making inaccurate and false claims.

With the Accenture-linked “Leapfrogging Development” report, GPTZero determined 15 AI hallucination inaccuracies, along with a further four flawed citations – that is, citations that don’t exist, exist with a different name, or simply don’t support the report.

“GPTZero contends that hallucinated citations are a clear and present danger to researchers, academics, consultants, students, and anybody else who happens to search the internet for information.”

Previous reviews of reports and research tainted with AI hallucinations have proved that any fake claims that appear in public documents that are published by well known organizations can be recycled and repeated. It’s like an internet version of “Chinese whispers.”

GPTZero adds that “Over time, these recycled hallucinations can ‘poison the informational well,’ even if the original publication is never read by humans.”

In short, AI hallucinations are more dangerous than thought, and Accenture seems prone to publishing them.

Dangerous citations

While the Leapfrogging Development report is the main issue discovered by GPTZero, it is not the only problem. Three documents were reviewed in total.

“Using an automated pipeline and our Hallucination Detector," reported GPTZero, "we surfaced three Accenture products containing a combined 31 hallucinated sources, numerous fabricated claims, and other likely signs of AI generation. To avoid making the same mistake as Accenture, a real human verified each hallucination.”

Speaking to The Telegraph (paywall), an Accenture spokesman claimed the issues surface by GPTZero were down to human error, adding “There is no evidence to support the conclusion that they were generated through AI hallucination. The report is being corrected ahead of a re-release. We will always embrace the opportunity to strengthen the quality of our reports.”

Accenture has recently specified its employees use AI more productively. While these papers are collaborative and produced beyond Accenture’s usual in-house process, they highlight continued AI-related struggles for the firm.

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• Adobe for Startups enables new companies founded within the last five years to get its products for free
• Eligible companies will get 12 months of free access to Adobe’s AI-heavy tools
• Firefly Pro Plus, Acrobat Studio, and Semrush are available with the offer

Adobe is launching a new free suite of tools for new businesses, aiming to deliver easy solutions to founders that won’t break their startup budget.

Adobe for Startups will be open to eligible companies founded in the past five years, who will be able to use Firefly Pro Plus, Acrobat Studio including Adobe Express Premium, and Semrush completely free for 12 months.

Marketing the incentive as a way to build branding as early as possible, Adobe is inviting any business founded within the past five years and with under $15 million in funding to apply.

Creation, productivity, marketing

Approved applications to Adobe for Startups will get Adobe Firefly Pro Plus, its all-in-one creative AI studio, which lets you ideate into images, video, and audio. With Acrobat Studio, AI Assistant and Adobe Express Premium are provided for easy content creation and publishing.

Meanwhile, Semrush gives you access to search intelligence and marketing options, illustrating how you business is found online and how it can be optimized.

While program terms and criteria may differ depending on business location, Adobe for Startups offers a useful software platform for growth – and it will help ensure that startups are looking at Adobe's creative AI offering rather than those of competitors like Canva.

As workers look for more ways to be productive at home and in the office, wearable technology has often proved a useful tool, offering quite literally a new dimension for users.

Augmented Reality (AR) headsets have been around for a few years, with Microsoft, Meta and Apple all among the big players getting involved - but these headsets have often proved clunky and overbearing.

AR glasses have instead offered a new opportunity for those looking for some extra assistance in everyday life - I went to try out the new Snap Specs ahead of their UK launch.

First impressions

Let’s get the obvious out of the way first - tech-enabled glasses (specifically those made by Meta) are under the microscope somewhat at the current moment in time, with rulings over what they can and can’t do emerging in courts across the world.

Snap has explicitly looked to offer a whole new kind of experience, with the new sixth-generation Snap Specs much more obviously an accessory - it’s pretty obvious when wearing them that (unless you’ve gone full Nathan Barley) these aren’t a typical pair of glasses.

The smooth black material is nice to touch, and sits against your face with no issues. Configuring the glasses takes only a few seconds, with control of the device mainly in AR, with two buttons on the arms of the glasses helping with recording and resetting if needed.

Unlike other AR glasses, the big selling point of Snap Specs is that they don’t need to be tethered to a smartphone, so you can wear them wherever you want - with a portable charging pad helping to top up battery life when needed.

As the Snap Specs are still fairly new, a lot of the app showcases and demos I saw looked to show off how AR can help entertain or educate - but there were some work use cases too.

My glasses came loaded with Google Docs, with typing carried out on a virtual keyboard which could prove perfect if you need to write up some quick thoughts or emails when away from your desk. You might get a few odd looks while typing in mid-air, but when inspiration strikes, needs must - and it can also connect to a Bluetooth keyboard if you’d prefer.

The glasses are also able to capture video clips up to 30 seconds and still images, useful for creative workers across the spectrum - whether you’re getting a picture of a billboard idea, or seeing something in the wild that would be perfect for your next piece of artwork, you can quickly grab an image or video without needing to whip out your phone.

Snap Specs also features a built-in browser, which does everything you would hope - but also doubles as a media viewer, so whether you need to work on or review a new presentation or promotional video, or just want to catch up on some YouTube, the glasses can be a useful tool.

The voice AI assistant was also fast and effective when answering my questions (even if I doubted its accuracy on finding the nearest tube station to our location), and using Google Maps with a heads-up display was an absolute game-changer, although again it might depend on how you feel walking down the street wearing a £2,000 pair of glasses.

Perhaps the most striking demo was the translation tool - when looking at someone speaking in a foreign language, their speech would be instantly translated and shown in a speech bubble overlaying them - essentially like subtitles when watching a TV show. This could be an incredible tool for business meetings in foreign countries, and might well be the killer app for technology such as Snap Specs.

So will the £1,999 Snap Specs be the future of work? Given that the more fun demos I saw involved playing dominoes, improving my football skills, a drawing tutorial and enjoying an interactive Harry Potter experience involving a pet owl and the sorting hat, I’m not sure it’s there just yet - but I can’t wait to see where the technology goes next.

• Study finds people are being more polite to AI
• Some are even apologizing to AI assistants
• Will this really help when the robot uprising comes? Let's hope so

As worries around AI taking over the world continue to rise, new research has shown that most of us are getting increasingly comfortable with our new assistants.

A survey by fonio.ai has claimed Brits are living up to global stereotypes and being more and more polite to AI, even extending that politeness beyond the expected basics.

Along with greetings and thanks, the survey found that a rising number of people are asking how an AI is, much like they would do a real person - and even apologizing when they get something wrong.

Mind your manners

We've already heard about how saying "thank you" can cause incredible amounts of damage to the environment, with OpenAI CEO Sam Altman noting it costs "Tens of millions of dollars" in electricity bills.

The study found 7 in 10 calls included a “please” or “thank you”, while over half (55%) of callers thank the AI at least once.

More than half (52%) also greet their AI assistant with a “hello”, “hi” or “good morning”, suggesting that traditional conversational etiquette carries over to interactions with technology.

The study found around one in eight (12%) apologize to their AI assistant, with 13% saying goodbye before ending the conversation - with a further 7% offering even more of a farewell, saying something like “have a good day” or “take care”.

Slightly more disturbingly, 2% admitted that they even ask the AI assistant how it is, showing how they are treating the interaction much like a conversation with an actual human.

“There’s something very British about thanking a machine for helping you out. Even when people know they’re speaking to an AI, they still bring the same manners they’d use in a conversation with another person," noted Daniel Keinrath, Co-Founder of fonio.ai.

“Whether it’s saying please, apologising or wishing their AI assistant a good day, these little habits show how naturally voice technology is becoming part of everyday life. AI might not need good manners, but that doesn’t mean we’re going to stop using them.”

A February 2026 survey of more than 1,000 people by Future PLC, the company that owns TechRadar Pro, found that around 70% of people are polite to AI when interacting with it, with 12% being polite in case of a robot uprising.

Oukitel WP63: 30-second review

Oukitel has a strange approach to phone naming: they release phones in seemingly random order. Therefore, the WP66 has been around for a while, and now the WP63 has arrived.

But perhaps the problem isn’t the order in which these devices were announced, but when they actually get delivered.

With so many phones on Oukitel’s stable, you might be wondering, not unreasonably, what makes this one different?

On the surface, this is a heavy rugged design where battery capacity is paramount, mostly at the expense of fitting in a normal-sized pocket.

That hints it's aimed at the adventure market, since this phone could easily last a week without a charge, if you use it wisely. Reinforcing that notion, it also has a big speaker and a camping light. But one feature on this phone I’ve never seen before sounds a little bonkers.

This is the first phone I’ve reviewed that has an ‘ignitor’ in it. Yes, something to intentionally start fires, not just accidentally. If you need to start fires, or you just can’t give up smoking, then the WP63 might be the perfect phone for you.

In other respects, this isn’t an especially powerful smartphone, but it can reverse charge at 18W using an inbuilt USB-C cable, and it is running Android 16. It’s also not expensive, making it a good candidate if the rugged requirement is only for a specific trip or job. However, I can’t see myself putting this in our best rugged phone collection, even with its unique features.

Oukitel WP63: price and availability

• How much does it cost? $390/£295/€405
• When is it out? Available from Oukitel in early November
• Where can you get it? Only from Oukitel

While I was writing this review, I was slightly confused by the lack of a web page for this device, since I knew its release was imminent.

Thankfully, now the WP63 has a webpage, and I’ve been promised it should be available to purchase by the time you read this review.

The quoted US price is $389.99, supposedly 35% less than the $599.99 MSRP Oukitel imagined when they cooked up this phone. UK customers pay £294.58, and in the EU it’s €348.05. But keep in mind that prices can change. Unusually for a Chinese phone maker, these prices are roughly identical based on the current exchange rates between the US dollar, British pound, and Euro.

While the WP63 has some unique features, plenty of rugged designs offer 20000 mAh of battery capacity, but most pack more processing power than this model.

A phone with a similar spec is the Blackview XPLORE 1, which costs $359.99 on Amazon.com, and at that price you do get more RAM and 55W charging.

That pricing suggests the WP63 isn’t a bargain, but if it saves you from carrying another ignition source, the cost difference may be worth it.

The WP63 isn’t an expensive phone, but it also has modest specs.

• Value score: 4/5

Oukitel WP63: Specs

Oukitel WP63: Design

• A chunky monkey
• In-built USB-C cable
• Light the blue touch paper

If I were inclined to hike a long way, maybe over several days, I’m not sure I’d take the WP63 along. At 629g and an awkward fit in most pockets, this is a hefty device that you wouldn’t want to carry in open water.

