Children are reportedly bypassing online age-verification systems using methods as simple as drawing fake facial hair, raising fresh questions about whether current age-assurance technology is robust enough to protect young users online.

How Children Are Bypassing Age Checks

The issue was highlighted in a new report from UK online safety organisation Internet Matters, which surveyed more than 1,200 UK children and parents about online safety and age verification under the Online Safety Act.

The findings suggest that many children already understand how to bypass checks designed to block access to adult content, restricted social media features, and age-limited online platforms. The report found that 46 per cent of children believe age checks are easy to bypass, while only 17 per cent described them as difficult.

One of the more unusual techniques involved children drawing fake mustaches or facial hair using makeup pencils in order to fool facial age-estimation systems. Internet Matters stated that “children demonstrated a clear awareness of how to bypass age checks” and noted that drawing on facial hair was “reported as working in multiple instances”.

The report also found that around one-third of children admitted bypassing age checks entirely, including by entering fake birthdays, using someone else’s account, uploading photos of adults, or using VPNs to avoid restrictions.

Parents were also found to play a role in some cases. Internet Matters reported that 26 per cent of parents had either helped their child bypass age checks or knowingly allowed it.

Why Age Verification Is Expanding

The rapid growth of age-verification systems is being driven largely by new online safety laws introduced across the UK, Europe, Australia, and parts of the United States.

In the UK, the Online Safety Act requires platforms to take stronger steps to protect children from harmful content, including pornography, violence, self-harm material, and certain addictive platform features. The law also requires pornography services to implement what Ofcom describes as “highly effective age assurance”.

As a result, many websites and apps now use facial age estimation, government ID uploads, third-party verification systems, or behavioural analysis to estimate a user’s age.

Internet Matters found that 53 per cent of children had recently been asked to verify their age online, with checks commonly appearing on platforms including TikTok, YouTube, Roblox, Instagram, Reddit, Discord, and Twitch.

The report also noted that many children actually support stronger safety protections online. One child quoted in the research said: “I think it’s good because it keeps us from viewing adult content which is not going to be good for our mental health.”

How Meta Is Using AI To Estimate Age

The wider technology industry is already moving beyond simple “enter your birthday” systems and towards AI-driven age estimation.

Meta recently confirmed it is using AI systems to analyse photos, videos, captions, interactions, and behavioural signals to determine whether users may actually be underage, even if they claim to be adults.

According to Meta, its systems now use “visual analysis” to estimate age using factors such as height, bone structure, and broader visual cues. The company stated: “Our AI looks at general themes and visual cues, for example height or bone structure, to estimate someone’s general age.”

Meta stressed that this “is not facial recognition” and says the technology is designed to place suspected teenagers into stricter “Teen Account” protections automatically, or remove users believed to be under 13 until they can verify their age.

The company is also expanding these systems across Instagram, Facebook, Messenger, Reels, Live streams, and Groups as governments place increasing pressure on platforms to improve child safety.

Why The Technology Still Struggles

Despite increasingly sophisticated systems, the latest findings show that age assurance remains far from foolproof.

Facial age-estimation technology relies heavily on probability rather than certainty, meaning lighting, makeup, camera quality, facial expressions, accessories, and image manipulation can all affect results. Internet Matters also found that some children had successfully used video game characters, AI-generated faces, or edited images to bypass checks.

The report also highlighted wider concerns around privacy and cybersecurity. Some parents and children expressed discomfort about uploading passports, ID documents, or facial scans online, particularly if third-party verification companies are involved.

Others worried that large-scale age verification could create attractive targets for cybercriminals if sensitive personal data were breached or leaked.

At the same time, supporters argue that platforms cannot realistically deliver age-appropriate experiences without some form of reliable age assurance.

What Does This Mean For Your Business?

For UK businesses, the story highlights the growing difficulty of verifying identity and age online, particularly when AI systems are being asked to make judgement calls based on appearance, behaviour, and probability rather than certainty.

Organisations developing online platforms, customer portals, AI tools, or digital services are likely to face increasing regulatory pressure around age assurance, child safety, privacy, and identity verification as online safety laws continue to expand globally.

The findings also underline a wider cybersecurity and governance challenge. Systems that rely entirely on automated trust signals can often be manipulated in unexpected ways, particularly when users actively look for workarounds.

