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The Nintendo Switch 2 has had a chaotic time since launch, with the risk of tariffs and price hikes threatening to increase the cost of the console far above its original launch price. However, thanks to a brand-new price cut — and one excellent value bundle deal — it's now the best time to pick up the console ever.

You'll want to take yourself over to Argos, where you can save £65 on the Nintendo Switch 2 and add a game of your choice for £20 — for a total spend of £374.99. Available titles are not the usual garbage we see with these offers, too, as there are some excellent options to choose from, including Cyberpunk 2077, Metroid Prime 4, Pokémon Pokopia, or Star Fox.

Considering the Switch 2 is £419.99 at full price, and depending on the game you choose, that means the total potential savings are up to £112. I'd say Pokémon Pokopia is the frontrunner here, not simply in terms of value for money alone, but also because it's one of the console's best exclusive games.

No matter which game you pick, altogether, this is the sort of discount I never imagined we'd see on the console this early.

Today's best Nintendo Switch 2 deals

Switch 2 + 1 game for £20: was £486.98 now £374.99
Deals on the Nintendo Switch 2 have disappeared recently, but here's a chance to get it at the best price in months, as it drops to £354.99. You can also throw in a game for £20, including big hitters like Cyberpunk 2077, Metroid Prime 4, Pokémon Pokopia, or Star Fox. Any one of those will be a great way to start your collection.View Deal

Smyths Toys doesn't have bundle deals as good as the ones above, but you can also pick up the Nintendo Switch 2 by itself at the discounted price at the retailer. There is an offer to pick up a PowerA Slim Case for £10 when you buy the console as well, which is a cheap bonus item, but I'd recommend any of those £20 games at Argos over this useful but not essential accessory.View Deal

Is there a reason for this surprise discount? Well, I believe that it's at least partly due to a recent EU ruling that means the Switch 2 must comply with new battery regulations. The current version of the console doesn't, and so a new revision is set to become available this autumn, featuring a user-replaceable battery.

Nintendo has made it clear that there is "no difference in functionality between current products and revised products containing user-replaceable batteries," so you're not getting an inferior console when buying this current version. It plays all the same games and offers no performance differences.

With that in mind, I think this offer is going to be very difficult to beat, even with Amazon's Prime Big Deal Days coming in October and Black Friday in November. In fact, I wouldn't be surprised if the retailer is saving its current stock for next month's sale before launching a similar offer itself.

There's reason to wait, though, while the current Argos deal offers so much value.

• A bug in Windows 11's September update broke File History
• Microsoft admitted the backup feature was scuppered and has apparently now fixed it
• However, the cure is in an optional update, so it might be best to wait for the full release of the upgrade next month

Microsoft has admitted that Windows 11 has a bug that messes up a backup feature in the OS, although a new optional update fixes it (but not quite fully).

Windows Latest reports what's been a slightly odd tale in that the bug in File History has been kicking about since the September update first emerged over two weeks ago, but Microsoft didn't acknowledge it — even though it was a widely reported issue.

File History is a feature that enables you to keep files backed up to an external drive, and while it doesn't see a whole lot of use these days, it's obviously important for those who do still avail themselves of the functionality.

Microsoft informed Windows Latest that: "After installing the September 2026 Windows security update KB5124008, some customers using File History, might be unable to create or update backups. File History is used to back up files to an external drive or network location."

The good news here is that the latest September update, which is optional — it's a preview of the October update in fact — does fix this bug, as confirmed by Windows Latest, but it seemingly doesn't fully iron out every issue with File History.

Windows Latest noticed a post on Microsoft's Learn portal from a user who confirms that the new September preview update does mean that File History is working again and making backups, but there still appears to be an issue with the 'Run now' ability and problems with synchronization of save times therein.

However, this isn't a bug caused by Microsoft's recent work on Windows 11, and in fact this glitch dates back to a Windows 11 update in July 2026.

Analysis: update skeptics

(Image credit: Mark Pickavance)

At least File History appears to be cured of this latest feature-breaking bug, and hopefully the other problem highlighted on Reddit will be fixed before too long.

You don't necessarily want to download an optional update, of course, as it may bring in other bugs — after all, it's still a beta. The safest bet is to wait for the October update to arrive in two and a half weeks (on October 13) and then install that as the remedy for your File History blues (while temporarily keeping backups a different way, manually or on OneDrive, in the meantime).

Windows 11 bugs have remained a problem throughout 2026, and every year before for that matter (particularly with the 24H2 release). Microsoft still needs to do better in this regard considering this is one of the thornier issues that has continually dogged its OS, which it's busy fixing this year.

The trouble with the long-running overly buggy nature of Windows 11 is that it's making some users hold off updating the OS, and I don't mean for just a week or two. (I'd advise a week's breathing room in general myself, just to see if there are any major bugs or nasty showstoppers with any given update).

For example, this Redditor notes: "I am once again advising everyone to disable Windows updates. Let people test the bugs for a few months, then update. Your PC isn't gonna implode because you are 3 months behind on Windows 11 versions."

This was in reply to a comment which simply asked: "Is there a Windows 11 core feature that hasn't been broken at least twice since release?"

Cynicism prevails around Windows 11 updates in many corners of the web these days, and I think this is something Microsoft needs to act on. Yes, Windows is a very complex operating system that needs to cope with umpteen PC and device configurations, and a labyrinth of legacy features that must be maintained for a niche set of customers, but still — that's ultimately not an excuse.

Something needs to be done to improve QA and testing, otherwise it's going to be difficult to declare that 'Windows 11 is fixed' next year, which is Microsoft's goal (presumably).

I don’t know about you, but with every other ad being for some sports betting or prediction market platform, and every other app store game looking to cram in some kind of gacha system, I’m plenty sick enough of the 'gamblification' creeping into our daily lives.

At the same time, I kinda love Meta’s new blind box Meta Glasses with BlackPink and White Lotus star Lisa.

Call me a hypocrite, but the design collaboration is frankly genius, and while it isn’t for me (nor something I want to be bombarded with), as a one-off experiment, it feels set to be a runaway success.

@techradar

Are you ready to drop some money on the Meta Glasses Lisa Edition? ✨

♬ original sound - TechRadar

To catch you up to speed, alongside its new Meta VR Glasses, Ray-Ban Meta Gen 3 smart specs, and its first-ever cameraless glasses in the Ray-Ban Meta Audio glasses, we were also treated to a new Meta Glasses style at Meta Connect 2026.

The Meta Glasses are Meta’s own-brand smart specs. It still works with EssilorLuxottica experts on the designs, but they aren’t branded as such — making them more accessible as they don’t carry the same price premium a named brand would.

It’s also where Meta has debuted collab designs with celebrities. It kicked things off with Kylie Jenner with the Meta Starfire Kylie Edition shape — they’re much more rounded than anything Meta has released before, though the name always makes me think of the Australian pop singer — and has now announced a partnership with Lisa.

The specs of the Meta Glasses haven’t changed here. They still boast a 12MP ultra-wide camera with a 3K recording resolution, a battery life Meta rates at over eight hours, plus open-ear speakers for listening to music and six microphones for recording audio and taking calls.

(Image credit: Meta / Lisa)

Lisa’s glasses differ entirely due to their design. They come with black and pink lens and frame options (clearly inspired by Lisa’s world-famous K-pop group), and Lisa’s star icon on each stem tip.