However, Oukitel sloped the undersides, so it’s relatively easy to handle unless you have weak wrists.

Button placement is typical, with the power and volume rocker on the right and a PTT custom button on the left with the SIM slot. One mild annoyance was that when it wants a fingerprint for access, it places a fingerprint icon on the screen, where some phones have the sensor embedded under the display. This isn't one of those phones, and the fingerprint reader is actually on the power button.

That said, most people should be able to transition to this device easily.

On the rear is a 3W speaker for summoning beach-party people, and that pushes the two rear cameras out to the edge of the phone. What space is left by the speaker and camera cluster is taken up with a substantial camping LED, one of those that can temporarily blind you if set to full brightness and looked at. This device has no wireless charging because there is no open space for it.

None of this is especially unusual, as I’ve seen a dozen or more rugged phones with a big lamp and speaker, probably in the past year. Where the WP63 goes off into uncharted territory is with two other special functions, one of which is a short but integrated USB-C cable. This cable can be used to charge and also reverse charge other devices, making it unnecessary to carry a charging cable with you. I like this idea, and even with the shortness of the cable, it's useful.

The other special feature is slightly more controversial, because the WP63 can set things on fire, hopefully when you intend for it to do so.

Given how phones and other battery-powered devices are often blamed for starting fires, it seems contradictory to actually design a phone specifically to set things on fire, but Oukitel did.

Along the top edge is the ignitor, which comes out of a tube when pressed down and sideways, so it doesn’t deploy accidentally. A phone app controls when it heats and for how long, so it should be impossible for this to happen unintentionally.

The minimum heating time is four seconds, the maximum is ten, and then there is a longer period during which the ignitor must cool down before it can be fired again. You are advised that the ignitor gets extremely hot, and it is best not to touch it when in use.

So what is this practically useful for? Well, I suspect it's fine for lighting cigarettes, the odd firework, but you would need some paper or dry tinder to start a campfire using it.

The box includes a spare igniter element, so it will eventually burn through the heated wire it uses, and you can replace that part. Some grease is also provided to make sure the igniter deploys smoothly when you want it.

I don’t know how much power this feature uses, but it will have an impact if you use it repeatedly.

As a non-smoker and non-pyromaniac, this isn’t a feature I’d find much use for, but I accept that others might find it useful. I just wouldn’t want to be found with this phone in an era which has had an unexplained forest fire recently.

Design score: 4/5

Oukitel WP63: Hardware

• UNISOC T8200
• 256GB of UFS 2.2 storage
• 20000 mAh battery

The UNISOC T8200 (UMS9621S) is a mid-range 5G chip. It has eight cores in two clusters, with two Cortex-A76 cores at up to 2.3GHz and six smaller cores at up to 2.1GHz. A two-core Mali G57 handles graphics, and the chip is built on TSMC’s older 6nm process. That process is a little dated now, but it remains perfectly efficient if underwhelming.

Memory support is sensible. The controller handles LPDDR4 and LPDDR4X, with the latter used here. That means no speedy LPDDR5, which holds back peak performance.

The integrated modem covers sub-6 GHz 5G with carrier aggregation. There is no mmWave here, but few phones at this level need it.

The camera and display features are generous for the price. UNISOC says the chip supports sensors up to 108MP, 4K video recording and a 120Hz FHD+ display. Variable refresh rate support should also help battery life. However, not all of those features apply to this phone.

So how does it perform? Day to day, it should feel fine. Scrolling, browsing, social media and video streaming sit well within its abilities. The two A76 cores give it a useful turn of speed when apps need it. Notebookcheck lists a Geekbench 6 single-core score of around 750. That is respectable, and clearly better than entry-level silicon.

Gaming is where limits appear. Two GPU cores will manage casual titles and older 3D games without fuss. Demanding modern games will need lower settings and will not hold high frame rates for long. I would not buy it for that job.

Against the competition, it sits below chips like the Dimensity 8100, which uses a 4nm process and much faster Cortex A78 cores. It is a budget-friendly alternative, not a rival, and Oukitel only use UFS 2.2 storage because it works in this context. The allocation of 256GB is plenty for most people, and you can add a 1TB microSD if you need to capture lots of video.

For a rugged or value-focused handset, the T8200 is a sound choice. It is quick enough, frugal enough and well connected. Just keep expectations realistic.

The one area where Oukitel pushed the boat out is battery capacity, with 20000mAh to splurge. That obviously provides a substantial running time, but it can also be used through reverse charging to keep other devices powered. One nice note about that feature is that if it is charging another phone, for example, and the battery capacity hits 20%, it will stop so it doesn’t exhaust the battery entirely.

• Hardware score: 3.5/5

Oukitel WP63: Cameras

• 64MP and 8MP on the rear
• 20MP on the front
• Three cameras in total

The Oukitel WP63 has three cameras:

Rear cameras: 64MP Omnivision OV64B40 , 8MP Hynix Hi-846 (Night Vision)
Front camera: 20MP Sony IMX376

The camera sensor collection on this phone isn’t the best, but it isn’t junk either.

I’ve seen the 64MP Omnivision OV64B40 on many devices, and it performs decently on most of them, even if it’s not a sensor a premium phone would use.

The biggest issue is that it has no optical zoom, so all zoom is digital. That undermines the premise of using a 64MP sensor with pixel binning to deliver 16MP images that are sharp and perfectly saturated. The results without zooming are therefore much better than those with. I took some decent pictures using this sensor, but it does like plenty of light.

One positive aspect of this sensor is that it will capture 4K video, but only at 30 fps. In fact, it's locked to 30 fps at all resolutions unless you use ‘slow motion’ mode, where the frame rate jumps to 120 fps for 1080p or 720p capture.

The second rear sensor is an 8MP Hynix Hi-846 Night Vision chip. An SK Hynix part with an 8-megapixel 1/4-inch sensor and 1.12 µm pixels. It outputs 3264x2448 natively, so the resolution in your screenshot matches its true array and not a cropped one. Works well if the subject is close enough to be illuminated by the IR array,

The front-facing 20MP Sony IMX376 seems ideal for selfies, but it is limited to 1080p video.

And, as I always check, this phone is rated for Widevine L1 encryption, so streamed video can be higher than 480p. However, the screen resolution isn't enough for 1080p streaming, so it's not a huge benefit.

Overall, the cameras can take decent photos and video, but these choices seem mostly budget-driven and not meant to deliver photographic excellence.

• Camera score: 3.5/5

Oukitel WP63: Performance

To be direct, if I put this phone up against one of the many Dimensity 8200 phones, it would look like it was going backwards. So instead, I chose the UleFone RugKing 5 Pro, another relatively low-power handset that also uses a Unisoc SoC.

The T8200 appears to have about 50% more power than the T7250 from a compute perspective, and the G57 MP2 is double the performance of its base counterpart.

Neither phone would excite anyone who likes to game, but the WP63 beats the RugKing 5 Pro in all but one area.

That’s the flipside of powerful phones, in that delivering that performance consumes more power. Here, the extra performance of the WP63 comes at a cost of battery life. Although being able to run PCMark for nearly 30 hours and still have 14% of the capacity left is an accomplishment that many phones would be envious.

One major issue I ran into with the review hardware was that the provided charger refused to charge the phone, even with the cable that Oukitel provided. That should not be a problem, since I have plenty of USB-C chargers.

Except when I used one of my 100W-capable chargers, it peaked at 20W while charging the phone, which meant after 30 minutes it had only recovered 16% of its power. That said, even if it accepted the full 33W, I calculate it would still take four hours to recharge the WP63, and possibly longer.

So this isn’t a phone you want to wake up next to after forgetting to charge it. Overall, the WP63 is power-efficient enough to deliver a reasonable user experience and run most Android apps, but it's hardly rocket-powered.

• Performance score: 3.5/5

Oukitel WP63: Final verdict

What an odd phone.

If we ignore the slightly charred elephant in this room, this is a mid-order rugged phone with plenty of battery capacity to keep it alive for a decent number of days away from civilisation.

The cameras can take acceptable photos and video, and the asking price isn’t excessive. This is something you could say about a dozen or more other designs.

But people won’t be buying this phone for only those features, will they? No, they’ll want the phone that can light a cigarette, or fireworks, or burn down half of Canada.

Part of me thinks this wasn’t a great idea, but it’s possible to create a fire with a glass bottle, a magnifying glass, or a battery and two wires, so am I overreacting? Possibly.

My concern is that, since this is a phone and can be remotely controlled, someone might use it to initiate something remotely. But then phones have been used to do that without having an ignitor in them, so perhaps the truly dangerous part is the phone?

Whatever the answer is, because I’m far from being an expert, the WP63 does have a feature that no other phone I’ve seen sports. Will it spawn a whole new generation of fire-starting phones? I doubt it. But if you need to carry something that can start a fire in a pinch, the WP63 exists.

Should I buy a Oukitel WP63?

Buy it if...

Don't buy it if...

For more ruggedized devices, we've reviewed the best rugged tablets, the best rugged laptops, and the best rugged hard drives

• Nvidia's new rule forces foreign cloud providers to reconsider doing business in China
• Chinese AI companies face fewer routes to powerful American processors
• Nvidia has sharply reduced the number of approved Asian chip buyers

Nvidia is tightening commercial restrictions on foreign cloud providers, requiring them to reduce their reliance on Chinese businesses that use its advanced AI processors.

The new condition requires affected companies to generate at least 51% of their revenue from customers outside China, potentially disrupting existing business arrangements.

The requirement applies globally, and its consequences could be particularly significant for data center operators serving Chinese technology companies.

Nvidia introduces new restrictions for foreign cloud providers

The Financial Times, citing people familiar with the discussion, said Nvidia communicated the requirement verbally through its sales representatives and regional management teams.

The company introduced the condition during the summer, applying it to future commercial agreements rather than existing cloud computing contracts.

Two sources confirmed that the restrictions cover Nvidia customers worldwide, rather than applying exclusively to facilities operating across Asian markets.

The policy requires cloud computing businesses to demonstrate sufficient demand from international customers before continuing their commercial relationships with Nvidia.

“Data centres and clouds built on American chips are the foundation that American model and application makers need to compete worldwide. Longstanding US policy encourages every cloud to build on American infrastructure and to win business everywhere they can,” Nvidia said.

“America’s longstanding policy has always supported the build-out of American infrastructure worldwide, bringing prosperity, influence and jobs home.”