At the same time, the growing use of facial analysis, behavioural monitoring, and AI-driven verification is likely to increase scrutiny around privacy, biometric data handling, transparency, and UK GDPR compliance.

The main lesson here for businesses is that safety technology alone rarely solves behavioural problems completely. Effective online protection increasingly depends on combining technical controls with education, parental involvement, platform accountability, and realistic expectations about how people actually behave online.

Reports that Google Chrome may download a multi-gigabyte AI model onto some desktop computers without many users realising it have sparked debate about transparency, storage use, privacy, and how AI features are increasingly being embedded into everyday software.

How The Controversy Started

The issue emerged after privacy researcher Alexander Hanff published a detailed blog post claiming that Chrome had silently downloaded a file called weights.bin onto his system as part of Google’s Gemini Nano on-device AI system.

According to Hanff, the file appeared inside a folder named OptGuideOnDeviceModel and occupied around 4GB of storage space. He claimed Chrome downloaded the model automatically in the background and that manually deleting the file caused it to reappear later after Chrome re-downloaded it.

The story quickly attracted wider attention, leading to other users reporting that they had discovered large unexplained files linked to Chrome installations.

Importantly, there is currently no evidence that the file is malicious software or spyware. The debate instead centres on whether users were given enough visibility and control over what was being installed and why.

What The File Actually Does

The file is understood to contain Google’s Gemini Nano model, a smaller local version of its Gemini AI system designed to run directly on devices rather than entirely in the cloud.

Google has increasingly been building AI capabilities into Chrome, including scam detection tools, writing assistance, summarisation features, developer APIs, and other AI-assisted functions. Running some of these tools locally can reduce latency and limit the amount of information sent back to remote servers.

In a statement from Google, reported by Android Authority, the company said: “We’ve offered Gemini Nano for Chrome since 2024 as a lightweight, on-device model. It powers important security capabilities like scam detection and developer APIs without sending your data to the cloud.”

Google also stated that the model is designed to uninstall automatically if a device is low on resources, and that it has started rolling out settings allowing users to disable and remove the model more easily.

Why Some Users Are Concerned

Much of the concern is not about AI itself, but about how these features are being deployed.

Many users appear to have been unaware that Chrome could download several gigabytes of AI model data in the background, particularly on systems where storage space, bandwidth, or battery life may already be constrained. Some users also questioned whether these features should be enabled automatically rather than introduced through a clearer opt-in process.

Hanff’s blog post went much further, arguing that large-scale AI downloads could carry environmental implications when multiplied across potentially hundreds of millions of devices worldwide. His article also raised legal and regulatory questions under European privacy law, although those claims have not been tested in court and Google has not publicly responded directly to the legal allegations.

The broader issue reflects growing public unease around how AI is increasingly becoming embedded inside familiar products, often with little visibility into what is running locally, what data may be processed, and how much system resource is being consumed.

Why Google Is Pushing AI Into Chrome

It should be noted here that Google is certainly not alone in embedding local AI models into consumer software.

For example, Microsoft has added AI assistants and local AI features into Windows and Office. Apple is expanding on-device AI processing across macOS and iOS. Also, Meta is building AI tools directly into Facebook, Instagram, and WhatsApp. Browser makers and operating system vendors increasingly view AI as a core platform feature rather than a standalone application.

It’s also worth noting here that local AI processing can offer some genuine advantages. For example, keeping certain AI functions on-device rather than constantly sending data to cloud servers can improve response times, reduce some privacy risks, and allow features to continue working offline.

That said, this has created a new challenge for software vendors because AI models are often large, resource-intensive, and not always obvious to ordinary users.

The debate around Chrome highlights how software expectations are changing. Browsers are no longer simply lightweight web access tools. They are increasingly becoming AI-enabled operating environments running sophisticated local models behind the scenes.

What Does This Mean For Your Business?

For UK businesses, the issue is less about the AI model itself and more about whether organisations have enough visibility and control over the growing number of AI features now being built into everyday software.

Organisations should review which AI features are enabled across browsers and workplace devices, particularly in managed IT environments where storage, performance, bandwidth usage, and data handling policies matter. IT teams may also want to assess whether local AI models are necessary on all devices or whether some features should be disabled through enterprise policy controls.

