News
- The European Union is working on tech repairability rules...
- ... except some 'wet appliances' are now exempt now
- This puts 'devices that are worn on the body' in a very gray area…
- …and yes, that probably means AirPods
E-waste worriers (and warriors) like me have been watching the creation of EU regulations with glee, since a selection of them will require tech manufacturers to put replaceable or repairable batteries in their gadgets. But now, there are a few new key exceptions to the rule.
Some major new clarifications, listed on the European Commission's website, mute the positive impact of replaceable, upgradable tech. These exceptions mean that wearables including smartwatches and fitness trackers don't have to be repairable — and I think it's ironic that these are precisely the kinds of gadgets you're more likely to throw out and replace, rather than try to repair.
The EU has moved these products to its "wet appliances" category, for gadgets which can't be kept repairable for safety reasons (ie, because they deal with water). However, no reason was given for why wearables, especially ones not designed for wet use (based on IP ratings) are now exempt.
While the EU's rule change doesn't actually mention AirPods (or earbuds in general), what the wording essentially means is that wireless earbuds, Apple watches and smart glasses reportedly also fall into this specific wearable category. Smart glasses are, to hammer home the point, really not designed for wet use — but their wearer might get caught in a rainstorm by accident, say.
There are two key pieces of information regarding the classification of small devices exempt from adhering to the EU's battery rules, as published in the recent guidelines. The first is that "Wearable devices are portable electronic devices that are worn on the body and often have sensors and connectivity to collect and transmit data. Examples of wearables include smartwatches, fitness trackers, smart glasses or other electronic devices integrated into clothing and other accessories".
The second? It's to do with those IP ratings for water- and dust ingress and whether the addition of a replaceable battery is "compromising safety". It states that if "there is evidence in the product documentation when placing the product on the market that battery replaceability and removability by end-users would compromise the safety of the user or the appliance", the product may be exempt.
So your AirPods 4 with ANC will likely no longer need to feature replaceable batteries because of the EU, including the case itself.
An Apple a day keeps the e-waste away(Image credit: Future)It's no secret that e-waste is a massive issue: according to the United Nations, the amount of discarded electronics we produce is rising five times faster than our ability to recycle it.
It's why the EU recently pushed through rules to ensure tech is repairable. A pair of headphones that break might just need a new battery; you don't need to buy a whole new pair.
Apple users have been begging for removable batteries in iOS devices, especially AirPods, as we argued back in 2024. AirPods are the best-selling earbuds in the world (and it's not even close), so at least some of them end up in landfill when they stop working, despite Apple's conviction to recycle any that get returned to its stores (Apple doesn't offer any trade-in value for AirPods, but dropping them in for recycling is free).
I believe it's important for all tech to be repairable (see B&O's long-running 'Cradle to Cradle' approach, even buying back and refurbing its own kit, to give it a new life), but doubly so for the ubiquitous kind.
Apple's way is of course a viable way to keep your eco credentials, while disposing of unwanted buds, but it's not the best way. That would be replaceable batteries, small and fiddly though it might be — and it is possible, because Fairphone has been doing it for a little while.
As per the mantra drilled into school kids: reduce, reuse, recycle, in that order. Reusing old earbuds, by repairing them, is much better for the environment than recycling them, and so it's a shame that the EU is giving out exemptions like candy.
If you have any broken tech, be it headphones, earbuds or something else entirely, a repair is always your first port of call before disposing of your existing ones. It's cheaper and quicker than buying new tech and, most importantly, is better for the planet. And if you do need to buy new tech, consider online or physical refurb shops such as Back Market, which repair others' gadgets.
- Aston Martin just revealed the Dreadnought, a digital-only military SUV designed exclusively for Call of Duty: Modern Warfare 4
- It features rugged armor plating and a powerful V12 engine
- The vehicle will feature in the game's DMZ mode and the free-to-play Warzone battle royale
Legendary luxury car manufacturer Aston Martin has just revealed the Dreadnought, a heavily armored all-wheel drive SUV said to offer "supercar levels of performance" and "elite tactical performance" on the battlefield.
Its Chiltern Green painted body combines rugged military armor plating with advanced aerodynamics to deliver a powerful combination of both speed and protection, while the interior includes luxury elements like an Oxford Tan leather dashboard and golden gear lever.
Under the hood, it boasts a mammoth V12 engine and comes with a unique range of combat-oriented features such as dedicated weapons storage and reserve fuel tanks.
Its name is intended to conjure images of the HMS Dreadnought, a famous 20th-century British vessel that was so significant it spawned a whole new class of battleship.