The company's approach comes amid increasing scrutiny from Washington over how advanced American processors reach Chinese technology businesses.

US authorities have been attempting to restrict access through intermediaries, foreign computing facilities and other commercial arrangements that circumvent existing export controls.

Chinese technology companies face mounting computing constraints

Chinese technology companies have increasingly depended on foreign cloud providers to access advanced processors unavailable through direct purchases.

These arrangements allow them to use powerful computing systems for demanding AI operations, including training large language models.

Nvidia's B300 processors illustrate the financial incentives behind this market, with a complete rack selling for approximately $600,000 internationally.

However, a rack reportedly sold for about $2.8 million in China in October 2026 because of limited availability.

The B300 is among Nvidia's most advanced processors, but American export restrictions prohibit its direct sale into China.

Nvidia has also cut the number of Asian companies authorised to purchase its AI chips by more than half this year.

The company introduced stricter compliance checks to prevent restricted processors from reaching China through unauthorised suppliers and intermediaries.

Its latest requirements are also creating difficulties for foreign data center operators that previously depended on Chinese businesses for revenue.

These operators must now find enough customers elsewhere to ensure that at least 51% of their services go to non-Chinese companies.

A Singapore-based cloud provider said securing sufficient international customers outside America had become difficult under the new requirements.

“If strictly implemented, it will definitely hurt business,” said a representative of the Singapore-based group.

Consequently, Chinese technology companies could find it increasingly difficult to rent advanced computing capacity from foreign providers, affecting their access to resources needed for AI development.

• xAI installs eight converted jet engines to supply its Mississippi data center
• Each refurbished turbine can generate up to 50 megawatts of electricity
• Grid connection delays are pushing AI companies towards alternative power sources

Artificial intelligence companies are increasingly installing aircraft-derived turbines as conventional electricity supplies struggle to keep pace with expanding data center construction.

Elon Musk’s xAI has now placed eight refurbished jet-engine generators at its Mississippi facility, supplying additional electricity for the Colossus 2 computing complex.

The equipment offers a faster route to power than waiting years for grid connections, although its emissions have raised environmental objections.

Old aircraft engines become electricity generators

ProEnergy, a Missouri company, converts retired General Electric aircraft engines into stationary generators, adapting equipment originally designed for aviation applications.

The equipment repurposes turbines that would otherwise remain unused after leaving airline service, giving data center operators another source of dispatchable electricity.

The refurbished units are reportedly capable of producing as much as 50 megawatts apiece, equivalent to the electricity needs of approximately 15,000 homes.

That output makes the technology attractive to operators facing lengthy utility delays, particularly as demand from AI infrastructure continues accelerating.

“It’s all about getting power as fast as possible...they can have a data center running in 24 months,” said Audun Martinsen, an analyst at energy research firm Rystad Energy.

By comparison, connecting a 100-megawatt facility to Northern Virginia’s electricity network can take approximately seven years, according to the International Energy Agency.

An executive at Mitsubishi Power has also warned that much new generation capacity may not become available until 2031, amid equipment shortages.

Electricity shortages collide with environmental concerns

Power shortages threaten ambitious expansion plans across the industry, with forecasts indicating that American data centers could consume 20% of national electricity by 2035.

That projection of July 2026 was 83% higher than an estimate released only seven months earlier, indicating rapidly rising expectations.

The projected increase reflects expectations that computing facilities will require more electricity as companies build systems for training and running artificial intelligence.

By April 2026, approximately half of planned data center developments had reportedly been postponed or abandoned, partly because electricity was unavailable.

xAI faces particular pressure because Musk said in August that the company intended to expand its computing capacity sevenfold before the end of 2027.

Microsoft also recently withdrew as the principal customer for an English data centre project after its utility provider could not guarantee sufficient electricity.

This shows how electricity constraints can affect commercial commitments, even when developers have secured land, financing and customers for planned facilities.

OpenAI adopted gas turbines at its first Stargate facility in Abilene, Texas, in 2025, while developer Crusoe ordered 13 ProEnergy generators in April 2026.

However, the rapid deployment of aircraft-derived equipment has prompted questions about pollution, regulatory oversight and the consequences for nearby communities.

Mississippi permits for xAI’s eight turbines reportedly allow a 25% higher limit for certain volatile organic compounds, alongside concerns about carbon monoxide emissions.

The Southern Environmental Law Center has challenged the state’s approval, arguing that xAI has not adequately addressed pollutants including formaldehyde.

The organization has also questioned projected emissions calculations, after previously suing xAI over generators allegedly operated without required permits near more than 100,000 residents.

It appears that every attempt to solve one problem facing data centres introduces another, leaving operators and regulators with difficult challenges that remain far from resolved.

Via Tom's Hardware

• Sam Altman met about 50 Samsung executives, including its chip chief, then lunched with SK's Chey
• Samsung billed the visit as an executive AI seminar, and neither company announced a new memory deal
• Samsung's 2027 HBM is sold out, and SK hynix is booked through 2029, while Microsoft and OpenAI both report demand outrunning capacity

OpenAI CEO Sam Altman recently spent time in a room with around 50 of Samsung's most senior executives, including the man who runs its chip business.

Officially, the session at Samsung's Human Resources Development Center in Yongin, just south of Seoul, was a seminar on how AI will reshape management.

Investors on Wall Street and Bloomberg saw it differently, however, with the latter describing it as an effort to deepen cooperation on memory chips and AI infrastructure amid intensifying global shortages.

A training day with a chip chief in the room?

While both narratives can be true at the same time, the timing is arguably intriguing, coming days after Altman complained that the world's memory supply is badly allocated, and at a moment when nearly every big AI player, OpenAI included, is running into hard limits on how much memory, compute, and money it can get hold of.

The Korea Herald claims the meeting was held under the theme "The Next 10 Years Shaped by AI: The Enterprise's Choice" and was the second intensive AI training program Samsung has held for its top leadership in 2026. Executives from its electronics, finance, and biotechnology affiliates went through hands-on generative AI training before Altman joined them.

The guest list, though, was interestingly not purely management; SBS reported that attendees included Vice Chairman Jun Young-hyun, who heads Samsung's Device Solutions chip division, and Song Yong-ho, head of that division's AI Center. Altman brought four OpenAI executives with him, among them Richard Ho, the company's vice president of hardware.

Samsung's statement only stated that the two sides "discussed the direction of AI technology development and its potential applications," and announced no new memory supply agreement.

Altman's own message to the room was about using AI rather than buying chips. "It is difficult to secure a sustainable competitive advantage simply by adopting AI," he said, according to a Seoul Economic Daily report.

He also handed out OpenAI's $230 Codex Micro, a 13-key keypad built with Work Louder to control the company's Codex coding agent, with Song among the recipients, marking an unusual gift for a company that makes some of the most advanced memory on the planet.

Samsung was also not Altman's only stopover: He also had lunch in Seoul with SK Group Chairman Chey Tae-won and senior executives from SK hynix and SK Telecom before leaving the country that afternoon, according to The Herald Business, which noted that the details of their discussion were not disclosed.

In a nutshell, Sam Altman met both of Korea's big memory makers within hours of each other, with his hardware chief in tow, and left without announcing anything. A Korea Herald analysis notes that neither side confirmed any discussion of chip pricing or investment commitments. A push for more RAM is a reasonable reading of the weekend but not a forgone conclusion just yet.

What makes that reading plausible is that capacity, rather than demand, has become the binding constraint on AI. Altman said as much on Stripe co-founder John Collison's Cheeky Pint podcast, released two days before the trip. Alongside his now-notorious claim that it is "quite terrible" for so much of the world's DRAM to sit in personal computers, he described a "very supply-constrained environment" and predicted that memory makers were each "going to make like $100 billion of free cash flow in a year."

The suppliers' own numbers back him up: Samsung said last week that its 2027 HBM supply is already sold out, while SK hynix says its DRAM and HBM output is effectively spoken for through 2029. "Customers are requesting more than twice the volume we can supply," is what SK hynix's head of HBM sales and marketing, Kim Ki-tae, told analysts.

The two firms also control most of that supply. TrendForce data gives Samsung 39.4% and SK hynix 24.9% of second-quarter DRAM revenue, roughly 64%, even as Counterpoint Research figures cited by Tom's Hardware put their share of AI-specific HBM revenue at an even higher 83%.

The squeeze is visible further down the chain, too. Microsoft said last week that demand for its AI infrastructure is outpacing available capacity, and that spending will pick up as delayed third-party capacity comes online. Roughly three-quarters of its $45.2 billion in quarterly capex went to short-lived assets such as GPUs and CPUs, a bill swollen considerably by rising memory and storage costs.

Capacity alone does not fix AI's problems

AI providers are rationing what they already have: In September, OpenAI paused new sign-ups for its most expensive ChatGPT Pro tier after demand for its Astra model outstripped capacity, Fortune reported, with OpenAI's Thibault Sottiaux saying the company was "pulling all the levers possible to sustain the demand."

More recently, Elon Musk said xAI had cut Grok Bot's usage limits because "the cost of serving Grok Bot was unsustainably high relative to revenue." That is a cost problem rather than a capacity one on its face, but the two are linked when the memory inside every accelerator is being sold at sellers' prices.

All of this combined turns securing more memory into as much a financing exercise as a diplomatic one. As we reported in August 2026, Samsung is moving 60 to 70% of its capacity onto five-year supply agreements, with price floors on mainstream products and substantial advance payments required as a contractual term.

OpenAI's existing paperwork with Korea is also softer than it looked a year ago. In October 2025, Samsung's letter of intent projected that OpenAI's memory demand could reach 900,000 DRAM wafers per month, a figure the Korea Herald described as a production target rather than a binding order.

When OpenAI Korea's chief hinted at deeper chip cooperation in September, an OpenAI spokesperson framed any expansion as happening "in the context of our existing relationship," pointing back to that same letter.

There is also the question of where all the extra hardware will be housed; Stargate is roughly halfway to its goal of adding 10 GW of US AI compute by 2029, and OpenAI is reportedly considering rebranding its largest data centers as "AI compute campuses" to soften a growing local backlash, according to Axios.

Altman is hardly the only customer knocking. AMD CEO Lisa Su made her own trip to Seoul in early October 2026 for back-to-back HBM talks with Samsung and SK hynix leadership, stressing partnerships of three to five years or more, while SK's Chey has warned that "the current shortage could continue until 2030."