The story also highlights a wider challenge facing businesses as AI becomes embedded into mainstream software products. Features that were once optional add-ons are increasingly arriving automatically through standard updates, making it harder for organisations to fully understand what software is doing behind the scenes.

Businesses that maintain clear software governance, strong endpoint management, and active oversight of AI-related features will be better placed to balance the potential benefits of AI against the operational, security, privacy, and compliance risks that increasingly come with it.

New research from Cifas suggests some UK employees are becoming increasingly comfortable with workplace fraud and insider threats.

The survey found that 24 per cent believed it was acceptable to secretly work for a competitor, while 13 per cent admitted selling, or knowing someone who had sold, company login details.

Cifas warned the findings point to “shifting norms, blurred boundaries, and rising risks to organisational integrity”, with insider threats becoming a growing concern for employers.

For businesses, the report reinforces the need for stronger access controls, staff training, and better monitoring of insider risks, as cybercriminals increasingly target employees as a route into company systems and sensitive data.

A US startup has raised $140 million to build autonomous floating AI data centres powered by ocean waves, as the technology industry searches for new ways to meet the rapidly growing energy demands of artificial intelligence.

Why AI Is Driving A New Search For Energy

The rapid growth of AI has created a major infrastructure challenge, with data centres now consuming increasing amounts of electricity, cooling water, and computing hardware. Industry forecasts suggest AI-related power demand could rise dramatically over the next decade as more businesses adopt large language models, AI assistants, image generation, automation systems, and real-time inference services.

Panthalassa, an Oregon-based renewable energy and ocean technology company, believes the answer may lie far offshore.

The company has developed autonomous floating platforms designed to generate electricity directly from ocean waves while simultaneously powering AI computing systems onboard. Rather than transmitting electricity back to land through undersea cables, the platforms process AI workloads at sea and send the results back via satellite connections.

US tech billionaire Peter Thiel, whose Founders Fund has backed the company, described the scale of the challenge directly, stating: “The future demands more compute than we can imagine. Extra-terrestrial solutions are no longer science fiction. Panthalassa has opened the ocean frontier.”

How The Floating Data Centres Work

Panthalassa’s systems, known as Ocean nodes, are large steel floating structures deployed in deep ocean regions with strong and consistent wave activity.

The motion of the waves drives internal turbines that generate electricity continuously. That power is then used directly onboard to run AI chips and inference systems housed inside sealed computing containers.

One of the key advantages is cooling. For example, traditional AI data centres consume enormous quantities of water and energy to keep high-performance chips from overheating. Panthalassa instead uses the surrounding ocean as what it calls “free supercooling”, reducing the need for conventional cooling infrastructure while potentially extending chip lifespan.

The company says its Ocean-3 pilot systems will be deployed in the North Pacific later this year ahead of planned commercial operations in 2027.

Garth Sheldon-Coulson, Panthalassa’s co-founder and CEO, said: “We’ve built a technology platform that operates in the planet’s most energy-dense wave regions, far from shore, and turns that resource into reliable clean power.”

He added: “We’re now ready to build factories, deploy fleets, and provide a sustainable new source of energy for humanity.”

Why The Idea Is Attracting Attention

The concept is gaining attention because many land-based data centres are already running into physical and environmental limits.

Large AI facilities require enormous amounts of grid power, land, cooling infrastructure, and permitting approvals. In some regions, utilities have warned that electricity networks may struggle to support projected AI growth without major upgrades.

Panthalassa argues that moving AI infrastructure offshore could reduce pressure on national grids while avoiding many of the environmental and planning conflicts associated with large terrestrial facilities.

The company also claims its systems rely mainly on abundant materials such as steel rather than scarce minerals, potentially making large-scale deployment easier than some alternative clean energy technologies.

Investor John Doerr described the system as “a game changer in addressing global energy needs and clean power generation”, adding that it represents “a triple win: workers benefit, communities benefit, and we gain a strategic asset that strengthens American technological leadership.”

Other Companies Are Exploring Similar Ideas

Panthalassa is not alone in looking for unconventional locations and power sources for future data centres.

For example, Microsoft previously tested underwater data centres through its Project Natick programme, placing sealed server containers on the seabed off Scotland’s Orkney Islands. The company reported lower server failure rates than conventional land-based facilities, partly because of the stable underwater environment and reduced human interference.