Activision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinActivision / Aston MartinThe catch? It's not a vehicle that you will actually be able to buy; it's a digital-only concept that's been designed exclusively for the upcoming video game Call of Duty: Modern Warfare 4.
According to the car maker's chief creative officer, Marek Reichman, designing the vehicle posed a "not inconsiderable challenge" to reimagine what Aston Martin could be in a virtual world where "the only limit is imagination."
Although the car is fictional, Reichman said that it was imagined as "a vehicle living in the real world" throughout the design process, and therefore "feels genuinely real."
You'll be able to go behind the wheel of the Aston Martin Dreadnought in Modern Warfare 4's DMZ mode when the game launches on October 20, 2026. It will also appear in the free-to-play battle royale Call of Duty Warzone.
Fans attending the upcoming Fanatics Fest in New York will be able to see a full-size model of the car in the flesh at the Call of Duty stand.
- Zoom patches critical improper input validation flaw in multiple Windows clients and SDKs that allowed remote account takeover
- Additional high‑severity bugs fixed include CVE‑2026‑53410 (TOCTOU race condition), CVE‑2026‑53409 (privilege management flaw), and CVE‑2026‑53411 (input validation issue)
- All vulnerabilities were found internally, with no evidence of exploitation; users are urged to update Zoom Workplace and related products to the latest versions
Zoom has patched a critical-level vulnerability in multiple products that allowed threat actors to take over people’s accounts remotely.
In a security advisory, Zoom said it fixed an Improper Input Validation bug plaguing Zoom Desktop Client for Windows (before version 7.0.0), Zoom VDI Client for Windows (before versions 7.0.10, 6.6.15, and 6.5.18), and Zoom Meeting SDK for Windows (before version 7.0.0). It did not go into more details on how the flaw works.
The bug is now tracked as CVE-2026-53412, and was given a severity score of 9.8/10 (critical). To fix it, users are advised to update their software to the newest version.
More vulnerabilitiesWhile certainly the most dangerous one, this is not the only bug Zoom recently addressed. The company also fixed a handful of less severe vulnerabilities, including a time-of-check to time-of-use (TOCTOU) race condition bug affecting Zoom Workplace for Windows before 7.0.5, Zoom Workplace VDI Client and VDI Plugin before 6.5.17/6.6.14, Zoom Rooms for Windows before 7.0.5, and Remote Control for Zoom Contact Center before 7.0.0. This bug is tracked as CVE-2026-53410 and was given a “high” severity score of 7/10.
Other notable mentions include CVE-2026-53409 (a high-severity improper privilege management flaw in Zoom Rooms for Windows before version 7.1.0), and
CVE-2026-53411 (a high-severity improper input validation flaw affecting the Zoom Workplace VDI Plugin for Windows before version 6.6.14).
Zoom found all of these vulnerabilities in-house and says there is no evidence that any of these were abused in real-life attacks in the past.
Zoom Workplace (the company’s all-in-one collaboration platform) offers video meetings, team chat, phone, email, calendar, scheduling, whiteboards, and other productivity tools. It is an evolution of the original Zoom Meetings app which now competes with platforms such as Microsoft 365 and Google Workspace.
Via BleepingComputer
In the summer of 1995, the future of computing briefly seemed to belong to Netscape.
Netscape went public that August, barely sixteen months after it had been founded. Its stock doubled on the first day. The company had no empire of hardware, no installed operating system, no grip on the office desktop. What it had was a window into a new world.
Open Navigator, type an address, and the Internet appeared with a little throb of electricity. The browser did not feel like an application. It felt like a passage out of Microsoft's world.
Microsoft noticed.
The battle that followed was called the browser wars, a phrase that makes it sound tidier than it was. Really, it was a fight over who had the right to stand between the user and the next era of computing.
Netscape believed the browser would make the operating system less important. Microsoft believed that anything capable of making Windows less important needed to become part of Windows, preferably yesterday.
By the end of the decade, the company that had introduced so many people to the Web was no longer the Web's gatekeeper. It had been out-distributed, out-bundled, and finally absorbed into a stranger corporate afterlife.
A familiar temptationThere is a familiar temptation now to ask which artificial intelligence company is "the Netscape of AI." The answer usually offered is OpenAI, and the comparison is not wrong. ChatGPT did for artificial intelligence what Navigator did for the Web. It turned a technical architecture into a public experience. It gave the future a text box.
But the more important question is this: Who is today's Microsoft? Who understands that the winner is often the company that owns the default?
Every platform shift begins with a miracle and ends with a map of choke points. The miracle is what users remember. The choke points are where the money goes.