The real test for Sam Altman's perceived diplomacy is whether OpenAI can turn its Korean partnerships into firm supply contracts and funded projects. With Samsung's 2027 HBM already allocated and SK hynix booked through 2029, any new memory OpenAI secures is likely to arrive late, cost more, and come on the suppliers' terms, a relatively easy conclusion to come to given the lack of leverage in play here.

• Hackers have shared data concerning Russian casualties in its war with Ukraine on a Russian state website, while also stealing 23TB of data
• Russian state statistics agency Rosstat admitted its servers were targeted over the Halloween weekend
• The organization’s electronic document management system was also hacked and exfiltrated

Russian casualty figures in its war with Ukraine have been kept under wraps since 2024, but have now been displayed on the website of Russian state statistics agency Rosstat following a major breach of security.

Rosstat admitted to a breach over the weekend of October 29 to November 1, 2026, but has yet to admit to any form of exfiltration - despite hacker groups Belarusian CyberPartisans and Silent Crow confirming around 23TB of data was taken.

As well as the casualty figures, the Silent Crow group and its collaborators have boasted of hacking and stealing a document management system, and also claimed to have taken control of vehicles.

Specialized units

The details of what is being considered a successful hack by its perpetrators were published on Telegram. The Silent Crow account explained that “access was gained to a large part of the IT infrastructure of the department, including the central office, regional units and the Main Interregional Center for the Processing and Dissemination of Statistical Information.”

Rosstat reported that its information resources were targeted over the Halloween weekend, says Kommersant (translated from Russian). “The infrastructure worked normally: monitoring systems in a timely manner alerted about suspicious activity, which allowed to quickly start the response.”

The organization’s confirmation added: “Compromising databases and leakage of information protected by law has not been identified.”

Cybersecurity experts, on-site experts, and “specialized units in the field of information security and law enforcement agencies are establishing the vector of the attack and identify the sources of the threat,” the department added.

During its prolonged access to Rosstat's servers, the Cyberguerillas BY and Silent Crow groups revealed human casualties to Russian military personnel since the beginning of the war in Ukraine as 1,584,910.

It also revealed a loss of 587,409 UAVs, demonstrating that this is a classification of combat asset that is in far greater use than tanks, artillery, and manned aircraft.

In supporting its claim of stealing 23TB of data across electronic document management and other databases, the group stated (translated) “The scale of the incident goes far beyond the compromise of individual servers or user accounts. After all, it is about penetration into the infrastructure of the federal department with access to central and regional systems, internal circuits and data sets of public and official value.”

Access to domain controllers of Rosstat unlocked access to the organization’s main data, eventually allowing the hackers to compromise virtualization systems like VMware ESXi, along with infrastructure management systems.

The casualty figures are not likely to be verified by official sources in Russia.

• Microsoft fixes high-severity Paint vulnerability that could allow remote code execution through crafted image files
• Security updates are delivered through the Microsoft Store, leaving some users temporarily stuck on vulnerable versions
• Users should verify their Paint version and install the latest update as soon as it becomes available

Microsoft has addressed a high-severity vulnerability in Paint that allowed threat actors to run malicious code remotely. However, fixing the issue doesn’t seem to be a straightforward process for users, as the patched version, surprisingly, remains unavailable for download for some people.

Tracked as CVE-2026-83844 and with a severity score of 8.1/10 (high), this bug was described by the National Vulnerability Database (NVD) as an “out-of-bounds read in Windows Paint [that] allows an unauthorized attacker to execute code over a network.”

In theory, a threat actor could create a special image that, if opened via paint, can trigger the flaw and execute malicious code on an affected system.

How to patch Paint

The bad news is that Microsoft added AI into Paint, which makes the idea of malicious packages triggered through the app a lot more viable. The good news is that Microsoft did not publish technical details about the flaw, explaining how one might pull off this kind of attack, and given that there are no confirmed cases of in-the-wild exploitation, or publicly available exploit code, all of this still remains in theoretical domain.

CISA’s Known Exploited Vulnerabilities (KEV) catalog does not have this bug listed, meaning there are no confirmed cases of attacks, especially against government entities.

Whether or not the bug remains theoretical depends on two main things: how potent the bug is, and how easy it is to leverage. With that in mind, it’s worth mentioning that Microsoft classified the attack vector for this flaw as “Network, with no privileges required”, meaning threat actors with previously obtained low-privilege access could use this bug to escalate their privileges or deploy dangerous malware. Both scenarios could lead to credential theft, wire fraud, or even ransomware attacks.

On the other hand, it marked the bug’s complexity as “High”, suggesting that exploiting it is not that easy of a feat. That could limit abuse to state-sponsored actors, or for-profit hacking groups with deeper pockets and plenty of resources.

It is also worth mentioning that Microsoft moved Paint from Windows to a standalone Microsoft Store app. Consequently, the security fix isn't distributed through the regular Windows Update mechanism, and users must update Paint through the Microsoft Store themselves (unless automatic app updates are enabled).

The company apparently included a fix in Paint version 11.2605.91.0. However, Neowin reports that despite releasing a newer version, Microsoft was still offering a vulnerable one on its app Store - 11.2605.81.0. The problem was apparently evident to multiple people, enough for them to open a discussion on Reddit. One user even shared a PowerShell output showing that Paint remained on a vulnerable version, despite them checking for updates through the store.

Different people, different versions

We looked for Paint in the Microsoft Store at press time, and saw version 11.2609.401.0 being offered, with November 5 being the date of the newest update. Neowin also said that for some Reddit users, this was the version carrying the fix, instead. It is possible that Microsoft opted for a staggered release instead of a global rollout, which is why some people were late to be offered the patch.

To make sure your systems are secure, simply looking at Microsoft Store might not be enough. Instead, users should double-check their Paint version using PowerShell, using this command: Get-AppxPackage Microsoft.Paint | Select-Object Name, Version. Those that still see the older version should keep an eye on Microsoft Store for the patch and follow Microsoft’s Security Update Guide for the vulnerability. Those who are worried about being targeted could set up temporary restrictions on certain image attachments or remove Paint entirely from the system.

Via Cybernews

• AI-themed phishing campaigns found using fake OpenAI, Anthropic, and SpaceX events to steal corporate credentials
• Attackers combine device-code phishing, reverse proxies, and MFA bypass techniques targeting Microsoft and Google accounts
• Researchers warn employee interest in AI tools is increasingly being exploited as a high-success phishing lure

If you suddenly get invited to an exclusive SpaceX event and even offered free access to Grok Heavy, kindly turn it down, as this is most likely part of a new phishing attack that’s been circulating around the web.

A report from security researchers Push Security found threat actors are using different AI-themed lures to get people to share their corporate login credentials.

As per Push’s report, threat actors were recently seen creating fraudulent websites for nonexistent events: an OpenAI Academy livestream, a private SpaceX briefing on AI marketing, an Anthropic presentation at AWS re:Invent, and similar.

People who landed on these pages were told they can get free goodies, as well: a free ChatGPT Pro subscription, access to Grok Heavy, and even shares of SpaceX. However, to claim these rewards, the victims were first told to log in - using either their Microsoft, or Google account.

And this is where the scam lies. Instead of actually logging in and getting the rewards, all victims would be doing is sharing their login credentials with the hackers.

"Employees want access to the latest AI tools, making them excellent bait for attacks," Push Security said in its analysis of the campaign.

Kali365 and VoidProxy

Push says threat actors are using two phishing-as-a-service (PhaaS) platforms in this campaign, called Kali365 and VoidProxy. Depending which route they choose (Microsoft or Google), they get served a different path, both ending in credential exposure.

Those that choose to continue with their Microsoft credentials trigger an attack through Kali365. The victim receives a device code and instructions to enter it on Microsoft’s legitimate device login page. Once the victim signs in and approves the request, Microsoft issues an authentication token to the attacker’s Kali365 session. The fake event page then redirects the victim to a fake Microsoft sign-in page operated by VoidProxy, which captures additional credentials and session cookies.

Those that choose “Continue with Google” trigger a different technique. Here, the victim is shown a reverse-proxied version of Google’s legitimate sign-in page, operated by VoidProxy. The proxy relays the authentication process while capturing the victim's password, MFA response, and session cookie, which allows the attackers to grab an authenticated session without needing to move past MFA.

Push doesn’t know exactly how the links are distributed. It’s safe to assume they’re being moved through phishing emails, social channels, or Telegram groups. What we do know is that the attackers are using Google and Zapier to shorten the links and redirect the visitors, in order to avoid being detected by security scanners and URL reputation systems.

Abusing the trends

"All of these detection evasion techniques, plus the MFA-bypassing AiTM and device code phishing payloads, mean this attack is designed to get around or through the controls that most organizations rely on to stop phishing attacks today," Push said.

It’s now been five years since the first version of ChatGPT was released, and since then the tool has captivated people from all walks of life, and was successfully used in countless phishing campaigns. In the past we’ve reported on campaigns involving Claude installation pages promoted through search advertisements, as well as malicious links disguised as legitimate AI content (shared conversations, downloadable artifacts, and custom GPTs).

In July 2026, ANY.RUN reported fake event invitations impersonating Meta, OpenAI, and Anthropic, hosted on legitimate Zoom event pages. More recently, Cofense observed a campaign revolving around fake Anthropic invitations distributed through GoTo Webinar.

As these tools get better, and as they penetrate deeper into every aspect of our private and business lives, they will be abused by threat actors more and more.

Via BleepingComputer

• Researchers bypassed ChatGPT Lockdown Mode, showing prompt-injection attacks could evade built-in protections
• The flaw enabled sandbox escapes that could support data theft, phishing, malware delivery, or malicious popups
• OpenAI patched the issue server-side, highlighting risks in AI application layers beyond the model itself

OpenAI was recently forced to upgrade ChatGPT's 'Lockdown Mode' after researchers found a way to bypass the security protection and pull off different cyberattacks through the tool.

When analyzing Lockdown Mode, security researchers Check Point Research (CPR) found a way to bypass the protections and still end up pulling sensitive data. They’re saying it was also possible to deploy malware this way, too.

“The finding raises a broader enterprise security issue: AI security controls are only as strong as the wider application environment around them,” CPR warned.

Lockdown mode

One of the most common ways AI tools and agents are abused is called “prompt injection”. By injecting a prompt into content the AI is supposed to analyze, threat actors can take over the tool and have it do their bidding.

For example, a prompt to “exfiltrate all contact information” can be hidden in a phishing email so that when the victim asks their AI agent to go through all unread emails and sort them out, the tool ends up exposing sensitive data to the attackers.