Importantly, each pair also comes with a random charm — one of 12, two of which are extra rare — of cute dogs cast in different poses and colors. They’re inspired by Lisa’s well-documented love of her pets and blind boxes — herein lies why I love Meta’s approach to add a random element to its specs.

Collaborative designs that incorporate some aspect of the celebrity’s persona are always appreciated by the fans, and Lisa has expressed so much love for random blind boxes that their inclusion here feels like a slam dunk.

Plus, while some charms are a bit more special than others, I personally love all 12, and they’re such a small aspect (and similar enough) that I don’t see anyone being truly devastated whichever one they get — nor needing to seek out all 12 by buying up as many Meta Glasses as possible.

Meta / LisaMeta / LisaMeta / Lisa

Of course, I expect some new TikTok series will launch where an influencer with money to burn does attempt to open all 12, but outside of a few obsessed edge cases, I see this as a delightful expression of Lisa

If you want to get in on the Meta Glasses Lisa edition randomness, the new specs start at $339 (UK and Australian pricing TBC).

@techradar

♬ original sound - TechRadar

• Amazon is re-hiring former workers back into AI and cloud roles
• The company is investigating the impacts of its office-working mandates
• Despite 30,000 layoffs in the past year, Amazon continues to hire for certain roles

Amazon is reportedly trying to re-hire old workers, including many who were affected by previous rounds of layoffs.

Recruiter emails cited by Business Insider reveal that rather than filling roles that have emerged following layoffs, the company is actually targeting specific ex-workers it seems, with the company's cloud computing business predominantly seeing these hiring efforts.

AWS, cloud computing, AI, ML and agentic AI are apparently the focus of these efforts, with one recruiter reportedly referring to the scheme as 'Swami's Boomerang Reengagement Initiative' – Swami Sivasubramanian is a VP for AWS Agentic AI.

Amazon is re-hiring ex-workers back into the company

The company is also said to be making it easier for former employees to return, offering shortened interview processes that may skip over some of the screening steps that aren't all that necessary.

Besides trying to attract former talent, Business Insider also reports that Amazon is digging deeper into why they left, and the potential impacts of its return-to-office (RTO) mandates. Specifically, the tech giant wants to know whether the RTO changes were behind some ex-workers' departures.

While company spokesperson Haley Silva told the publication that Amazon isn't specifically targeting people who left because of the RTO and that its in-office expectations haven't changed, it's an interesting perspective from a company that went pretty much all-in on the RTO years ago in a bid to drive more in-person collaboration and to boost productivity.

All of this comes in the wake of major ongoing layoffs – the company fired around 30,000 workers just in the past year. But it's apparently all part of a broader shift in focus, because instead of cutting headcount as aggressively as that 30k figure suggests, Amazon's more likely looking to lose workers in certain areas of the business and gain workers in more important areas.

• A regular leaker says the chips for the PS6 and Xbox Helix have been 'taped out', meaning the design is final for manufacturing
• The leaker claims 56 TFLOPS of power for the Xbox Helix and 40 TFLOPS for the PS6
• That compared to 16.7 TFLOPS on the PS5 Pro and 12 TFLOPS on the Xbox Series X

The launches of next-gen console hardware from Sony and Microsoft are edging ever closer, and the latest rumor doing the rounds suggests that the chips for both the PlayStation 6 and what's being called the Xbox Helix are now 'taped out' — as in, finalized for submission to chip manufacturers.

This comes from well-known tipster KeplerL2 (via VideoCardz), who also predicts 40 TFLOPS of performance for the Sony hardware and 56 TFLOPS for the Microsoft hardware. That's Tera Floating-Point Operations Per Second, or how many trillions of calculations a processor can do in a single single.

While TFLOPS gives us some indication of how powerful these consoles will be, they're not the whole story, as architecture choices and memory bandwidth will play significant roles too. That said, it seems the Xbox console may have a major edge in terms of raw power — although the Xbox Series X had a 20% edge on TFLOPS over the PS5 back in 2020 too, which didn't necessarily translate into better-looking games.

Direct comparisons with current generation consoles are tricky, as so many other variables will be changing as well as TFLOPS figures, but TweakTown reports that the PS5 delivers 10.28 TFLOPS, the PS5 Pro offers 16.7 TFLOPS (typical) and 18.05 TFLOPS (peak), and the Xbox Series X can hit 12 TFLOPS.

But how much will it cost?How are PS6 and Xbox Helix shaping up to be such spec monsters? Is RDNA 5 really that big of an architectural leap? from r/hardware

Both the Xbox Helix and the PlayStation 6 are expected to be based on the AMD Zen 6 family of CPUs and the AMD RDNA 5 GPU architecture, if previous leaks are to be believed, and there has been talk of 30GB of RAM being packed inside the Sony console (no RAM predictions yet for the Microsoft one).

Judging by the ongoing discussion on Reddit, gamers aren't placing too much stock in these leaked TFLOPS numbers, as they aren't guaranteed to convert directly into gaming performance. The bigger debate seems to be over how much Sony and Microsoft are going to charge for these next-generation machines.

There are mentions of "an inevitably massive price hike" while another user is prepared to "say goodbye to affordable console hardware" in this generation. As we've already seen with the Steam Machine, the ongoing shortage of memory chips is driving up prices across the board, including in gaming hardware.

As for when we might actually see these consoles, don't hold your breath: experts say a launch before 2028 is unlikely, even if the design for the main processor chips have now been finalized. We'll just have to fill the time exploring everything Grand Theft Auto 6 has to offer in the meantime.

For decades, banking technology has been built around a simple sequence: a person makes a financial decision and the bank’s technology processes it. A customer decides to open an account, move money into savings or apply for a loan, and the bank’s systems execute that instruction.

Artificial intelligence can potentially reverse that sequence. Instead of waiting for a human to specify an action, AI can interpret the person’s goals, understand the financial context around that goal, and determine what happens next. It could recognize that a customer is likely to face a cash shortfall, identify the available ways to address it, and potentially execute the appropriate action.

McKinsey estimates that generative AI could create $200 billion to $340 billion in annual value for the banking industry. Yet much of the industry is adding AI to systems designed for the old model, not rebuilding the model around AI.

The problem is that AI inherits the same product silos and process boundaries. Banks gain another layer of technology, but not the cross-system decision-making needed to realize AI’s full potential.

The first wave is still about better processes

The most visible applications of AI in banking are often the easiest ones to deploy. Banks are using AI tools to improve customer service, automate fraud detection, personalize recommendations, summarize documents and accelerate credit decisions. Lloyds Banking Group, for example, says more than 50 AI use cases were rolled out across the group in 2025, generating around £50 million in value, with more than £100 million in additional value expected in 2026.

McKinsey has made a similar observation based on the industry's experience with generative AI. Simply adding AI on top of existing processes will not produce transformational change and can instead create another layer of technical debt.

The difference between an AI-native architecture and a chatbot attached to an existing system can be tested with three questions.

• Is the AI following a fixed sequence of instructions, or can it choose and coordinate actions within a defined system of guardrails, trusted data sources and approved tools?
• Is the process designed for the agent to act, with human review and every decision recorded for analysis?
• And are permissions, monitoring and regulatory controls built into the workflow, particularly for critical functions such as compliance and fraud prevention?

If the answer is no, the company has added an AI interface without redesigning the underlying process.

From products to outcomes

The more significant transformation begins when the bank starts with the customer’s objective, not with the banking product.

Consider a customer who wants to maintain a certain level of liquidity while earning as much as possible on excess cash. An intelligent banking system could continuously monitor their balance, upcoming payments, income, available credit and other relevant information, then determine whether money should remain liquid, be invested elsewhere or be used to reduce borrowing.