The early Web was sold as an escape from gatekeepers. It created new ones. Search. Browsers. Marketplaces. Mobile operating systems. Cloud platforms. Social media. The AI era is being sold with the same democratic glow.
And yet the deeper stack is already hardening. It is made of chips, power contracts, data centers, model weights, enterprise identity, workflow data, cloud credits, procurement channels, and the small tyrannies of default settings. The romance is in the chatbot. The control is somewhere colder, louder, and much more expensive.
That was true in the nineties, too. The Web looked like a page. The winners understood it was a stack.
The danger to OpenAIOpenAI is the obvious Netscape figure because it supplied the first mass-market revelation. Before ChatGPT, artificial intelligence was a research field, a back-office tool, or a phrase executives used when they meant analytics with a larger budget. After ChatGPT, it was something anyone could talk to.
People underrate the power of the first interface that makes a new technology feel inevitable. Netscape did not invent the Internet. It made the Internet feel reachable. OpenAI did not invent the transformer. It made the transformer feel conversational.
But Netscape's story is not a founder myth. It is a warning label.
Netscape had the user's excitement but not enough control over distribution. Microsoft had the operating system. It could place Internet Explorer where users already lived. It could make the browser free. It could turn a product category into a feature.
The lesson was simple: if your rival owns the layer beneath you, your brilliance may become their menu option.
OpenAI is better protected than Netscape was, but not safely protected. It has a huge brand, astonishing usage, and deep ties to Microsoft. It also has the curse of being expensive in a way software companies used to avoid. Each improvement requires compute, chips, talent, energy, and capital. The old software dream was scaling with almost no marginal cost. AI can't do that.
That is why OpenAI's partnership with Microsoft is both strength and vulnerability. Microsoft gives it cloud computing infrastructure, enterprise access, and capital. Microsoft also sits close enough to learn from it, package it, hedge around it, and sell AI into the places where people already do work.
If Netscape's problem was that Microsoft stood underneath it, OpenAI's problem is subtler: Microsoft stands underneath it, beside it, and increasingly in front of the customer.
Netscape had the dazzling demo. Yahoo had the traffic. AOL had the subscribers. None of that was enough. The durable winners were the companies that turned their software layers into a control point and a tollbooth.
Nvidia may be doing exactly that.
The rise of NvidiaIn the nineties, Intel was the metronome inside the personal-computer boom. Microsoft owned the software platform. Intel owned the pace of the machine.
Nvidia occupies a similar place in AI, but the analogy understates the ambition. Nvidia is not merely selling chips into a boom. It is selling the industrial base of the boom: GPUs, networking, software libraries, developer habits, and a vision of the data center as an AI factory.
Every major AI player is both Nvidia customer and Nvidia escape artist. Google has TPUs. Amazon has Trainium. Microsoft is developing its own silicon. Everyone wants an alternative. The problem is that wanting one does not create an ecosystem.
Nvidia's position today may be the purest example of moving up the stack from below. A chip company becomes a systems company. A systems company becomes a software company. A software company becomes a developer environment. A developer environment becomes a tax on ambition.
For now, Nvidia is the toll collector.
The AI market will not resolve into one winner. Platform shifts rarely do. The Web did not produce one winner. It produced layers of power. Microsoft kept the desktop. Google won search. Amazon won commerce and cloud. Apple won mobile hardware and the app economy. Meta won social attention.
AI will do the same.
Microsoft may become the default enterprise AI company, not because every Copilot is brilliant, but because Microsoft sits where work already happens. Nvidia may remain the dominant compute toll collector. Amazon will likely win much of the infrastructure layer. Google must reinvent search while defending it. Meta will use AI to extend attention. Apple may yet turn personal AI into a device-native experience.
The likely losers are the companies attached to the wrong layer.
The changing landscape of AIIn the nineties, AOL looked invincible because it owned access. Broadband made that access less special. Yahoo looked inevitable because it owned attention. Search made that attention less decisive. Netscape looked revolutionary because it owned the browser. Microsoft made the browser a dependency of the operating system.
In AI, the same demotions will happen. Some model companies will become features. Some application companies will become demos. Some incumbents will decorate old products with AI and call it transformation, which is the corporate version of putting a spoiler on a minivan.
The mistake, in every technological boom, is to confuse the moment of wonder with the arrangement of power that follows it.
The wonder is sincere. The arrangement is not.
The early Web made people feel as if they had slipped the old gatekeepers. Then came the search box, the app store, the marketplace, the cloud account, the login, the subscription, the default. Each solved a real inconvenience. Each left behind a narrower path.
AI will likely travel the same road, only faster and with a larger electricity bill. It will begin as a conversation and mature into an administrative system for human intention: what we ask, what we buy, what we write, whom we trust, which choices are shown, and which never quite appear.
