Multiple London councils are responding to a cyberattack that has disrupted shared IT systems and raised concerns about data exposure. Kensington and Chelsea and Westminster councils detected the incident on Monday and alerted the Information Commissioner’s Office as investigations began.
The councils say they are working with specialist incident teams and the National Cyber Security Centre (NCSC) to protect systems and keep key services running. Several platforms have been affected, and staff have been redeployed to support residents through monitored phone lines and email channels.
Hammersmith and Fulham, which shares IT services with the affected councils, has also reported disruption. Local leaders say it is too early to confirm who was responsible or whether personal data has been compromised. Overnight mitigation work has been carried out as monitoring continues.
Security researchers describe indications of a serious intrusion involving lateral movement across shared infrastructure. They warn that attackers may escalate to data theft or encryption, given the sensitivity of the information held by local authorities.
National security agencies and police are assessing the incident’s potential impact. Analysts say the attack highlights long-standing risks facing councils that manage extensive services on limited budgets and with inconsistent cyber safeguards.
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The internet has become part of almost everything we do. It helps us work, stay in touch with friends and family, buy things, plan trips, and handle tasks that would have felt impossible until recently. Most people cannot imagine getting through the day without it.
But there is a hidden cost to all this convenience. Most of the time, online services run smoothly, with countless systems working together in the background. But every now and then, though, a key cog slips out of place.
When that happens, the effects can spread fast, taking down apps, websites, and even entire industries within minutes. These moments remind us how much we rely on digital services, and how quickly everything can unravel when something goes wrong. It raises an uncomfortable question. Is digital dependence worth the convenience, or are we building a house of cards that could collapse, pulling us back into reality?
Warning shots of the dot-com Era and the infancy of Cloud services
In its early years, the internet saw several major malfunctions that disrupted key online services. Incidents like the Morris worm in 1988, which crashed about 10 percent of all internet-connected systems, and the 1996 AOL outage that left six million users offline, revealed how unprepared the early infrastructure was for growing digital demand.
A decade later, the weaknesses were still clear. In 2007, Skype, then with over 270 million users, went down for nearly two days after a surge in logins triggered by a Windows update overwhelmed its network. Since video calls were still in their early days, the impact was not as severe, and most users simply waited it out, postponing chats with friends and family until the issue was fixed.
As the dot-com era faded and the 2010s began, the shift to cloud computing introduced a new kind of fragility. When Amazon’s EC2 and EBS systems in the US-East region went down in 2011, the outage took down services like Reddit, Quora, and IMDb for days, exposing how quickly failures in shared infrastructure can cascade.
A year later, GoDaddy’s DNS failure took millions of websites offline, while large-scale Gmail disruptions affected users around the world, early signs that the cloud’s growing influence came with increasingly high stakes.
By the mid-2010s, it was clear that the internet had evolved from a patchwork of standalone services to a heavily interconnected ecosystem. When cloud or DNS providers stumbled, their failures rippled simultaneously across countless platforms. The move to centralised infrastructure made development faster and more accessible, but it also marked the beginning of an era where a single glitch could shake the entire web.
Centralised infrastructure and the age of cascading failures
The late 2000s and early 2010s saw a rapid rise in internet use, with nearly 2 billion people worldwide online. As access grew, more businesses moved into the digital space, offering e-commerce, social platforms, and new forms of online entertainment to a quickly expanding audience.
With so much activity shifting online, the foundation beneath these services became increasingly important, and increasingly centralised, setting the stage for outages that could ripple far beyond a single website or app.
The next major hit came in 2016, when a massive DDoS attack crippled major websites across the USA and Europe. Platforms like Netflix, Reddit, Twitter, and CNN were suddenly unreachable, not because they were directly targeted, but because Dyn, a major DNS provider, had been overwhelmed.
The attack used the Mirai botnet malware to hijack hundreds of thousands of insecure IoT devices and flood Dyn’s servers with traffic. It was one of the clearest demonstrations yet that knocking out a single infrastructure provider could take down major parts of the internet in one stroke.