While the system can continue making decisions as the customer’s circumstances change, that does not require customers to surrender control immediately. Adoption can begin with low-risk actions, such as moving excess cash into savings or setting aside VAT for future tax payments, before expanding into more consequential decisions.

This is already beginning to appear in financial institutions, although mostly in bounded applications. Deutsche Bank, for example, has deployed an agentic AI system for third-party risk management in which several AI agents retrieve relevant controls, analyze supporting documentation, and propose assessment outcomes. Human assessors remain responsible for reviewing or overriding those recommendations.

Like a new employee, an AI agent should receive defined permissions. Transparent activity logs, alerts, approval thresholds and the ability to override decisions would make that principle visible in the product and enforceable by regulators.

The bank becomes a continuous decision system

Under this premise, the bank becomes an intelligent execution layer that continuously manages financial activity to accomplish a defined objective.

This shifting structure is also visible outside traditional banking. Visa and Mastercard are both building infrastructure for AI-initiated payments, allowing agents to act on behalf of consumers and businesses. Visa Intelligent Commerce is designed to let AI agents find and purchase products on a user’s behalf, with tokenized credentials, authentication and spending controls built into the payment flow.

As agents move from recommending actions to executing them, banks will need to ensure transactions remain within the customer’s intent and risk tolerance. The institution remains responsible for keeping the agent within those limits.

The architecture has to change with the AI

Deloitte found that integration with existing systems and tools is the top modernization challenge for 77 percent of banking executives deploying AI, ahead of security, compliance and cloud interoperability concerns.

Traditional banking systems separate payments, lending, accounts and compliance across different applications. AI agents need to work across those boundaries, combining data and actions from several systems to make a single decision.

Banks therefore need an orchestration layer that allows AI to access those systems without requiring another custom integration for every use case. The core platforms can remain systems of record, while more of the decision-making happens above them.

This gives AI-forward fintechs such as Revolut or Ramp, as well as new entrants designing their infrastructure from scratch, an advantage over institutions that must retrofit deeply embedded systems. If regulation remains broadly unchanged, the first major financial institution built around continuous decision-making could emerge within five years.

It may not be a bank in the strict regulatory sense, but it could perform an increasing share of a bank’s functions, allowing customers to manage their finances.

To thrive, I believe banks need to become institutions organized to make continuous decisions for the customer’s benefit, not simply to follow instructions. And when it comes to AI, they must stop treating it as a fancy tool to add and start treating it as something to build around.

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Saving $1,000 sounded pretty good to me. I wasn't entirely sure where Meta's Muse AI was supposed to find it, but Meta's chief AI officer, Alexandr Wang, and the #MuseMoneyChallenge sounded pretty encouraging about putting the company's new AI agent to work finding $1,000 in savings.

Some of the results shared so far make that target seem surprisingly plausible. People have reported finding cheaper insurance, forgotten subscriptions, and even unused gift cards, although many of the early examples highlighted around the challenge have come from Meta employees.

the last thing your unnecessary expenses see before your muse saves you $1000 pic.twitter.com/NwEO7nhmbKSeptember 19, 2026

I decided to give it a try. I was not expecting Muse to discover a forgotten Swiss bank account, but $1,000 seemed like a sufficiently concrete, if unlikely, target. The results showed how impressive Muse can be, if you're willing to let it into your life.

Financial exploration by AI

Muse is different from a conventional chatbot because it is designed to take action rather than simply tell you what you should do. Meta says it runs on its own secure virtual computer with a browser, can connect to services such as email and calendar, and can handle tasks including filling out forms and dealing with customer service. It can continue working after you close the app, although actions such as purchases and sending messages can require your approval.

That makes the money challenge more interesting than simply asking ChatGPT for tips on saving cash. Telling a chatbot to help me save $1,000 would probably produce an earnest lecture about meal planning and canceling streaming services. Muse can potentially go looking for the forgotten subscription itself.

I started broadly and told Muse I wanted it to find ways to save me money. Muse requires a little commitment from the user. The more useful you want an agent like this to be, the more access it needs to the places where useful information lives. Meta lets Muse connect to other apps and services, and says users control those permissions. The company also says login credentials are stored separately so the agent cannot read them, while sensitive actions can require approval.

Once I had given it enough to work with, Muse began looking for things that applied to me and surfaced possible actions. I already know that canceling services I do not use saves money. I do not need artificial intelligence to explain the revolutionary concept of paying fewer bills. What I wanted was something able to find the bills I have forgotten about.

Muse eventually identified some Patreon and Substack subscriptions I might not want anymore and another opportunity to reduce my phone bill based on some newly released data plans. Between them, the useful savings came to about $35. I checked the suggestions before acting on them, which is something I would strongly recommend doing.

Despite saving only 3.5% of the goal of $1,000, I was mildly impressed. It was still $35 I would probably have continued spending every month otherwise.

AI is good for boring work

(Image credit: Shutterstock/Poetra.RH)

The gap between my result and the #MuseMoneyChallenge highlights something important about these increasingly capable personal AI agents. Their usefulness can depend enormously on how much financial debris you have accumulated.

The impressive examples circulating online underline the difference in how people may keep an eye on their money, and where AI might actually help those who struggle with doing so. Recovering a year's worth of subscription payments is possible if you have accidentally been paying for something for a year. Those are genuine opportunities, but they are not necessarily waiting in everyone's accounts.

My $35 therefore felt less like Muse failing and more like discovering that I apparently did not have $1,000 sitting around waiting for an AI to rescue it. I would also let it spend more time searching for refunds and credits rather than concentrating entirely on recurring expenses.

One of the advantages of an agent is that it can tackle exactly the kind of mildly irritating administrative task that I postpone because the potential reward does not seem worth 40 minutes navigating a company's customer service system. That may ultimately be a better pitch for Muse than the tantalizing $1,000 target.

You will almost certainly have heard many business and technology leaders extolling the virtue of AI. They will enthusiastically tell you that the technology will have a transformative impact on businesses across the globe.

I think they are right. However, with two important caveats: AI must be given the right jobs, and the people using it must trust what it does.

Too often, AI is deployed across a business without much thought, as overconfident bosses assign agents tasks it isn't designed for. The problem this creates is that many employees using AI tools every day are not yet prepared for their new role in managing these agents. Trust only comes from experience and that builds over time.

When an AI system provides you with results that make sense and actually helps with your work, people start to feel more confident in using it. But if it makes a mistake, that confidence can be lost in an instant. If things go wrong, employees start finding ways around AI or stop using it altogether, and when leaders ignore employee concerns about making AI work better, its benefits are undermined.

The best way to ensure that AI delivers the efficiencies it promises is to ensure that it is doing the right job, and this isn't as straightforward as it sounds.

The areas where AI excels

AI works on probabilities, producing answers that are likely to be right. The key word here is ‘likely', which is why it occasionally hallucinates.

Being probabilistic makes AI very effective when dealing with unclear or complicated information. But it's not the best fit for tasks where a wrong answer could have serious consequences.

There are three core areas where AI really can make a difference. Firstly, when processing documents; secondly, decision support; and finally, personalization.

AI is especially effective at tasks involving many documents. It can extract, classify and summarize information that would normally take humans many hours to review. For example, an AI system could compare contracts against a standard set of clauses, or organize a large collection of customer emails by the issues they concern. This way, a person only has to look at the important findings instead of reviewing entire documents.