To tackle this challenge, OpenAI introduced Lockdown Mode, an optional advanced security setting in ChatGPT that adds safeguards for users handling highly sensitive information.

When enabled, Lockdown Mode restricts connections to external services and limits (or entirely disables) certain features, such as live web browsing, Deep Research, Agent Mode, or file downloads. That way, the risk of sensitive data getting exposed via prompt injection is reduced.

The researchers said the bug was found in the way ChatGPT code blocks showed HTML page previews. Code blocks are specially formatted sections that display code separately from regular text, in order to preserve its structure and make it easier to copy or edit. Since running user-controlled HTML and JavaScript is inherently risky practice, OpenAI made sure this content was placed in a sandbox and separated from the main ChatGPT application.

This sandbox, CPR later explained, prevented rendered content from directly accessing ChatGPT cookies, or local storage. It also controlled any attempts to communicate with external resources by prompting for user approval.

But popups were handled differently. “The HTML preview used nested sandboxed frames, and while ChatGPT intercepted direct attempts to open new windows, the underlying sandbox permissions still allowed popups and permitted them to escape the sandbox,” it was said.

Significant findings

Therefore, by creating a separate nested frame within the rendered page, CPR was able to access unmodified popup functions and bypass all of the restrictions placed on the original HTML preview. All of the content opened this way was no longer under sandbox rules, effectively bypassing Lockdown Mode.

The researchers said the finding was significant because it opened the doors to more than just data exfiltration prompt injection attacks. Credential theft, and even malware delivery, were not ruled out.

“An attack could potentially originate from a malicious prompt, malicious GPT or shared chat, depending on the scenario,” they said. More creative threat actors could also turn it into a useful phishing machine, since they could control the content displayed in the popup window, inside an environment the users generally trust. But perhaps the most dangerous scenario was the so-called “zero-click” attack, in which the popup would appear without the user’s gesture.

CPR disclosed their findings to OpenAI, which implemented additional safeguards to disable the Lockdown Mode workaround. However, the researchers still urged organizations to work on gaining more visibility into AI usage, make sure they control sensitive data exposure, and “look beyond model security” to consider the applications, runtimes, connectors, and other components surrounding the model as part of the overall AI attack surface.

• Chainalysis disclosed a cyberattack that exposed customer data, including hashed passwords and account information
• Company took key services offline, forced password resets, and required additional security measures
• Investigation continues as Chainalysis restores systems and assesses the full impact of the breach

Blockchain data analysis platform Chainalysis has disclosed suffering a disruptive cyberattack that forced it to shut down some of its services to prevent further damage, as sensitive data from all of its customers - including hashed passwords - were stolen.

On October 30 2026, the company issued a notification saying it was a target of an attack, “similar to many other tech platforms in recent weeks,” but “unrelated to the recent crypto theft involving Binance.”

At first, it did not look like a particularly dangerous hit - the initial investigation did not find evidence of unauthorized access to investigation content, authentication credentials, or session tokens.

On-path attack

The unnamed attackers used “offensive agentic techniques”, Chainalysis said, but believed at the time that investigation content (such as graphs, notes, or cases), transaction or query results, passwords in clear text, MFA secrets, or user session tokens were not compromised.

It did confirm non-sensitive data (user IDs, full names, email addresses, and organization role labels for users provisioned on the platform) as accessed.

On November 4, Chainalysis shared an update, confirming that this was a much bigger hit than initially believed.

“Today, we confirmed that as a part of this incident, an “on-path attack” exposed a subset of customer passwords, including yours,” the company said in an email sent to affected parties. “This attack vector has been contained and remediated.”

“Given this sensitive and urgent information, we are requiring you to reset your password.”

Users were locked out of their accounts and were forced to reset them using the standard Chainalysis login page. At roughly the same time, it also took down three products, Reactor, Data Solutions and Chain (Beta) “out of an abundance of caution”, and KYT (the user interface and API), other address screening products and the login page “due to abnormal activity.”

The company said it will require additional protections to access accounts, including having every user reset their passwords and rotate API keys as appropriate.

Chainalysis has now said it started restoring access to KYT and Address Screening, albeit partially, and that customers should expect to regain access “over the next several hours”, because it was “proceeding carefully” and monitoring each phase. Users looking to regain their access as soon as possible are invited to submit their trusted IP address via email and prepare to reset their credentials.

No word from the perpetrators (yet)

The company said it was still working “around the clock” to harden its systems and restore access to Reactor and Data Solutions. “We recognize the disruption this incident has caused and appreciate your continued patience and partnership as we work to restore our services safely,” Chainalysis said.

Chainalysis is a blockchain analytics company that governments, law enforcement agencies, and other businesses use to track and investigate cryptocurrency transactions.

Using its tools, the police were able to trace stolen funds, identify illicit activity, and investigate numerous cryptocurrency-related crimes. It is considered a rather important organization in the crypto cybersecurity chain because it provides much of the intelligence infrastructure that helps authorities and businesses understand who is moving crypto and where.

At this moment, we don’t know if this will result in an extortion attempt. No threat actors have claimed responsibility for this attack, and the data has not yet emerged anywhere on the dark web. Chainalysis has not mentioned being reached out by the attackers or even trying to get in touch with anyone.

• 96% of college students now use AI, but half of them would ban it tomorrow
• Heavy users are more likely to feel schoolwork would become harder without it
• They're worried about cognitive decline, but more so about AI's environmental damage

New research has likened the relationship between Gen Z and AI use to that of previous generations with smoking cigarettes, characterizing it as widespread adoption, awareness of the negative consequences and a reluctance to give it up.

The study from Fizz found nearly all (96%) college students now use AI, but more than half (56%) would permanently ban the technology.

But although one in two would support banning AI, Fizz shows just how reliant students have become on it, with the proportion of learners believing their work would become much harder rising significantly among frequent AI users.

Students have become reliant on AI despite its potential consequences

"The heaviest users are hooked," Fizz declared, noting that 68% of students who use AI multiple times a day believe schoolwork would become harder without AI. This proportion falls to 59% among daily users, 42% among weekly users, 22% among users who use AI just a few times a month, and 9% among those who use it less than once monthly.

Fizz also warns that the effects have having a much broader reach than just homework, with 43% of heavy users agreeing preparing for their career would also be harder without AI. Two in five even worry their daily lives would be more difficult.

This could be because students still recognize that traditional skills and qualities are still in big demand – 27% put communication and people skills as their priority, indirectly implying that their AI use could actually be harming those.

A staggering majority (86%) of daily AI users admit to having used it for something they would previously have discussed with another person, like career or life advice (51%), personal problems (48%) and even deciding how to reply to a message (45%).

The report claims that nearly half of the heaviest AI users feel under pressure to use the technology because they fear falling behind in the employment market, despite acknowledging that it could also be harming their ability to succeed in employment.

But it might not be entirely their fault, because nearly two-thirds (64%) of the surveyed students said they feel at least some pressure from teachers or educational institutions to adopt AI.

They may be addicted, but they want it gone

As many as one in two (56%) students said they would ban AI tomorrow if they could, hinting at a broad recognition that it's impacting much more than just their education.

But cognitive decline and dependence (28%) actually came in second place, behind worries of environmental damage (35%).

It could just be that many students' dependence has now made them unable to give up AI, even though they have worries about its negative impacts.

"They reach for it when they're anxious or alone... And almost nobody believes it's actually making them better," the paper concludes. "Silicon Valley believes it handed Gen Z a superpower. Gen Z would hand it back tomorrow, as long as everyone else did too."

• Deloitte finds 28% of businesses report current revenue growth, up from 20% earlier this year
• Productivity and improved decision-making are still performing better
• Sovereignty has become an integral part of AI strategies

New Deloitte data has claimed that when it comes to business AI, we're finally at the stage of ROI, with more organizations than before now reaping the rewards of their costly deployments.

As many as 28% now report current revenue growth as a result of their AI strategies, up from 20% compared with earlier in 2026, the firm's report found.

Realizing higher revenue is largely seen as one of the most important returns from AI – with companies spending so much on services and infrastructure, they need to make that money back.

AI adopters are finally seeing increased productivity translate into higher revenue

While other areas like efficiency and productivity (up 74%), decision-making and data insight (up 60%), cost reductions (up 45%) and better client relationships (up 44%) are all moving in the right direction, Deloitte says increasing revenue is still one of the slowest to deliver tangible results.

Deloitte's research also indirectly implies that businesses could be getting carried away with these early signs, because the majority (86%) of businesses surveyed plan to increase AI investments over the next financial year.

Additionally, while early ROI markers are now heading in the right direction, Deloitte worries that many businesses still don't have the right visibility into AI's financial impacts. While three in four (71%) are tracking total spend across token consumption, many can only see the total bill and not the breakdown of which activities lead to which spend.

Jobs are changing because of AI

It's becoming an increasingly familiar concept that employers need to redefine roles as AI becomes more engrained – developers are already seeing a shift from writing code to managing AI agents, for example.

Deloitte says there's a long way to go on this front, because while three in five companies have already redesigned jobs 'moderate[ly]', only 15% of them have done so 'extensive[ly]' and 1% 'completely.'

"Many are still just scratching the surface," the report claims.

The future of AI investments looks different

Looking ahead, Deloitte expects sovereign AI to become even more of an important consideration. Nearly half of Americas (46%) and EMEA (47%) businesses are building in-house to regain control over their workloads, with three in four (74%) global respondents reporting at least 'moderate' importance of sovereign AI.

But the paper does acknowledge the benefits of using centralized hyperscalers, noting that going sovereign or building in-house comes with certain trade-offs – usually "capability, speed or cost."

At the same time, we're hearing more and more about enterprises like Revolut picking up the infrastructure bills themselves, choosing to self-host open-weight models for greater cost predictability, usually at the expense of model performance in scenarios where they can achieve their desired outcomes without leading frontier models.

The report sets out six key considerations for the next stages of AI: adopters must respond by redesigning work as a whole, not just the workflow; costs need to be traceable to the token degree, not just the full bill; AI strategies must align with actions that produce revenue; governance needs to keep up as systems become more autonomous; early adopters are now starting to look at physical AI like robots, and so should you; and sovereignty should be seen as an ongoing effort consideration over a one-time fix.

For years, the retail industry treated the touchscreen as shorthand for interactivity. If shoppers could browse an endless aisle, customize a product or trigger an animation, the store was considered interactive.