In 2017, another major outage occurred, with Amazon at the centre once again. On 28 February, the company’s Simple Storage Service (S3) went down for about 4 hours, disrupting access across a large part of the US-EAST-1 region. While investigating a slowdown in the billing system, an Amazon engineer accidentally entered a typo in a command, taking more servers offline than intended.
That small error was enough to knock out services like Slack, Quora, Coursera, Expedia and countless other websites that relied on S3 for storage or media delivery. The financial impact was substantial; S&P 500 companies alone were estimated to have lost roughly 150 million dollars during the outage.
Amazon quickly published a clear explanation and apology, but transparency could not undo the economic damage nor (yet another) sudden reminder that a single mistake in a centralised system could ripple across the entire web.
Outages in the roaring 2020s
The S3 incident made one thing clear. Outages were no longer just about a single platform going dark. As more services leaned on shared infrastructure, even small missteps could take down enormous parts of the internet. And this fragility did not stop at cloud storage.
Over the next few years, attention shifted to another layer of the online ecosystem: content delivery networks and edge providers that most people had never heard of but that nearly every website depended on.
The 2020s opened with one of the most memorable outages to date. On 4 October 2021, Facebook and its sister platforms, Instagram, WhatsApp, and Messenger, vanished from the internet for nearly 7 hours after a faulty BGP configuration effectively removed the company’s services from the global routing table.
Millions of users flocked to other platforms to vent their frustration, overwhelming Twitter, Telegram, Discord, and Signal’s servers and causing performance issues across the board. It was a rare moment when a single company’s outage sent measurable shockwaves across the entire social media ecosystem.
But what happens when outages hit industries far more essential than social media? In 2023, the Federal Aviation Administration was forced to delay more than 10,000 flights, the first nationwide grounding of air traffic since the aftermath of September 11.
A corrupted database file brought the agency’s Notice to Air Missions (NOTAM) system to a standstill, leaving pilots without critical safety updates and forcing the entire aviation network to pause. The incident sent airline stocks dipping and dealt another blow to public confidence, showing just how disruptive a single technical failure can be when it strikes at the heart of critical infrastructure.
Outages that defined 2025
The year 2025 saw an unprecedented wave of outages, with server overloads, software glitches and coding errors disrupting services across the globe. The Microsoft 365 suite outage in January, the Southwest Airlines and FAA synchronisation failure in April, and the Meta messaging blackout in July all stood out for their scale and impact.
But the most disruptive failures were still to come. In October, Amazon Web Services suffered a major outage in its US-East-1 region, knocking out everything from social apps to banking services and reminding the world that a fault in a single cloud region can ripple across thousands of platforms.
Just weeks later, the Cloudflare November outage became the defining digital breakdown of the year. A logic bug inside its bot management system triggered a cascading collapse that took down social networks, AI tools, gaming platforms, transit systems and countless everyday websites in minutes. It was the clearest sign yet that when core infrastructure falters, the impact is immediate, global and largely unavoidable.
And yet, we continue to place more weight on these shared foundations, trusting they will hold because they usually do. Every outage, whether caused by a typo, a corrupted file, or a misconfigured update, exposes how quickly things can fall apart when one key piece gives way.
Going forward, resilience needs to matter as much as innovation. That means reducing single points of failure, improving transparency, and designing systems that can fail without dragging everything down. The more clearly we see the fragility of the digital ecosystem, the better equipped we are to strengthen it.
Outages will keep happening, and no amount of engineering can promise perfect uptime. But acknowledging the cracks is the first step toward reinforcing what we’ve built — and making sure the next slipped cog does not bring the whole machine to a stop.
The smoke and mirrors of the digital infrastructure
The internet is far from destined to collapse, but resilience can no longer be an afterthought. Redundancy, decentralisation and smarter oversight need to be part of the discussion, not just for engineers, but for policymakers as well.
Outages do not just interrupt our routines. They reveal the systems we have quietly built our lives around. Each failure shows how deeply intertwined our digital world has become, and how fast everything can stop when a single piece gives way.
Will we learn enough from each one to build a digital ecosystem that can absorb the next shock instead of amplifying it? Only time will tell.
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OpenAI has unveiled an updated ChatGPT interface that combines voice and text features in a single view. Users can speak naturally at any point in a chat and receive responses in text, audio, or images. The new layout also introduces real-time map displays.