AI can also play a key role in supporting company executives to make decisions, as it's very good at taking lots of different pieces of information, finding patterns and delivering options as to what to do next.

It is, however, important to remember that AI is not always the right technology to make that decision. For example, imagine you're buying something and have to choose among many different suppliers.

AI can look at all the information, like how well they've done in the past, what they can deliver, how quickly it is likely to arrive and whether the supplier offers discounts for repeat purchases. It can even articulate why one option might be better than another. In most scenarios, though, it is the human who makes the final choice.

For some businesses, personalization is a promising tool, as AI can be used to make products more relevant to the individual using them. This is an area where working with probabilities can become a key driver for AI. The content only has to be good enough to make that connection so the recipient feels they are being addressed in a bespoke way.

The cost of assigning AI the wrong job

One of the key concerns companies should have about managing AI is that while AI-generated answers can sound assured, there is still a possibility that the technology has got something wrong. If that answer is allowed to trigger action without validation, a small error can travel rapidly through a workflow.

Think about what happens when someone makes a small mistake with a rule or detail in a contract. By the time someone catches the error, it may have already been added to records, sent to people outside the company, or even used to create new software.

To remind myself of AI’s limitations, I find it useful to think of the technology as the equivalent of a super-intelligent, hard-working intern. Interns need guidance and oversight, which should be provided by experienced, knowledgeable colleagues. Crucially, their access to sensitive information needs to be limited and granted only as they demonstrate they can make sound decisions.

AI needs to be managed in the same way. It should only be given greater levels of control when it has proved itself, and then its work must still be monitored by humans.

A good example of the importance of managing AI is its role in software development. AI can deliver a lot of code quickly, but its fast pace means the quality isn't always the same as that of human developers.

In fact, managing large amounts of AI-generated code can be a real headache for IT professionals. For example, surging token consumption and a shift to consumption-based pricing is ballooning AI coding costs, forcing developers to be selective on when and where they apply AI models, as reported by Gartner.

Let AI help design the model, not control the machinery

The most important design decision is where AI is allowed to reason. The riskiest place is deep in the implementation layer, where a small mistake can cause big problems that are hard to fix.

I believe a sound approach is to use AI to work with business ideas and rules. This way, it's easier for people to check and understand what the AI is suggesting.

Domain-specific languages and other abstractions used in model-driven development can provide that separation. AI helps create or refine a high-level application model, while a developer then validates the model before a deterministic platform transforms it into executable software.

AI can suggest how something should be done, but it doesn't have to be responsible for executing every step.

Abstraction helps developers, and in agent-driven systems it becomes a control tool. It simplifies complex systems and prevents small errors from becoming big problems, making AI output easier to test and fix.

Human expertise is becoming more valuable, not less

As AI becomes more prevalent, developers' roles will evolve. They will still write code, but a larger part of their role will be overseeing systems, checking outputs and catching mistakes, a change that brings with it the opportunity to learn new skills.

Developers will increasingly work at the level of systems and architecture, understanding the business rationale, recognizing patterns and judging whether AI-generated code fits the wider application and holds together.

One company that has innovated in this area and is already reaping the rewards for their experience is Ford. They recently hired 350 experienced engineers to help train younger colleagues and improve their AI and automation tools.

The shift was driven by the fact that the AI tools weren't producing the results they wanted without the expertise brought by seasoned professionals. Now, these experienced engineers act as internal auditors, reviewing designs and finding potential problems before they become major issues on the factory floor.

When you combine AI's ability to recognize patterns and process information with human knowledge and experience, it becomes a much more powerful tool. This combination is what makes it truly effective, not just relying on one or the other.

Building trust

Enterprises should also resist the pressure to deploy agents everywhere simply because competitors appear to be doing so. When it comes to using AI, leaders need to think carefully about each situation.

They should ask themselves three important questions. First, are they asking AI to only suggest what to do or to actually do it? Next, can someone check and fix what the AI says before an error spreads? Finally, what would happen if the system is certain about something but is actually wrong?

The answers play a big role in deciding how much freedom to give the technology. For example, a tool that summarizes documents might only need a quick check, but a system that suggests business decisions needs someone's logged approval.

When companies start using AI for specific, practical tasks, it shows employees that it can really make a difference in their work. This approach gives the company a chance to get its data, rules and processes in order. If people can see that the system is working well, and they understand what it can and can't do, they start to trust it more. Over time, this trust grows.

The key is to create a work setup where humans and machines do what they're good at. AI is great at processing large volumes of information and surfacing patterns. People are good at understanding the bigger picture, pointing out mistakes, and taking responsibility for their actions.

The wrong job to give to AI is any task where a mistake carries real consequences, no one checks the work before it causes harm, or the system sounds certain while being wrong. Companies that respect this division will build the confidence to give agentic AI greater autonomy over time. Those who ignore it may discover that a single poorly chosen task can undermine their entire AI strategy.

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• OpenAI agent breached Australia’s Medicare portal on June 18, 2026, accessing internal files
• Government says no personal medical data was taken, but three other agencies may be affected
• PM Albanese slammed OpenAI’s 84‑day delay in disclosure, calling the notification “unacceptable” and warning of legal consequences

An OpenAI agent has allegedly broken into a website of the Australian government, which has slammed the “unacceptable” attack, promising an in-depth investigation, and threatening “legal consequences”.

Australian Prime Minister Anthony Albanese revealed how in June 2026, OpenAI’s research team tasked the agent with researching public medicine spending, as part of an internal capability evaluation - but as the agent got to work, it was initially denied access to some of the information it requested.

However, instead of stopping, or trying to find a different lawful way of obtaining this data, it circumvented those restrictions and landed inside the infrastructure behind Services Australia’s public-facing Medicare Statistics Reporting Service portal.

AI agent did what?

The public details are still quite limited, and we don’t know the technicalities of what the AI actually did.

The acting prime minister, Richard Marles, told the media during a recent press conference that the AI “scaled the fence”, despite the portal having security measures in place.

The bot apparently accessed internal infrastructure and wrote files to an internal server but exactly what it wrote, how it obtained the access, and precisely which technical mechanism it used, is still not public knowledge.

Once inside, it accessed both public and non-public files, but individual medical data was not accessed and the system itself was not compromised, the Australian government said.

There is also the possibility that three other government systems were affected - the Australian Institute of Health and Welfare and two state-based agencies - the New South Wales Bureau of Crime Statistics and Research and the Victorian Department of Health. However, this has not been confirmed yet.

"No personal information is believed to have been accessed at this stage, but investigations are ongoing," Albanese said. "Nonetheless this situation is obviously unacceptable."

OpenAI's sluggish escalation

Albanese was particularly unsatisfied with how OpenAI handled the situation. The breach happened on June 18, but it took the company 84 days to notify the Australian government of the incident. And when it did - it did so in a manner better suited for an amateurish start-up rather than one of the most important organizations on the planet right now.

OpenAI was apparently evaluating its models, and investigating “misaligned model activity” when, on August 11, it discovered the breach in Australia. It seems the AI agent simply did not take “no” for an answer. The company then notified Services Australia on September 10 - almost three months after the incident. To make matters worse, the company reached out via publicdisclosures@servicesaustralia.gov.au, inbox researchers usually use to report potential vulnerabilities, instead of trying to escalate the incident higher.

Services Australia reviewed the information and notified the Australian Signals Directorate on September 15.