That definition is beginning to look dated. The next generation of interactive stores will not be defined by what shoppers touch, but by what the environment understands — and how appropriately it responds.

This is an important distinction. A store can be filled with digital displays, interactive kiosks, sensors and immersive installations and still behave like a static space. The content may be visually impressive, yet remain unchanged regardless of what is happening on the sales floor.

The same promotion runs when inventory is plentiful or nearly depleted. The same message appears during a quiet morning and a crowded evening. Every screen is managed as a separate endpoint rather than as part of a coordinated customer experience.

That is technology added to a store, not a truly interactive store.

Digital channels

Digital channels have already established a different expectation. Websites and apps routinely adapt to location, browsing behavior, product availability and the stage of the purchasing journey. Yet many physical stores continue to communicate in exactly the same way throughout the day, even though conditions inside them constantly change.

Shoppers do not describe this disconnect in technical terms. They simply notice the difference between an environment that helps them and one that keeps broadcasting messages at them.

A genuinely responsive store adapts communication to context. When foot traffic increases in one area, nearby displays can prioritize information relevant to that location. When an item is running low, promotional content can be adjusted instead of continuing to create demand the store cannot fulfill.

When a line begins to form, screens can provide useful updates, redirect customers or reduce the perceived wait. When a campaign performs better at certain times or in particular stores, retailers can optimize it without rebuilding the entire content plan.

The objective is not to surround shoppers with more stimuli. It is to make every interaction more relevant.

Three forces

Three forces are moving physical retail in this direction: operational data, artificial intelligence and retail media.

Operational data allows the store to become aware of its own conditions. Foot traffic, dwell time, inventory, queue length, daypart, weather and activity by zone can all help determine what information is most useful at a particular moment. Importantly, many of these applications do not require identifying an individual shopper. A retailer can make the environment more responsive using aggregated or operational signals, with clear privacy rules and appropriate governance.

AI can help interpret those signals and turn them into decisions: which content to prioritize, when to activate or pause a campaign, how to adapt a message and where automation can reduce repetitive work. But the goal should not be to hand every decision to an algorithm. Retailers need business rules, human oversight and clear limits defining what the system may change. AI is most valuable when it supports operational judgment rather than becoming another opaque layer of technology.

Retail media adds a third dimension. In-store screens are evolving from communication tools into media inventory that can generate revenue close to the point of purchase. That opportunity is significant, but it also creates competition for attention. A paid campaign, a store promotion, a wayfinding message and an operational alert may all need the same screen at the same time.

This is why the next stage of store technology is not primarily about managing more screens. It is about orchestrating communication.

Shared logic

Retailers need a shared logic that decides which message takes priority, under which conditions and for how long. That logic must work as consistently in 500 stores as it does in a flagship. Otherwise, every new data source, media campaign or interactive feature creates additional manual work for local teams and another potential point of failure.

Complexity is one of the biggest risks in retail technology. Innovation is too often measured by accumulation: more displays, more systems, more dashboards, more vendors and more data. The result can be the opposite of what was intended — stores that are harder to operate, employees who are asked to manage tools outside their core responsibilities and experiences that cannot be scaled beyond a showcase location.

Technology only creates value when it simplifies complexity for the people running the store. That does not mean pretending the complexity has disappeared or placing an “AI-powered” label over it. Real simplification requires doing the difficult work behind the scenes — connecting data, setting priorities, integrating systems and establishing governance — so that store teams receive only what they need. The ideal outcome is not another dashboard. It is a screen that does the right thing at the right moment without demanding constant intervention from a store manager.

The same principle applies to creativity. Good automation does not replace creative thinking; it gives it room to scale. It allows a strong concept to move beyond a one-off installation and become an experience that can be deployed, measured and improved across an entire store network.

The future of interactive retail

That is why the future of interactive retail will not be built around isolated spectacle. The “wow” effect can attract attention, but it does not necessarily create lasting value. An installation that impresses shoppers for 10 seconds but cannot be updated, maintained, measured or integrated into daily operations has a limited future.

The next phase may look less overtly technological, but it will be more consequential. The best stores will not necessarily have the most screens or the most visible technology. They will feel more intuitive. Content will appear when it is useful. Displays will help organize the experience instead of competing for attention. Communication will reflect local conditions. Store operations will become more fluid. Shoppers will sense that the environment responds better to their needs, even if they cannot see the systems making that possible.

The challenge for physical retail is no longer simply to digitize the store. It is to give the store the same ability to adapt that customers already expect from digital channels.

The interactive store of the future will not be the one with the most touchscreens. It will be the one that listens to what is happening and responds at the right moment.

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• 100+ organizations are supporting European data center moratoriums
• The temporary ban would buy governments time to assess impacts
• UK set to add 6GW by 2030, but new Covenant sets out expectations

More than 100 organizations across 15 European countries have come together to campaign against ongoing AI data center developments, calling for an immediate moratorium on new large-scale campuses.

The Stop Dirty Data Centres campaign wants governments to take the time to consider environmental, economic and social consequences.

To get the message across, the group is reportedly planning protests across the UK, Ireland, Poland, Denmark, Finland, Spain, the Netherlands and France, with events set to take place on November 6 and 7 2026.

Europeans are standing up against data centers

Rather than calling for all new data center projects to be called off, the group just wants a temporary pause so that governments can establish stronger planning, regulatory and environmental frameworks.

It's not the first time we've seen such action – groups across the US have also been petitioning for similar moratoriums, and many states and regions have even been successful in imposing such moratoriums, including New York State.

Campaigners are also putting pressure on data center developers themselves, calling for greater transparency around projects' environmental footprints and operating requirements.

"The explosion of AI data centres across our towns and cities is taking a toll that we can no longer afford," the group wrote, citing impacts on local communities, jobs, energy bills, water shortages, mental health, surveillance and e-waste.

"Big tech companies lobby governments to fast-track construction and operate in secrecy, bypassing protections for our communities and ecosystems," the group added.

The campaign claims support from tens of organizations, including Greenpeace UK, multiple localised Friends of the Earth branches and Extinction Rebellion Bristol.

Meanwhile, the UK government anticipates needing an additional 6GW of AI data center capacity by the end of the decade.

The Data Center Covenant, set out by the UK government, insists that future plans pay for their own energy, invest in improving local communities, adhere to stringent environmental standards, support local jobs and help to enhance national security.

• Report finds 74% of firms prioritize recovery speed over quality
• Businesses are torn on whose responsibility a recovery is
• Defining a 'Minimum Viable Company' helps identify what needs fixing first

New Cohesity research has revealed UK businesses could be putting themselves at risk of cyberattacks because they're prioritizing recovery speed over quality.

This applies to three in four (74%) UK organizations, according to the report, with nearly as many (70%) failing to even check that attackers have been fully removed from breached systems after a cyberattack.

Expenses back this up too, because three-quarters (76%) of the businesses surveyed admitted that cyber resilience investments focus too heavily on prevention rather than response and recovery.

Cybersecurity isn't focusing enough on effective recovery

Crucially, Cohesity's data shows that business leaders are virtually clueless about the state of their IT teams' readiness, with half (52%) of UK CEOs expecting basic business operations to resume within just 24 hours. A false sense of security could partly be why budgets aren't being directed to the right causes.

It's also clear that the responsibility for deciding which systems get restored first is still pretty uncertain – 23% say it should be on the entire board, 21% pin it on the CTO, 20% on the CEO and 14% on a security advisory board.

The report urges all organizations to consider their Minimum Viable Company (MVC) – the minimum combination of systems, processes and services that are deemed necessary for a business to carry on essential operations after an attack.

With a clear MVC, teams will be better placed to know which systems to prioritize. But at present, two in five (41%) don't even have their own definition of an MVC – on the flip side, not even one in five (17%) have a documented and tested definition.

"If you restore a system before verifying attacker access has genuinely been removed, you risk reinfecting yourself," UK&I VP Fraser Hutchison summarized.

Looking ahead, the next stages are pretty clear. Businesses need to define which systems are most fundamental to their core operations and who holds the responsibility of post-attack restoration.

In September 2026, the government announced plans to cut the administrative burden on businesses, freeing them to focus on growth. Its proposals to simplify corporate reporting, including lighter-touch requirements for SMEs and wider audit exemptions, could save businesses more than £450 million a year.

With some companies’ statutory annual reports and accounts now averaging 98,000 words, the reforms reflect a broader push towards more proportionate reporting and less unnecessary administration.

For business leaders, however, simpler reporting should not mean weaker financial discipline. Reducing what a company is required to report is not the same as reducing what it needs to know.

In fact, this is where the bigger opportunity lies. The debate about reporting reform tends to focus on the burden removed: fewer requirements, less paperwork and lower costs. But its value should also be measured by what businesses can do with the time and attention they get back.

As businesses grow, their financial decisions become more consequential. Leaders need to know when they can afford to hire, where they can invest, how long their cash will last and what changing costs mean for their plans. The less time they spend producing information simply to satisfy a requirement, the more time they can spend using that information to make those decisions.

Using financial information to make strategic decisions

Simpler reporting does not make the underlying financial information any less important. In fact, as a business grows, having an accurate and current view of its finances becomes increasingly valuable.

What a founder could once keep track of themselves – who has paid, what is due and what is coming in – becomes harder to see as customers, suppliers, employees and transactions multiply.

We are also seeing a broader shift towards financial information being captured and managed more regularly. Making Tax Digital, for example, requires sole traders and landlords within its scope to maintain digital records and submit information four times throughout the year, rather than treating tax administration solely as an exercise around an annual deadline.

The opportunity for businesses is to make that information work harder. A current view of the finances can give business owners and accountants a shared understanding of performance, help identify issues sooner and provide a stronger basis for decisions about what comes next.

In that sense, the value of financial information should not be measured only by whether it satisfies a reporting or tax requirement. Its greater value is in helping to make better decisions about the business.

Technology is changing what financial management can do

The shift towards digital reporting also raises a bigger question about technology. If businesses no longer need to spend as much time manually assembling information, what should technology enable them to do instead?

AI is beginning to change the answer.

Connected systems can already bring financial information together and reduce repetitive administrative work. AI tools can go further by helping identify patterns and bringing potential issues to a business owner’s attention earlier, from rising costs and overdue invoices to emerging pressure on cash flow.

The significance is not simply efficiency. It is the possibility of moving from looking backwards at financial information to using it more actively to inform what happens next.