The redesign adds a scrolling transcript within the chat window. It allows users to revisit earlier exchanges and move easily between reading and listening. OpenAI states that the goal is to support voice-led tasks without compromising clarity.
With the unified experience, conversations no longer require switching modes. ChatGPT can deliver audio, written, and visual replies simultaneously. Maps and images appear directly alongside the voice response.
Every spoken message is automatically transcribed. However, this helps users follow more extended discussions and keep a record for later reference. OpenAI says the feature supports both accessibility and everyday convenience.
The update is rolling out gradually across web and mobile platforms. Users who prefer the earlier voice-only layout can revert to it in settings. OpenAI says the unified mode will remain the default as development continues.
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The UK’s Met Office has laid out a strategic plan for integrating AI, specifically machine learning (ML), with traditional physics-based climate and weather models. The aim is to deliver what it calls an ‘optimal blend’ of AI-driven and physics-based forecasting.
To clarify what that blend might look like, the Met Office has defined five distinct approaches. One is the familiar independent physics-based model, which uses physical laws to simulate atmospheric dynamics, trusted but computationally intensive.
At the other end is an independent ML-based model that learns patterns entirely from data, offering far greater speed and scalability.
Between these extremes lie two ‘hybrid’ approaches: hybrid-integrated ML, where ML replaces or enhances parts of the physics model, and hybrid-composite ML, where ML and physics models run separately and feed into each other.
A fifth option is augmented ML, where ML is applied after the model has run to improve its output (for example, downscaling or refining ensemble forecasts).
However, this framework is more than a technical taxonomy; it provides a shared language for scientists, policymakers, and clients to understand how AI and traditional modelling can coexist.
It also helps guide future decisions, for example, allowing gradual adoption of ML in places where it makes sense, while preserving the robustness of well-understood physics methods in critical areas.
The move comes as ML-based weather and climate tools have shown increasing promise. For instance, in 2025, the Met Office published research showing a purely ML-based model achieved seasonal forecasting skill comparable to conventional physics-based methods, but with far lower computing demands.
For digital-policy watchers and climate analysts alike, this signals a shift: forecasting may become more dynamic, scalable and accessible, especially valuable in a changing climate where speed, resolution and adaptability matter as much as theoretical accuracy.
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Amazon Web Services plans to invest $50 billion in high performance AI infrastructure dedicated to US federal agencies. The programme aims to broaden access to AWS tools such as SageMaker AI, Bedrock and model customisation services, alongside support for Anthropic’s Claude.
The expansion will add around 1.3 gigawatts of compute capacity, enabling agencies to run larger models and speed up complex workloads. AWS expects construction of the new data centres to begin in 2026, marking one of its most ambitious government-focused buildouts to date.
Chief executive Matt Garman argues the upgrade will remove long-standing technology barriers within government. The company says enhanced AI capabilities could accelerate work in areas ranging from cybersecurity to medical research while strengthening national leadership in advanced computing.
AWS has spent more than a decade developing secure environments for classified and sensitive government operations. Competitors have also stepped up US public sector offerings, with OpenAI, Anthropic and Google all rolling out heavily discounted AI products for federal use over the past year.
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OpenAI has launched ChatGPT for Teachers, offering US US educators a secure workspace to plan lessons and utilise AI safely. The service is free for verified K–12 staff until June 2027. OpenAI states that its goal is to support classroom tasks without introducing data risks.
Educators can tailor responses by specifying grades, curriculum needs, and preferred formats. Content shared in the workspace is not used to train models by default. The platform includes GPT-5.1 Auto, search, file uploads, and image tools.
The system integrates with widely used school software, including Google Drive, Microsoft 365, and Canva. Teachers can import documents, design presentations, and organise materials in one place. Shared prompt libraries offer examples from other educators.
Collaboration features enable co-planned lessons, shared templates, and school-specific GPTs. OpenAI says these tools aim to reduce administrative workloads. Schools can create collective workspaces to coordinate teaching resources more easily.
The service remains free through June 2027, with pricing updates to follow later. OpenAI plans to keep costs accessible for schools. Educators can begin using the platform by verifying their status through SheerID.