When the news reached prime minister Anthony Albanese, he spoke to OpenAI CEO, Sam Altman, and expressed the country’s “extreme concern” about this incident, as well as his “disappointment that it took the company way too long to inform the government what had occurred.” He also pointed out the way OpenAI reached out: “The notification was an email sent just to the public mailbox.” Albanese described the “nature of the notification” as “unacceptable.”

The Australian government is now looking into the matter to see if any laws were broken and what legal consequences, if any, could follow.

"And obviously we will investigate all of that. What the consequences are, if there has been a breach of the law, but also part of the task force is to assess whether or not the legal regime we have in place is fit–for–purpose in a world where we have an emerging AI capability,” Marles said.

Via BBC

• French streaming service Qobuz is introducing tags to denote AI-slop music
• The firm also shared stats on how many people engage with this kind of audio
• Meanwhile, Spotify wants you to use its new AI agent to listen to music

When AI-made music is covered in the media, it's often painted to be an insidious success story; reports on artists including Velvet Sundown, Breaking Rust and Enlly Blue invariably mention high stream numbers, along with huge estimated revenues. If that rightly frustrates you, know that the problem is occasionally with the reporting, and not with AI music being popular.

French streaming service Qobuz has never been backwards about coming forwards when tackling what Managing Director Dan Mackta refused to call music at all, when we spoke to him earlier in the year. And now, Qobuz has unveiled a feature which adds tags to music it detects was generated with AI. This goes further than Spotify's opt-in AI persona label, by highlighting real artists' slop tracks. So expect to see it on Dr. Dre's new music, for example.

This continues a run of anti-AI moves from streaming services such as Qobuz, Deezer and Tidal, which have all identified sentiment to slop at being overwhelmingly negative. Highlights include Tidal giving no royalties to AI music, and Deezer adding a filter to remove AI tracks.

The major outlier is Spotify, which has made small steps to combat AI music, but some steps backwards too. Recently, it teamed up with Meta's AI agent Muse (no, not the Plug In Baby band, the chatbot that Meta kicked the band off its social handles for). This partnership lets you... queue up music, give voice commands to control your playlists, create playlists, and set up playing schedules. How did we cope before AI?

Time to decide whether you want Muse (band), or Muse (Meta)?

(Image credit: Spotify /Muse (Meta))

But perhaps the war against AI is all for naught? Because when unveiling its new AI tag system, Qobuz also shared some statistics on this kind of 'music' (word used lightly), which recontextualize the whole thing.

Case in point: apparently only 0.38% of streams on Qobuz are from AI-generated tracks. Yes, less than half a percent. For every 263 streams, only one comes from an AI track. If all the streams were represented by the population of the US, team AI would just about fill up Dallas.

There's more: over a third of all AI albums receive not a single listen. Not even from their creator. That's about four million songs, apparently, all of which are created just to take up space (and have been removed from Qobuz's library, so if you missed them, it's too late).

And if that wasn't enough, apparently 60% of all AI-music is demonetized by Qobuz's anti-fraud systems. This is based on the brand's AI Charter, unveiled in February, which detects AI music created solely for financial gain.

Qobuz is the original hi-res music service and as the connoisseurs' choice (devoid of many extra AI add-ons), one could argue that very few users are hitting up Qobuz for AI tracks, but still, the figures are telling. According to these Qobuz stats, you're largely all avoiding AI slop — well done you, take a pat on the back — and sticking to real music made by real people. Well, mostly. Looking at you, 0.38%...

Artificial intelligence has become a significant area of investment for UK businesses. More than £6 billion of new AI-related investment was announced during London Tech Week in June, while the UK remains home to the largest AI sector in Europe and the third largest globally.

From customer service and knowledge management to software development and internal operations, organizations are looking for places where AI tools can improve productivity, decision-making and business performance.

But as investment accelerates, another gap is becoming harder to ignore: organizations are often scaling AI faster than their ability to measure, govern and explain its value. That matters when CIOs and CFOs are increasingly being asked not simply whether AI is being adopted, but what the organization is getting in return.

As businesses move from individual copilots towards agents embedded across workflows, the economics become more complicated. A user making a single prompt is relatively easy to understand. An agent may make multiple model calls, retrieve information, invoke tools and take actions to complete one task.

Depending on the platform and pricing model, that can introduce additional consumption, infrastructure and oversight costs. CIOs therefore need to understand not only where AI has been deployed, but what it is doing, what it costs and whether the outcome justifies that cost.

The not-so-hidden cost of AI

AI investment is increasingly being scrutinized in the same way as any other major technology investment. The difficulty is that measuring its return can be unusually complex.

Usage may be distributed across departments, applications, models and workflows, while the benefits can range from time saved to improved quality, reduced risk or increased revenue. Without agreeing what success means first, organizations can end up measuring activity rather than value.

That becomes difficult when organizations expand AI without first defining where it sits in the workflow, who owns the outcome, what success looks like and how costs will be measured. Spending can become fragmented across licenses, models, infrastructure, platforms and consumption-based services, with no single view of whether those investments are delivering value.

The scale of the challenge is becoming visible. Research commissioned by Emergn estimates that large UK businesses lose £67 billion annually across transformation and AI initiatives that fail to deliver. Separately, a Censuswide survey of 500 senior UK decision-makers found that just 31% of businesses already using AI reported a positive return on their investment.

Governance is part of that measurement challenge. A 2026 ShareGate survey of 851 IT leaders across seven countries found that cost visibility was the most commonly cited barrier to measuring AI ROI, identified by 51% of respondents, followed closely by governance complexity at 47%. The challenge isn't simply knowing what AI costs. It's connecting that cost to the use case it supports, the information AI interacts with and the outcome it creates.

Much of the AI debate to date has focused on model selection, skills and productivity. But as adoption spreads, another gap is becoming visible: confidence in governance does not always match what happens in practice.

The same study found that 93% of IT leaders believed their Microsoft 365 governance was ready to support AI responsibly, yet 29% reported that AI tools had surfaced sensitive internal data that should not have been accessible. Another 8% weren't sure whether it had happened at all.

Those gaps carry costs as well as risk. Duplicated tools, additional validation, rework, security investigations and time spent establishing whether an output can be trusted all create a hidden tax on AI adoption. For CIOs trying to demonstrate value, reducing that friction starts with making AI usage more visible, accountable and measurable.

How organizations can regain control

Good governance doesn’t begin and end at procurement. Knowing how many licenses have been purchased and where they have been assigned is useful, but regaining control requires a broader view: visibility into how AI is being used and what it costs, clear ownership of the outcomes, and a well-governed information environment for AI to work from.

Clear ownership matters just as much. As AI becomes embedded in business processes, responsibility can easily become fragmented across IT, security, business teams and individual employees. That makes some basic questions surprisingly difficult to answer: Who owns the outcome? Who monitors the cost? Who decides whether a use case should scale, change or stop?

Cost governance is only part of the picture. Organizations also need to improve the information environment in which AI operates. That means reducing redundant and outdated content, managing access appropriately and helping employees and AI systems find authoritative sources.

Cleaner, better-governed information does not guarantee a correct AI response, but it can reduce ambiguity and make reliable grounding easier. That can mean less time spent searching, validating and reworking outputs.

Employees have a role here as well. Clearly distinguishing drafts from approved material, keeping trackers and priorities current, recording decisions and maintaining authoritative sources all make organizational context easier for people and AI to interpret. Where organizations use AI meeting assistants or similar tools to capture context, those tools should be subject to the same privacy, retention and access controls as the information they create.