The future does not usually arrive wearing chains. It arrives offering to save time.
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The enterprise technology industry has a peculiar relationship with accountability. When it comes to cloud uptime, latency, and data security, we expect contractual guarantees, SLAs, and clearly defined remedies. But when it comes to AI-generated outputs, the actual content these systems produce, we've quietly accepted a different standard: best effort.
I've spent years in commercial and operational roles at companies like Gap, Amazon, and Door Dash / Wolt. In every one of those environments, product visuals weren't a marketing nice-to-have. They were infrastructure. A wrong color on a listing didn't just look bad; it drove returns. A missing ingredient on a food image wasn't an aesthetic issue; it was a trust issue that compounded at scale and was dangerous to our customers.
So when AI-generated images started entering enterprise workflows in earnest, I watched with real interest. The efficiency gains were compelling: the ability to generate, retouch, and adapt product visuals at a speed and scale that traditional studio workflows simply cannot match.
But something fundamental was missing from the enterprise conversation: accountability for outputs.
The gap between impressive and dependableThere's a difference between AI that produces impressive results in demos and AI tools you can stake commercial operations on. For enterprise buyers, that gap matters enormously.
Consider what happens when am AI-generated product image fails at volume. A wrong product color in a hero image doesn't trigger one return; it triggers thousands. A distorted shape on a fashion listing doesn't affect one conversion; it affects an entire category. The commercial exposure from visual inaccuracy compounds at scale in a way that individual errors simply don't.
Yet for most of the AI visual tools currently available to enterprise buyers, the contractual position on this exposure is essentially zero. You buy credits, you run images, and what comes out is what you get. If the output doesn't match the brief, you absorb the cost: in regeneration time, in quality control overhead, and ultimately in the downstream commercial impact of content that doesn't perform.
This isn't an indictment of the technology. AI-generated images have genuinely transformed what's operationally possible for enterprise visual production. But the commercial model hasn't kept up with the commercial reality.
Why ownership changes everythingThe reason most AI visual vendors can't offer meaningful output guarantees isn't reluctance; it's architecture. If you're building on third-party foundation models, you have no ability to evaluate, course-correct, or stand behind the quality of what those models produce at the output level. The accountability stops at the API.
The vendors who can make guarantees are the ones who own the full stack: the generation models, the evaluation models, and the remediation process. This is the structural distinction that makes contractual guarantees viable, not as a commercial gesture, but as something that can actually be operationalized.
When a proprietary fidelity evaluation model is running on every output before delivery, you have a mechanism for identifying failures before the client does. When you own the rater, the fixer, and the generation pipeline, you have the ability to correct those failures.
When you've run a feasibility check on a customer's actual catalogue before any commercial commitment, you know what the pass rate will look like in production.
That's the architecture that makes a guarantee meaningful: not a promise, but an auditable process with contractual teeth.
What contractual accountability looks like in practiceThe mechanics matter here, because "guarantee" can mean many things. In practice, an enterprise visual guarantee should do three things: define pass/fail criteria upfront based on the customer's actual brief; evaluate every output against those criteria before delivery; and trigger a clear remedy, regeneration or credit refund, when failures occur.
Critically, the criteria need to be specific. Product fidelity failures, an altered color, a missing ingredient, a distorted product shape, are measurable and contractually defensible. Subjective aesthetic preferences, a lighting angle, a background tone, are not. The boundary between these two things is where a real guarantee lives, and where vague commitments fall apart.
For enterprise buyers, this specificity is valuable in itself. It forces the conversation about what "quality" actually means for a given catalogue before procurement, rather than after. That clarity typically improves outcomes on both sides.
The accountability moment for enterprise AIWe're at a point in the enterprise AI cycle where the conversation needs to shift from what these systems can do to what vendors are willing to stand behind. Capability is no longer the differentiator; the market is full of capable tools. Dependability is.
For enterprise procurement teams, this means starting to ask harder questions. Not just "what's your accuracy rate?" but "what happens when it's wrong, and what are the contractual terms?" Not just "can you handle our volume?" but "what remedies apply when you don't meet the standard we've agreed?"
For the vendor community, it means recognising that the era of best-effort AI in enterprise contexts is ending. Buyers who are running tens of thousands of product images through AI pipelines need the same accountability from those systems that they expect from any other mission-critical infrastructure.
The goal in commerce was never the most beautiful image. It was always an image that sells, reliably, accurately, at scale. Enterprise AI that can guarantee that outcome is the next competitive frontier. The vendors willing to back their outputs contractually are the ones that will earn a place in enterprise infrastructure for the long term.
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