Meanwhile, Aikido Technologies recently announced plans for floating offshore wind-powered data centres in the North Sea, with pilot deployments expected near Norway before larger UK projects later this decade.

Also, British company Core Power has explored floating nuclear-powered platforms capable of supplying electricity to offshore computing facilities and military infrastructure.

Elsewhere, some firms are experimenting with placing data centres in colder climates such as Iceland, Norway, and northern Sweden, where naturally low temperatures reduce cooling costs and improve energy efficiency. Major cloud providers including Google and Meta have increasingly prioritised locations with access to renewable energy and cooler operating conditions.

Even Meta’s expanding AI-driven age assurance systems, which analyse images, video, behavioural signals, and account activity to estimate user age, form part of the wider trend driving demand for increasingly large AI compute infrastructure.

Still Some Challenges

Despite the enthusiasm surrounding offshore AI infrastructure, some major practical questions remain.

Open-ocean environments are among the harshest operating conditions on Earth, exposing equipment to corrosion, storms, maintenance difficulties, and communication challenges. Wave energy itself has historically struggled with reliability and commercial scalability, despite decades of experimentation.

There are also environmental questions around marine ecosystems, shipping routes, and the long-term impact of deploying large autonomous industrial systems at sea.

Commercial viability remains another unknown. Panthalassa’s business model depends not on selling electricity, but on selling AI computing capacity generated offshore. Whether this can compete economically with rapidly expanding terrestrial AI infrastructure remains uncertain.

What Does This Mean For Your Business?

For UK businesses, the story highlights how AI is increasingly reshaping not just software and automation, but the global infrastructure required to support digital services.

The energy demands created by AI systems are already influencing investment decisions across energy, construction, semiconductors, cooling technology, networking, and cloud computing. Businesses involved in these sectors may see growing opportunities linked to alternative energy generation, distributed computing, and sustainable infrastructure development.

The story also underlines how sustainability is becoming tightly connected to AI deployment. Organisations adopting AI tools may face growing scrutiny around the environmental impact of the computing resources they consume, particularly as governments and investors place greater emphasis on carbon reduction and energy efficiency.

At the same time, the search for cleaner AI infrastructure is likely to accelerate innovation far beyond traditional data centres, creating new commercial opportunities while also raising new technical, environmental, and regulatory challenges that businesses will increasingly need to understand.

Microsoft’s helpful new Computer Use feature in Copilot Researcher allows the AI to interact directly with websites and software on a user’s behalf, helping automate complex online tasks, speed up research workflows, and reduce the time spent manually navigating between apps and services.

[Note – To Watch This Video without glitches/interruptions, It may be best to download it first]

Google Chrome’s built-in Reading Mode can turn busy web pages into a clean, distraction-free reading view, making it easier to focus on important information without adverts, pop-ups, videos, or visual clutter getting in the way.

On desktop, Reading Mode opens in a side panel that can be widened for a more immersive layout, while Android displays the page in a simplified full-screen view. You can also customise the font, text size, spacing, and background colour to make reading more comfortable.

One particularly useful feature is the small play button inside Reading Mode, which uses AI-powered text-to-speech to read the page aloud while highlighting the words as it goes. This can be especially helpful for reviewing long articles, reducing screen fatigue, multitasking, or improving accessibility.

How It Works

Reading Mode strips away unnecessary page elements and focuses only on the main content, helping you absorb information faster and with fewer distractions. The built-in read-aloud feature also allows you to consume content hands-free while keeping your place visually on screen.

How To Use It in Chrome On Desktop

– Open the web page you want to read.

– Click the three-dot Chrome menu in the top-right corner.

– Select More tools, then Reading mode.

– The page will appear in a simplified side panel.

– Use the controls at the top of the panel to customise the appearance.

– Click the small play button to have Chrome read the page aloud using AI-powered voice narration.

How To Use It In Chrome On Android

In Android, Chrome’s Reading Mode opens as a simplified full-screen reading view rather than a side panel. To use it:

– Open the web page you want to read.

– Tap the three-dot Chrome menu in the top-right corner.

– Select Reading mode (or Simplified view on some versions of Android).

– The page will open in a cleaner, distraction-free layout without adverts or clutter.

– Use the controls to adjust text size, font style, and background colour for easier reading.

– Tap the play button to have Chrome’s AI-powered voice feature read the page aloud while highlighting the text as it goes.