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Deepfake abuse is accelerating across India as AI tools make it easy to fabricate convincing videos and images. Researchers warn that manipulated media now fuels fraud, political disinformation and targeted harassment. Public awareness often lags behind the pace of generative technology.
Recent cases involving Ranveer Singh and Aamir Khan showed how synthetic political endorsements can spread rapidly online. Investigators say cloned voices and fabricated footage circulated widely during election periods. Rights groups warn that such incidents undermine trust in media and public institutions.
Women face rising risks from non-consensual deepfakes used for harassment, blackmail and intimidation. Cases involving Rashmika Mandanna and Girija Oak intensified calls for stronger protections. Victims report significant emotional harm as edited images spread online.
Security analysts warn that deepfakes pose growing risks to privacy, dignity and personal safety. Users can watch for cues such as uneven lighting, distorted edges, or overly clean audio. Experts also advise limiting the sharing of media and using strong passwords and privacy controls.
Digital safety groups urge people to avoid engaging with manipulated content and to report suspected abuse promptly. Awareness and early detection remain critical as cases continue to rise. Policymakers are being encouraged to expand safeguards and invest in public education on emerging risks associated with AI.
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Holiday shoppers can now rely on AI to make Black Friday and Cyber Monday less stressful. AI tools help track prices across multiple retailers and notify users when items fall within their budget, saving hours of online searching.
Finding gifts for difficult-to-shop-for friends and family is also easier with AI. By describing a person’s interests or lifestyle, shoppers receive curated recommendations with product details, reviews, and availability, drawing from billions of listings in Google’s Shopping Graph.
Local shopping is more convenient thanks to AI features that enhance the shopping experience. Shoppers can check stock at nearby stores without having to call around, and virtual try-on technology allows users to see how clothing looks on them before making a purchase.
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AI-driven fraud schemes are on the rise across the US health system, exposing older adults to increasing financial and personal risks. Officials say tens of billions in losses have already been uncovered this year. High medical use and limited digital literacy leave seniors particularly vulnerable.
Criminals rely on schemes such as phantom billing, upcoding and identity theft using Medicare numbers. Fraud spans home health, hospice care and medical equipment services. Authorities warn that the ageing population will deepen exposure and increase long-term harm.
AI has made scams harder to detect by enabling cloned voices, deepfakes and convincing documents. The tools help impersonate providers and personalise attacks at scale. Even cautious seniors may struggle to recognise false calls or messages.
Investigators are also using AI to counter fraud by spotting abnormal billing, scanning records for inconsistencies and flagging high-risk providers. Cross-checking data across clinics and pharmacies helps identify duplicate claims. Automated prompts can alert users to suspicious contacts.
Experts urge seniors to monitor statements, ignore unsolicited calls and avoid clicking unfamiliar links. They should verify official numbers, protect Medicare details and use strong login security. Suspicious activity should be reported to Medicare or to local fraud response teams.
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Google says Europe faces a pivotal moment as AI reshapes global competitiveness, arguing that the region has the talent to lead the way. It points to growing demand for tools that help businesses innovate and expand. Startups like Idoven are highlighted as examples of Europe’s emerging strengths.
Google highlights its long-standing partnership with Europe, pointing to significant investments in infrastructure, security, and research. It has more than 40 offices and 31,000 staff across the region. DeepMind’s scientific advances, including broad use of AlphaFold, remain central to that work.
Despite this foundation, Google warns that Europe risks falling behind other regions without faster access to advanced AI models.
Only 14% of European companies currently utilise AI, which is significantly lower than the adoption rates in China and the United States. Google says outdated technology limits competitiveness across sectors.
Regulatory complexity is another concern, with more than 100 digital rules introduced since 2019. Google supports regulation but notes that abrupt changes and overlapping requirements can slow product launches and hinder smaller developers. The company calls for more straightforward, more explicit rules that avoid penalising innovation.
Google argues that Europe must also expand AI skills, from technical expertise to leadership and workforce readiness. It cites a decade of training initiatives that helped 15 million Europeans gain digital skills. With the right tools and support, Google says Europe could unlock €1.2 trillion in economic value.
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