The question for leaders, then, is no longer simply whether AI is worth the investment. It is whether they have enough visibility and control to understand where AI is creating value, where it is creating cost and what they should do differently as a result. AI investment is likely to continue, but under different expectations.

Deployment alone is not evidence of value, and governance is becoming more than a risk-management exercise; it is increasingly part of the business case. Leaders need to understand what AI costs, who is accountable for its outcomes, whether the information supporting it can be trusted and what measurable benefit it creates.

The organizations best positioned to scale will not necessarily be those deploying the most AI, but those that can explain what it is doing, understand what it costs and make informed decisions about where it belongs.

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Since 1998, we've been enjoying the feature films and TV shows of one Guy Ritchie. A man who arguably defined the British gangster sub-genre, cult hits like Snatch and Lock, Stock and Two Smoking Barrels have stood the test of time.

Fast-forward to 2026, and streaming hits like Netflix's The Gentlemen and Paramount+'s MobLand are all anybody wants to talk about... and rightly so. And that's all without scratching the surface of the projects Ritchie has worked on in between.

But can you fill in the gaps? I've created the ultimate quiz for any and all Guy Ritchie fans, focusing on his feature-length movies and TV shows over the last three decades.

I didn't say it was going to be easy, though... so do your worst.

Of course, all of this is up to the time of writing — we already know that we've got plenty more Ritchie projects to look forward to.

Young Sherlock season 2, The Gentlemen season 3 and MobLand season 3 have all either been greenlit or are in development. There's a few more titles to add to this list... but that would be giving away the quiz questions.

Much like Ritchie-style gangster, I'm just not that nice.

• Disney has confirmed new price hikes for Disney+ and Hulu in the US
• However, the cost of three bundles has been frozen
• Fans in the UK, Europe, and Australia won't be affected for the time being

Disney has confirmed price hikes for all but three of its standalone Disney+ and Hulu plans, and bundles including both platforms, in the US — but there's no word on when other nations might be hit by similar rises.

Yesterday (September 23), Bloomberg reported that the entertainment giant was about to increase the cost of signing up for a subscription for the sixth time in as many years.

Per Bloomberg's sources, the biggest markup would see the Hulu-Disney+ Premium (ad-free) bundle go up by 13% to $21.49 per month. That means new and current users would have to pay an additional $2.50 every 30 days. Meanwhile, the cost of numerous other standalone tiers and bundles would go up by as little as $0.50 or as much as $3.00.

The latest price hikes come as Marvel fans prepare for Avengers: Doomsday's arrival with another MCU movie marathon (Image credit: Marvel Studios)

Approached by TechRadar for comment, Disney acknowledged that Bloomberg's report was factual.

However, the studio was keen to stress that three of its bundles, including its cheapest offering — the Hulu-Disney+ bundle (with ads) experience — would not be subject to price increases.

Disney added that, compared to its rivals raising the cost of their standalone ads-based tiers by 13%, it had only done so by 4%. Finally, the House of Mouse attributed the price hike to investing in the user experience by way of new technology, features, and back-end improvements.

For reference, here's a full breakdown of every price rise or freeze across Disney's myriad streaming service offerings in the US:

• Disney+, Hulu Bundle (with ads) — staying flat at $12.99
• Disney+, Hulu Bundle Premium (ad free) — increasing +$2 to $21.99
• Disney+ and Hulu standalone plans (with ads) — increasing +$0.50 to $12.49
• Disney+ and Hulu Premium standalone plans (ad free) — increasing +$2.50 to $21.49
• Disney+, Hulu, ESPN Select Bundle (with ads) — increasing +$2 to $21.99
• Disney+, Hulu, ESPN Select Bundle Premium (ad free) — increasing +$3 to $32.99
• Disney+, Hulu, ESPN Unlimited Bundle (with ads) — staying flat at $35.99
• Disney+, Hulu, ESPN Unlimited Bundle Premium (ad free) — staying flat at $44.99

Why the UK, Europe, and Australia is immune to the Disney+ price hike — for now

Disney+ users outside of the US should steel themselves for further price rises, too (Image credit: Ivan Marc/Shutterstock)

Crucially, UK and European subscribers appear to be temporarily immune to these price increases.

Responding to a separate request for comment from TechRadar, a Disney+ UK spokesperson told me: "We don't have anything to share on UK or European pricing at this time."

However, in previous years, UK and European fans have seen the cost of Disney+ climb just weeks after their US counterparts were slapped with the now-annual price hike. I wouldn't be stunned, then, if account holders in these regions are forced to pay more for two of the world's best streaming services in the weeks ahead.

Australian Disney+ users were hit by a price hike in April, so it's unlikely — but not completely out of the question — that they'll experience another one in due course.

Regardless of whether you've been hit by this latest price hike, it's been a rough few days for Disney+ users all around.

The week began with Disney having to placate furious fans over inaccurate reports that its ad-free Disney+ tiers would start showing ads. The dust hadn't settled on that story before fans learned that Marvel TV show Daredevil: Born Again would end after its forthcoming third season on Disney+, too.

I'm not superstitious but, as the saying goes, bad news comes in threes. Let's hope that this is the third and final piece of unwelcome news that Disney fans have to deal for a while, then.

• Revolut reveals new payment method which just needs a smile
• Facial recognition technology will help identify Revolut customers
• Technology could help protect SMBs from losses caused by tech outages

If you've ever been about to pay for something in a shop and suddenly realised you've misplaced your wallet, Revolut may have the answer to help avoid any more embarrassing situations.

The payments giant is launching Revolut Pay with Smile, the UK’s first in-store facial recognition checkout, meaning customers can pay with a glance or even a smile - no need for a wallet or even a phone.

The move looks to make sure that UK small businesses don't lose money from payment terminal issues, whether hardware or software-related, offering a new way to accept payments.

Pay with Smile

We were invited along to try out the new Revolut Pay with Smile at a Kiss the Hippo Coffee shop in central London, where customers could try out the new technology.

Guests who paid in-store with a smile were able to order from a special Revolut menu, with speciality coffees at £1 - a bargain in today's market.

We gave it a go, and found the process to be pretty painless - much like authenticating yourself on a phone app, or having your photo taken at passport control, it was fairly quick and smooth to get through - and the coffee wasn't bad either.

All it took was a quick facial scan, and the system verified the payment in a matter of seconds - quicker than many contactless payments, we'd say.

Users will have to be existing Revolut customers, as the system uses advanced facial technology to verify the user's identity against the selfie ID checks they added when first signing up to Revolut to authenticate and process a payment securely.

Powered by the new Revolut Register, a modular, two-screen register designed to bring together payments, banking, and floor operations, Pay with Smile offers 0% processing fees for merchants, a huge boost when overhead costs are higher than ever.

Transactions are authenticated with end-to-end encryption managed inside the Revolut app, with no personal data stored by merchants

Revolut Register is available now with a special 50% discount for £349.50 + VAT (RRP: £699 + VAT) on a merchant's first terminal until 31st December 2026 for both new and existing customers.

Adidas' has collaborated with Pokémon and the results are far wackier than I was expecting. The new lineup of themed sneakers ranges from subtle (pearlescent lilac Handball Spezial shoes) to downright inconvenient (orange Superstar Vintage sneakers with a giant orange wing protruding from one side). But can you tell which shoe goes with which Pokémon?

You might be looking below at that furry yellow sneaker with ears and thinking this will be a cake-walk, but they're not all the most obvious choices you might expect for a big Adidas collab. As you get further down, there's little more than a color scheme to go off. Okay, yes, the character outlines are visible if you look closely… but maybe that's cheating?