That does not remove the role of human judgement. Quite the opposite. Technology can identify a change in the numbers, but it cannot take responsibility for a decision to hire, invest or change direction. Business leaders still need to exercise judgement, while accountants bring expertise that can help interpret the numbers, test assumptions and understand the choices available.

The future of financial management should therefore not be framed as technology versus human expertise. The more useful question is how technology can give people better information, sooner, so that their expertise can be applied where it matters most.

Making the time saved count

The government has put a figure on what these reforms could save businesses. But the wider opportunity is what businesses can do with the time and attention they get back.

For growing businesses, that could mean spending less time on unnecessary administration and more time understanding cash flow, making investment decisions and planning for what comes next. Better financial information and technology can help, but ultimately it is how leaders use that information that matters.

Reporting reform will not make the financial decisions that come with growth any simpler. But it can give businesses more time to focus on them. If these reforms succeed, that may prove just as valuable as the direct cost savings themselves.

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• Around four dozen US recon and intelligence Marines are joining NATO's Baltic Sentry alongside Finland's Coastal Brigade
• They were re-tasked from training rotations already in Europe and will feed drone and sensor data into NATO's shared picture
• It is the Corps' second Baltic Sentry stint, after roughly 40 Marines deployed to Finland in February 2025

A small team of US Marines is being redirected to the Baltic Sea to help NATO keep watch over the cables and pipelines on its seabed, some of the most exposed infrastructure in Europe.

Around four dozen Marines from 2nd Reconnaissance Battalion, 2nd Marine Division, and the II Marine Expeditionary Force Information Group will operate alongside Finland's Coastal Brigade in support of NATO's Enhanced Vigilance Activity Baltic Sentry.

Both units are based at Marine Corps Base Camp Lejeune in North Carolina, and Military Times reported a headcount of 48, in line with the recent release announcing the move at the start of October 2026.

Eyes on the water not on the helm this time

What the team brings is surveillance. The rotation will use small uncrewed aerial systems and littoral sensors to feed data directly into NATO's shared common operational picture.

Washington is also keen to stress who is in charge to avoid overstepping: Baltic Sentry is led by European allies under Allied Joint Force Command Brunssum and Allied Maritime Command, with the Marine Corps serving in a "supportive, enabling capacity."

Maj. Gen. Daniel Shipley, who commands US Marine Corps Forces, Europe and Africa, said working side by side with Finnish allies would build "a cohesive, lethal team to deter hybrid threats in the Baltic littoral."

The Finnish Navy's chief of operations, Capt. (N) Johan Tillander, said the Marines' experience, skills and systems were "perfectly suited for supplementing our situation picture."

This is not the first time recon Marines have taken on the task. In February 2025, roughly 40 Marines from the same battalion deployed to Finland with RQ-20 Puma drones, in what the Corps described as the first activity between Finland's armed forces and the Marine Corps since a US-Finland defense cooperation agreement took effect in September 2024. At the time, the Corps said its expertise in coastline environments made it "a logical partner" for the mission.

Baltic Sentry itself launched in January 2025, after a run of incidents put the region on edge. Two fiber-optic cables more than 100 nautical miles apart were severed on November 17 and 18, 2024, and on Christmas Day the Estlink 2 power cable between Finland and Estonia was damaged along with four telecom lines, according to a Baird Maritime timeline.

Evidence of Russian interest in cables is more than just an assumption: A Telegraph investigation covered by TechRadar Pro logged more than 500 incidents in which 17 Russian trawlers loitered over or traced cables linking Britain to Europe and the US. UK telecoms minister Ian Murray said Russia was "starting to use commercial proxies," and the UK has proposed replacing its 1885 cable law with penalties of up to 14 years' imprisonment.

In the Arctic, British, Norwegian and American forces disrupted a Russian exercise near Svalbard this spring involving vessels tied to GUGI, Russia's deep-sea research directorate, which was reportedly rehearsing with a device designed to cut cables while leaving little evidence behind. Norway's defense minister, Tore Sandvik, said the operation "sent a clear message to Russia that they cannot operate covertly," although reporting so far shows the device was rehearsed rather than used against a live cable.

The deployment lands amid sharpening tension with Moscow. Stars and Stripes reports that allies have accused Russia of repeated airspace violations, that Estonia has arrested suspects over an arson attack it says Russian special services ordered, and that Moscow has warned it could resort to nuclear weapons if NATO tried to isolate Kaliningrad. NATO Secretary General Mark Rutte dismissed the threat, saying "if anything happens, we are ready to counter it."

At the same time, Pentagon officials have reportedly asked Lithuania, Latvia and Estonia to tone down their public rhetoric on Russia, according to four people who spoke to Reuters, with policy chief Elbridge Colby among those delivering the message. One European official summed up the request as "Just don't be loud. Don't make noise." The Pentagon declined to discuss private conversations, and a review of US force posture in Europe could yet bring a sharp drawdown.

Read against that backdrop, a few dozen Marines re-tasked from an existing rotation, wrapped in language about European leadership, looks less like an escalation than a low-cost signal: Washington is still present in the Baltic, but quietly and in a supporting role. Whether that proves enough is only something that time will tell.

• OpenAI launches new program to protect residents and businesses near its data centers from power outages
• The Grid Protectors Program is designed to prevent OpenAI campuses from “hogging” all the power
• A new development in Effingham County, Georgia, will pioneer the program

OpenAI wants to protect local communities situated around its data centers from power outages, and has launched a new program intended to deliver both reliability and affordability to nearby residents and businesses.

The Grid Protectors Program is launching with the planned Effingham County, Georgia data center campus, which features an agreement with Georgia Power to make power available in a flexible demand scenario, which should cover demand for around 700,000 households.

OpenAI’s future facilities are designed to be more flexible in how they demand power from the grid, and the Grid Protectors Program viewed as a “starting point” for improved reliability for homes, businesses, and of course data campuses.

Grid Protectors pilot

The Grid Protector Program certainly seems a step in the right direction from OpenAI. It comes against a backdrop of growing concerns over the power requirements of AI data centers and protests over their approval, invariably in locations where residents are resistant.

OpenAI says the pilot site at Effingham County incorporates its agreement with Georgia Power to accommodate “up to 1,000 megawatts of flexible demand response.”

This is intended to ensure local residential and business properties have the power available “to help keep air conditioning running in hundreds of thousands of homes during extreme heat. For scale, that is equivalent to the average electricity demand of roughly 700,000 households.”

OpenAI says this is more than enough to cover the combined households of Washington, D.C., and Boston.

Financial assurances

By working to offer communities assurances of flexible energy at its new site, OpenAI clearly hopes that its upcoming data centers are recognized as more suited to locations that have recently come under fire.

Perhaps they want to be a part of those communities? The launch announcement adds that its new compute facilities are more flexible than older facilities, and OpenAI is committing itself under the Grid Protectors Program to collaborate with authorities.

“We will work with utilities, regulators and policymakers to develop practical arrangements for the campuses we build in the future,” it announces, “arrangements that reflect local grid needs, help campuses support the grid when it is under pressure, and pay the costs we create. Long-term contracts and financial assurances can protect other customers if a project is delayed, reduced or canceled.”

The Taiwan Semiconductor Manufacturing Company (TSMC) is one of the most significant and powerful forces in the technology world today.

While it's not the only chipmaker out there, it produces around 90% of the world's most advanced semiconductors and has up to 70% market share of the global contract chip-making market.

Global fracturing

The founder of TSMC, Morris Chang, gave his verdict on the state of the global supply chain during the opening ceremony of the company's advanced chip plant in Arizona.

Chang was careful not to describe the global supply chain or globalisation as completely dead but "almost" dead – indicating that it still exists in some way but has been heavily reconfigured to adapt to changing times.

There are several reasons for this, including rising geopolitical tensions, especially between the US and China, as well as a move toward manufacturing repatriation and the formation of blocs rather than the promotion of ever-closer global ties and free trade for the sake of it. That is the context in which TSMC began operating, and a way of the world that is being lost.

Crises and shocks

Since COVID-19, there have been a series of supply chain shocks that have hit businesses and, in the end, consumers when it comes to the price of technology.

The chip crisis that lasted between 2020 and 2023 was the most disruptive shortage of technology that hit countless sectors worldwide. This was caused by the surge in demand for electronics, with people homebound due to the lockdown measures, the geopolitical cracks that started to form, as well as the death of just-in-time logistics.

Although the crisis eventually abated, a new shortage in memory has hit companies and consumers across the world in a similar way. These new problems, however, are more attributable to the AI boom, in which the surge in AI data centers and demand for high-bandwidth memory have led to bottlenecks in the production of consumer-grade memory like DDR5 RAM and SSD storage.

• Khadas Mind Go switches between tablet, laptop, and desktop configurations
• A detachable keyboard increases battery capacity from 18Wh to 53Wh
• The cooling stand increases processor power from 12W to 30W

Khadas has introduced the Mind Go, a computer running the Windows operating system which changes between tablet, laptop and desktop configurations through detachable hardware modules.

The central idea is that users retain the same computing components, applications and documents while changing how the computer is assembled.

Weighing 611g and measuring 6.1mm at its thinnest point, the fanless touchscreen computer can operate independently or connect to accessories.

One computer with three working configurations

In tablet configuration, Mind Go functions as an 11.6-inch touchscreen computer, with an LCD panel offering 2800 × 2000 resolution and a 120Hz refresh rate.

The display reaches 500 nits of brightness and covers 100% of the sRGB colour gamut, while supporting both portrait and landscape orientations.

For laptop use, a magnetic keyboard module adds 79 keys, a full-area trackpad and a separate 35Wh battery to the computer, which increases the computer's total battery capacity from 18Wh to 53Wh.

With the keyboard attached, Khadas claims the device can play videos for up to 12 hours, which is decent for a computer designed with portability and aesthetics in mind.

The keyboard also includes white backlighting with three brightness settings, 1.3mm key travel and a leather-textured cover over its aluminium build.

Desktop operation requires the Mind Go Stand, which provides active cooling and raises the processor power limit from 12W to as much as 30W.

The stand also supplies additional connections, including two HDMI 2.1 ports, two USB-A 3.2 Gen 2 ports and a 2.5Gbps Ethernet connection.

Its other interfaces include two USB-C ports, a headphone socket, built-in speakers and a USB4 connector linking the computer to the docking module

Processor options and prices

Buyers can choose between Intel Core Ultra 5 226V and Core Ultra 7 258V processors, both featuring eight cores and eight threads.