Scroll down to check out the full range, and let us know how you did in our poll at the bottom.

Adidas X Pokémon: US range

Hop down to the UK range

Adidas X Pokémon Superstar II Mid Shoes

Adidas X Pokémon Superstar II Shoes — yellow

Adidas X Pokémon Superstar Vintage Shoes

Adidas X Pokémon Superstar II Shoes — white

Adidas X Pokémon Superstar II Shoes — red

Adidas X Pokémon Handball Spezial Shoes

Adidas X Pokémon Adistar Control 5 Shoes — purple

Adidas X Pokémon Adistar Control 5 Shoes — green

Adidas X Pokémon Samba OG Shoes

Adidas X Pokémon: UK range

Adidas X Pokémon Superstar II Mid Shoes

Adidas X Pokémon Superstar II Shoes — yellow

Adidas X Pokémon Handball Spezial Shoes

Adidas X Pokémon Superstar II Shoes — white

Adidas X Pokémon Superstar Vintage Shoes — orange

Adidas X Pokémon Superstar II Shoes — red

Adidas X Pokémon Superstar II Shoes — orange

Adidas X Pokémon Adistar Control 5 Shoes — purple

Adidas X Pokémon Adistar Control 5 Shoes — green

Adidas X Pokémon Samba OG Shoes — purple

Our 5K Test System

Motherboard: Asus TUF Gaming B550M-Plus WiFi II
Processor: AMD Ryzen 7 5700X3D
CPU Cooler: Thermalright Frozen Prism240 Liquid Cooler
GPU: Asus TUF GeForce RTX 4080 Super OC
Storage: 1TB Samsung 980, 4TB Lexar NM790
Case: Lian Li A3 m-ATX
RAM: Corsair Vengeance 32GB (16x2) DDR4
PSU: Seasonic 750W
Monitor: LG 39GX950B-B

I can't stress enough that Control Resonant is an absolute marvel in terms of visual enjoyment. Remedy Entertainment has crafted one of the most immersive visual experiences in gaming, doubling down on its predecessor's trippy, psychedelic, and mind-bending nature, and taking it to a new level using Nvidia's path tracing.

Putting my Nvidia GeForce RTX 4080 Super to the test, I ran Control Resonant on LG's 39-inch 5K2K OLED monitor, and I was pleasantly surprised by the significant enhancement to every detail on screen (albeit it did leave my GPU rather toasty).

At a 5120 x 2160 display resolution which is a 21:9 aspect ratio, you're getting 33% more pixels than a regular 4K gaming monitor at a 16:9 ratio, so the demand on the GPU is harder than most can handle — and even though Control Resonant was cooking my GPU, the frame rate was quite surprising.

Control Resonant with path tracing enabled (Image credit: Remedy Entertainment)

With DLSS 4.5 Quality and Frame Generation enabled, and the high graphics and high ray tracing presets, performance remained fairly consistent within the high 50fps to low 60fps range. At 5K2K resolution, that's very reasonable, even if Control Resonant relies on Frame Generation to keep the gameplay smooth.

Dropping DLSS down to Performance mode pushed the frame rate to the high 80fps mark, and it's worth noting that it remained consistent even in moments of intense combat with tons of foliage and objects involved.

It's worth noting that the graphics with standard ray tracing are still fantastic, and the high (or even the medium) preset is likely the best route for any PC gamer who is using a low- to mid-range GPU (with Frame Generation). Lighting in all areas, specifically those where the Hiss is present (the really bright red zones), is phenomenal, and frankly, that applies to the experience without any ray tracing at all.

Path to victory

(Image credit: Remedy Entertainment)

However, the star of the show is path tracing, which can be enabled by switching to the ultra ray tracing preset. I instantly knew my GPU was in for a rough ride once its temperature shot up to nearly 80C — but that's to be expected when running path tracing on a 5K2K display.

With DLSS Performance and Frame Generation enabled, I was able to achieve a solid 60fps in most scenarios, with occasional dips into the high 50s during traversal and combat. This aligns well with Remedy's system requirements for Control Resonant, which require an RTX 5080 for 60fps at 2160p using DLSS Performance, as the RTX 4080 Super is relatively close to this current-gen GPU for performance.

Realistically, this setup is out of the question for most gamers, as it will cost around $3,000 / £3,000 (or potentially more). LG's display is very expensive, sitting at $1,799.99 / £1,499 (on sale I should note), but an Alienware AW3926QW 5K2K alternative might help lower the cost.

The RTX 4000 series is discontinued, but pricing for anything equivalent to the RTX 4080 Super in the current-gen line-up (an RTX 5070 Ti or RTX 5080) would cost at least $800 (much more for the latter GPU), and then you need to add the cost of the other PC parts.

Handheld gaming PCs are still expensive, but more reasonable than an entire new PC build — and I tested Control Resonant on my Lenovo Legion Go S Z1 Extreme. That portable managed a solid 40fps on its handheld preset, and 70fps when dropping the resolution to 900p and enabling FSR Balanced with frame gen.

Overall, running Control Resonant at 5K2K is very demanding for any gaming PC, as expected, but I walk away shocked that it's even remotely possible given how much it elevates the gaming experience.

• The Z5 II C is a lighter version of the full-frame Nikon Z5 II, without a viewfinder
• Prices start at $1,399 / £1,349 / AU$2,399, on-sale date mid-October
• It's available in black or black/silver colorways, and numerous lens kit options

Nikon redefined entry-level full-frame cameras with the Z5 II, which scooped our Camera of the Year 2025 award. Now the company is upending the notion that full-frame is just for pros with its most affordable and compact model in this format yet, the Z5 II C.

As its name suggests, the Z5 II C is a ‘compact’ version of the Z5 II, and the key difference is that it doesn’t have a viewfinder (and it has a single card slot rather than dual slots). This means the ‘C’ model is smaller, lighter and cheaper.

It still has a tough magnesium-alloy body with a chunky grip, is sealed for dust and moisture resistance, and packs a healthy 3.2-inch, 2.1m-dot vari-angle LCD, all carried over from the Z5 II. The cameras share identical features too; the same 24.5MP full-frame sensor with image stabilization that’s rated up to 7.5EV.

Nikon UK's Training Specialist Ricci Chera briefed me on the camera ahead of its September 24 announcement and mid-October on-sale date, emphasizing that the Z5 II C is about choice, offering certain users the “benefits of full-frame, without paying for something they’re never going to use [a viewfinder]”.

Is Nikon onto something here? Is the $1,399 / £1,349 / AU$2,399 asking price enough of a gap to tempt first-time buyers, or sway them from the Z5 II?

NikonNikonSo, full-frame is for beginners now?

The low £1,349 / AU$2,399 asking price of the ‘C’ version seems pretty appealing, especially given the spec and features you're getting: the Z5 II C has the same sensor as the Z5 II and Nikon’s latest processor, while its subject-detection autofocus can recognize subjects even when they take up as little as 3% of the frame, and which is low-light sensitive to -10EV (with a new ‘fish’ detection mode added — that’s a first),

There's also 14fps with a mechanical shutter (30fps electronic) and 4K video with 12-bit N-RAW internal recording, and much more. Besides the Lumix S9, I can't think of a better-value full-frame camera, and not one that launched for such a low price.

The price and compact size are the major selling points of this full-frame model, which Nikon says is about offering users "choice" — the pricier and larger Z5 II with a viewfinder and dual card slots, or the cheaper and smaller viewfinder-less Z5 II C. I get the logic.

However, I’d still stump up the extra cash for the Z5 II — its viewfinder is bright, big and immersive, it has the extra card slot, and I personally don’t mind the extra size and 100g in weight (the Z5 II C is around 600g with card and battery inserted while the Z5 II is around 700g).

Video-first users and even smartphone upgraders who've never experienced a viewfinder might not feel the same way, and for them the Z5 II C could prove to be the wiser choice, and one of the hits of 2026. We'll bring you our review of Nikon's latest full-framer soon.

• $1.6 billion has been claimed by scammers impersonating police and government officials
• The FBI’s Internet Crime Complaint Center (IC3) received almost 61,000 complaints concerning such scams between January 2025 and July 2026
• Some scams targeted foreign nationals and immigrants, threatening to cancel passports or impose extradition, unless payment is made

Between January 2025 and July 2026, the FBI’s Internet Crime Complaint Center received almost 61,000 complaints concerning scams using police and government official impersonation tactics. As a result, around $1.6 billion is believed to have been scammed and extorted.

Tactics used by scammers included unsolicited phone calls and in some cases video calls, with victims losing an average of $26,000 per scam.

Particularly concerning is the targeting of foreign nationals, international students, and immigrant citizens, often with threats to cancel visas and home country passports. Incredibly, 10% of all losses were traced to a single scam, one that targeted fewer than 3% of the victims.

Foreign national victims

According to the FBI, the fake cop/fake government official scam has various angles, from alleging missed jury duty to threatening arrest due to circumstantial links to an alleged crime.

The demand from the scammers, inevitably, is payment.

Making a commitment to extreme lengths of scamming and extortion, the criminals took things to a new level when it came to targeting victims. International students, visiting foreign nationals, and other immigrant citizens were given special treatment. Not only were they threatened with extradition, there was also the implication of victims losing their home country passport.

To convince the target, scammers built actual studio sets, donned uniforms or suits, and appeared in video calls to the victims, who were convinced they were talking to foreign law enforcement agents or US-based diplomats. Creating the illusion of officialdom to sell the scam, victims paid whatever necessary to stay in their adopted country.

How to spot the scam

It is important to note that not all fraud of this type takes place in the US. These may be online or offline, but the so-called fake cop scam is an international criminal phenomenon. So, how do you avoid it?

We’ll assume you’ve answered a call inadvertently rather than having spam calls blocked (that should be set already).

First, remain calm. These situations are designed to impose stress and heightened anxiety. Scammers rely on these factors to cloud their victim’s judgement and force the narrative they are selling (“you missed jury duty”/“your presence in the country is illegal.”)

Second, it is vital to request credentials. Failure to provide these is the first red flag that the person communicating with you is not what they seem. That’s your cue to end the conversation.

Third, check the credentials. It doesn’t matter how long this takes – a legitimate caller will not mind waiting for you to do the necessary background check, even if it means them calling back.

Finally, and most importantly: neither law enforcement, security services, nor the FBI will demand money. If that is happening, it’s time to end the call.

It’s not a Tamagotchi, but Mark Zuckerberg’s one more thing is just as cute and hopefully much more functional. Announced at the very end of Meta Connect 26 keynote — after the Meta VR Glasses and Meta Ray-Ban Audio — was Muse Charm.

A tiny silver square with a screen on the front and thicker black bezels, central to the experience is the display that shows off your custom Muse. It’s probably more of a squircle and had what looks like a wrist strap dangling from the bottom, seemingly showing off easy portability. Distinctly, you don't wear it, and since we didn't see buttons, it's a touchscreen, maybe an OLED or AMOLED.

Judging from the on-screen renders, it had a microphone on top, so you could communicate with your Muse from anywhere, essentially putting the already very popular Muse assistant quite literally in the palm of your hand.

@techradar

♬ original sound - TechRadar

Mark Zuckerberg was quick to note that Muse Charm is not ready just yet, but the hope is it will ship by the holidays. It’s also a brand-new device category for Meta: a true AI wearable distinct from glasses, focused entirely on Muse's capabilities and future roadmap.

Will it follow the Rabbit R1 or the Humane AI Pin and fail? That remains to be seen, but Muse is already proving powerful as a software-only, ultra-customizable personal AI assistant. Packaging that into a wearable, hopefully an affordable one, maybe cheaper than glasses, could be a winning package.

(Image credit: Jacob Krol/Future)

It was announced shortly after the news that Muse would be arriving on Meta Glasses, affording it multi-modal capabilities of both voice and seeing the world around you. Additionally, the Muse App for macOS will be getting computer use and that will allow the AI that you can name whatever you like to complete tasks for you.

The Muse Charm doesn’t appear to be multimodal and, apparently, avoids the Looki route, as it lacks a camera.

Much more to come, but for now, stick with TechRadar for all the news from Meta Connect.

• Two artificial whiskers give this tiny drone a working sense of touch
• Pressure sensors at the whisker base detect surface contact instantly
• Onboard software processes tactile data using only 34 kilobytes of memory

A research team from Delft University of Technology in the Netherlands has developed a tiny drone that uses artificial whiskers to navigate where conventional sensors struggle.

The system relies on physical contact rather than cameras or satellite positioning, allowing the aircraft to detect nearby surfaces through touch.

The researchers designed the technology for drones weighing below 100 grams, where adding substantial sensing equipment can quickly consume available capacity.

Tiny whiskers give the drone another way to sense surroundings

The device carries two slender filaments near its nose, angled upward and connected to miniature pressure sensors underneath.

When either filament touches an object, pressure changes provide information that helps the aircraft estimate its position relative to nearby surfaces.

That information allows the drone to move around obstacles, maintain contact with structures, and construct a basic representation of surrounding spaces.

The approach takes inspiration from rodents and other mammals, which use facial hairs to move through confined environments with limited visibility.

“Here, we aim to equip drones with rich tactile sensing — not for manipulation in the air, but for a novel concept of tactile navigation,” said Salua Hamaza, Associate Professor of Aerial Physical Interaction and Embodied Intelligence.

The system needed to be lightweight, process rapidly, and consume limited energy before tactile navigation could become practical aboard small aircraft.

The sensing system runs on only 34KB

A major hurdle was airflow, since passing wind can easily disturb whisker readings and confuse the pressure sensors beneath them.

To solve this, the researchers wrote a lightweight processing program that separates turbulence from genuine surface contact in real time with millimetric precision.

The complete onboard software occupies just 34 kilobytes of memory, keeping the computational requirements unusually low for an autonomous sensing system.

Traditional navigation software built for larger drones typically demands considerably more computing power than this compact whisker-processing system requires today

“We wanted to show that touch does not have to come at the cost of size or computational power,” said Chaoxiang Ye, a PhD candidate and researcher at Deft.

The small size allows the drone to interpret environmental information without depending on external processing.

The approach will not suit the fastest drones, but for small rescue units, sensing through touch may prove genuinely valuable.

This device is especially useful for environments where smoke, dust, darkness, or damaged infrastructure could interfere with cameras and other optical equipment.

One potential application of this drone is in collapsed buildings where rescue operations can prove to be difficult because of instability and tight spaces, and regular aerial sensing may be unreliable

Small drones could enter restricted spaces ahead of human responders, using physical contact to gather information about nearby structures and possible pathways.

The system could also provide another sensing method when GPS signals are unavailable or visual information becomes difficult to interpret.

Via TomsHardware