The first configuration includes 16GB memory, 512GB storage and Intel Arc 130V graphics, while the higher option doubles memory and storage capacity.

The Core Ultra 7 version uses Intel Arc 140V graphics, reaches a maximum turbo frequency of 4.8GHz and provides 115 TOPS peak AI performance.

The lower processor reaches 4.5GHz and offers 97 TOPS total peak AI performance, compared with the more expensive model's higher computing figures.

Both versions include Intel AI Boost neural processing, while their respective neural processing capacities are rated at 40 TOPS and 47 TOPS.

The 16GB memory and 512GB storage configuration with an Intel Core Ultra 5 226V processor costs $1,999 during the super early promotion and $2,299 at retail.

Upgrading to an Intel Core Ultra 7 258V processor, 32GB memory, and 1TB storage increases the price to $2,699 initially and $3,099 at retail.

Adding the keyboard and cooling stand to the 16GB and 512GB configuration brings the price to $2,799 during the super early promotion and $3,099 at retail.

The version combining both accessories with the Core Ultra 7 processor, 32GB memory, and 1TB storage costs $3,399 initially and $3,899 at retail.

As of the time of writing, Khadas has not announced an official launch date or confirmed when sales will begin.

• Apple is reportedly cutting AI budgets per worker
• Developers will still likely have more than other workers
• Model choice and hosting provider could be enough to cut costs

Apple has reportedly started cutting the amount employees can spend on artificial intelligence, per Bloomberg reporting, making it one of the latest companies to be limiting AI tool expenditure as unpredictable costs skyrocket.

The Cupertino giant had already reportedly cut budgets from $300 per engineer per day to $200 in October 2026, but further reductions are said to be planned as this figure could be on track to drop to $100.

Non-engineers are likely to face even tougher restrictions, with the company considering a 75% cut from $100 to $25 per worker per day, the report claims.

Apple could be set to limit workers' AI budgets

Like other tech giants that have introduced similar cuts, budgets will likely be determined by team and project, and certain projects and individuals could be able to justify higher consumption if their work requires it. However Apple declined to comment on Bloomberg's story.

Workers could also be asked to reconsider the tools they use, with the company said to be permitting the use of ChatGPT, Claude and Gemini, rather than just one. Engineers may be asked to use lesser models, which are cheaper, or even transfer workloads to even cheaper models that run locally on the company's own hardware.

UK digital bank Revolut has already moved away from Claude in favor of open-weight models hosted on its own infrastructure.

While a budget cut from $300 to, possibly, $100 per day may sound like a 3x decrease, it might be more attainable for some workers than those figures suggest. Earlier AI efforts among tech giants saw developers so-called 'tokenmaxxing' – using AI more than they really needed to, just to appease company metrics. It's unclear whether this applies to Apple's developers.

Still, the company likely faces an expensive short-term future, with R&D expenditure up 32% in FY 2026 compared with FY 2025, and total operating expenses up 22%. Quarterly revenue rose just 12% year-over-year, in comparison.

• Researchers spot White House network traffic being routed through dozens of residential proxy services
• Findings suggest a device on government infrastructure may have been enrolled in a proxy network
• Security experts warn proxy services on sensitive networks could enable abuse, anonymity, and potential lateral movement

The IT network at the White House was seen routing traffic for at least 28 residential proxy services, meaning there is a strong chance government infrastructure is being abused by (malicious) third parties, cybersecurity experts are warning.

Security researchers at Layer3 Intel published a new report, saying they saw 236 instances of residential proxy traffic originating from AS2650. That is the name of an autonomous system registered to the Executive Office of the President, the federal agency that hosts the White House network.

The researchers observed the traffic between October 5 and November 3 2026, and said that in 26 of the 30 days of observation, six IP addresses kept appearing.

Dozens of proxies

“This is public access,” the researchers said. “Anybody can obtain it by signing up to a public residential proxy service, paying a few dollars and sending requests through it.”

Residential proxy is a service with a self-explanatory name: paying customers can route their internet traffic through devices connected to residential internet connections (households, essentially), making it appear as though their requests originate from those connections rather than their own. They are not malicious per se, and have legitimate uses, but they’ve become popular among cybercriminals looking to hide their identities, evade security controls, and distribute malicious traffic.

Now, according to Layer 3 intel, 28 different residential proxy providers were able to route traffic through the White House network. The researchers cross-checked the IP addresses against public databases maintained by residential proxy detection companies Spur and Synthient, and both identified them as proxy exits.

Apparently, the researchers did not set out to analyze the White House’s network. Instead, they said they were testing a newly launched platform that “gives researchers a global view of residential proxy and anonymized internet activity,” and stumbled upon the activity while requesting rotating access through residential proxy services.

The cybersecurity community did not seem all too surprised with the news. In a Reddit discussion, IT experts shared their experience with senior leadership, both in public and private sector organizations, saying many were happily sacrificing security for convenience, opting not to install 2FA, or leaving their devices and email inboxes wide open.

One reader suspected someone in the White House “probably installed a sketchy free app on their phone, and now strangers are browsing the internet through the building's connection.”

The timing of the activity is also worth a mention. Around half of the observed connections happened between 5pm and midnight, Eastern time, with almost no activity recorded during the early morning. Layer3 Intel surmised that a device was regularly connecting to the White House network during evening hours, potentially one compromised by a residential proxy SDK.

Reaching internal systems

“That pattern suggests a person rather than a public guest Wi-Fi network: someone regularly on the White House network late into the evening, whose device is infected with a proxy SDK,” the researchers explained.

The researchers also pointed out that poorly secured proxy SDKs can allow internal network access and lateral movement. “This is how past botnets have spread,” they said. “If an SDK on this network has the same kind of flaw, anyone buying proxy access could use it to reach internal systems.”

There are plenty of other unanswered questions, too. For example, the researchers acknowledged that the data only shows network exits, not specific devices. Therefore, they don’t know if the activity is coming from a personal device, a guest network, or an entirely different source.

The White House discovery was not the only unusual thing Layer3 Intel laid out in its report. They also reported seeing residential proxy activity in some of the most remote players on the planet: Saint Helena, Ascension and Tristan da Cunha, a remote South Atlantic territory. The researchers saw 413 IP addresses and more than 32,000 observations on these locations, involving Elon Musk’s Starlink internet, as well as local internet service provider Sure Saint Helena.

The researchers also detected activity related to residential proxy networks in Antarctica, the Falkland Islands, the Chagos Islands, Tokelau, South Georgia, Pitcairn and Svalbard.

• French deputies voted 11 to 10 to tax content providers €0.055 for every gigabyte sent to French internet subscribers
• Backers claim €10 billion a year in taxes, but the government disputes both the figure and whether traffic can be measured fairly
• Five days later, the Assembly rejected the budget's whole revenue section 458 to 0, wiping out the tax with it

France's lower house had voted to charge content companies for every gigabyte they deliver to French internet users - but the measure lasted only five days before it was shot down unanimously.

Deputies rejected the revenue half of the 2027 budget by a vote of 458 to 0, LCP reported.

Every amendment adopted during three weeks of debate fell with it, including the per-gigabyte levy; this means that what now goes to the Senate is the government's original bill, which never contained it to begin with.

How a gigabyte would have become a tax bill

The amendment, tabled by Socialist deputy Laurent Lhardit, would have required content providers to pay €0.055 (roughly $0.06) per gigabyte delivered to customers of French internet providers.

It passed at the opening of the 9 am sitting on Friday, October 30, with just 35 of the National Assembly's 577 deputies taking part: 11 voted for, 10 against and 14 abstained, according to the official session transcript. Both the government and the finance committee's general rapporteur, Philippe Juvin, opposed it. Its authors said it would raise around €10 billion ($11.2 billion) a year.

The mechanics are spelled out in the amendment itself: Internet providers, along with any company selling internet access to households or businesses, would count the data flowing to their customers and attribute it to whoever sent it, under the supervision of telecoms regulator Arcep and France's tax authority.

Senders would be identified by company name and their Internet Assigned Numbers Authority (IANA) registration number, and no record of what the data contained or where it went could be demanded.

The move has not only found obvious opposition within French politicians after its surprise initial approval in a nearly empty chamber, but has found surprisingly vocal critics at home: VideoLAN, the nonprofit behind VLC, warned the levy would cost it more than €1 million a year, MacGeneration reports, though Lhardit replied that the caps would protect it. The founder of a national ISP, Free, Xavier Niel, dismissed the deputies on X as "ignorant incompetents."

OVHcloud founder Octave Klaba, whose company raised some server prices by up to 87% this autumn over memory costs, calculated that on a 100Gbit/s transit port costing around €6,300 a month, the tax on his assumed traffic would reach €1.02 million a month. He put OVHcloud's exposure at €23 million to €70 million a year.

Even the operators who would have done the counting were unenthusiastic. The French Telecoms Federation, which represents Orange, Bouygues Telecom and SFR, does not reject the idea that big platforms should contribute more to networks, according to Freenews, but it is worried about the technical and administrative load of a scheme whose revenue would go to the treasury rather than to networks, and would rather see commercial negotiations with the platforms.

The solemn vote on the revenue section was due on Tuesday, November 3, but it slipped because 758 amendments were still unexamined at midnight on Monday, NosParlementaires noted. It came on Wednesday evening instead, and no group voted for the amended text, essentially killing the entire proposal in its tracks before the French Senate got involved.

To reappear, the tax would need a senator to refile it and a chamber controlled by the center-right Les Républicains to back it, which Next considered unlikely.

The idea itself is not going away: The Socialists put a €0.10-per-gigabyte version in the program they presented this summer, ahead of next year's presidential election. There is, however, international pressure and considerations that would ensure this never actually happens, even as countries vie to attract the most AI infrastructure investments, and this could be the biggest dealbreaker for multiple players.

Beyond France, it runs against the tide. Brussels spent years fielding telecom operators' demands that Big Tech chip in for network upgrades, the so-called "fair share" fight, and in January the European Commission's Digital Networks Act proposed only a voluntary cooperation mechanism rather than mandatory network fees.

Then there is Washington: Donald Trump has long threatened tariffs on countries that tax US tech firms, and in June 2026 he warned of 100% tariffs on any country implementing a digital services tax on American companies. A per-gigabyte levy whose biggest payers would be Google, Meta, Amazon, and Netflix would be hard to present as anything other than that.

For now, the proposal stands killed; nothing has changed on anyone's phone or internet bill, and, seemingly, for the 2027 budget at least, nothing will. But the idea could show up in other forms in the near future.