Serbia sees wider coverage as Yettel activates 5G

Yettel has launched its 5G network in Serbia, offering higher speeds, lower latency, and support for large numbers of connected devices. Customers need a 5G-ready handset and coverage access, which currently spans major cities and tourist areas. The operator plans wider expansion as deployment progresses.

The service uses recently acquired spectrum, with 5G delivered across the 700 MHz low band and the 3.5 GHz mid band. The frequencies support stronger indoor reach and higher-capacity performance. Yettel says the combination will improve everyday mobile connectivity and enable new digital services.

Use cases include faster downloads, smoother streaming, and more responsive cloud-based gaming. Lower latency will also support remote work and IoT applications. The company expects the network to underpin emerging services that rely on real-time communication and consistent mobile performance.

Yettel forms part of the e& PPF Telecom Group and operates more than 130 retail locations alongside its digital channels. The company says the 5G rollout complements ongoing efforts to modernise national infrastructure. It also aims to maintain strong service quality across urban and regional areas.

The network received the umlaut ‘Best in Test’ award in 2025, marking a ninth consecutive national win. Yettel frames 5G as the next stage of its technological development. The operator expects the upgrade to strengthen the broader digital ecosystem of Serbia and improve long-term connectivity options.

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Mistral AI unveils new open models with broader capabilities

Yesterday, Mistral AI introduced Mistral 3 as a new generation of open multimodal and multilingual models that aim to support developers and enterprises through broader access and improved efficiency.

The company presented both small dense models and a new mixture-of-experts system called Mistral Large 3, offering open-weight releases to encourage wider adoption across different sectors.

Developers are encouraged to build on models in compressed formats that reduce deployment costs, rather than relying on heavier, closed solutions.

The organisation highlighted that Large 3 was trained with extensive resources on NVIDIA hardware to improve performance in multilingual communication, image understanding and general instruction tasks.

Mistral AI underlined its cooperation with NVIDIA, Red Hat and vLLM to deliver faster inference and easier deployment, providing optimised support for data centres along with options suited for edge computing.

A partnership that introduced lower-precision execution and improved kernels to increase throughput for frontier-scale workloads.

Attention was also given to the Ministral 3 series, which includes models designed for local or edge settings in three sizes. Each version supports image understanding and multilingual tasks, with instruction and reasoning variants that aim to strike a balance between accuracy and cost efficiency.

Moreover, the company stated that these models produce fewer tokens in real-world use cases, rather than generating unnecessarily long outputs, a choice that aims to reduce operational burdens for enterprises.

Mistral AI continued by noting that all releases will be available through major platforms and cloud partners, offering both standard and custom training services. Organisations that require specialised performance are invited to adapt the models to domain-specific needs under the Apache 2.0 licence.

The company emphasised a long-term commitment to open development and encouraged developers to explore and customise the models to support new applications across different industries.

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NVIDIA platform lifts leading MoE models

Frontier developers are adopting a mixture-of-experts architecture as the foundation for their most advanced open-source models. Designers now rely on specialised experts that activate only when needed instead of forcing every parameter to work on each token.

Major models, such as DeepSeek-R1, Kimi K2 Thinking, and Mistral Large 3, rise to the top of the Artificial Analysis leaderboard by utilising this pattern to combine greater capability with lower computational strain.

Scaling the architecture has always been the main obstacle. Expert parallelism requires high-speed memory access and near-instant communication between multiple GPUs, yet traditional systems often create bottlenecks that slow down training and inference.

NVIDIA has shifted toward extreme hardware and software codesign to remove those constraints.

The GB200 NVL72 rack-scale system links seventy-two Blackwell GPUs via fast shared memory and a dense NVLink fabric, enabling experts to exchange information rapidly, rather than relying on slower network layers.

Model developers report significant improvements once they deploy MoE designs on NVL72. Performance leaps of up to ten times have been recorded for frontier systems, improving latency, energy efficiency and the overall cost of running large-scale inference.

Cloud providers integrate the platform to support customers in building agentic workflows and multimodal systems that route tasks between specialised components, rather than duplicating full models for each purpose.

Industry adoption signals a shift toward a future where efficiency and intelligence evolve together. MoE has become the preferred architecture for state-of-the-art reasoning, and NVL72 offers a practical route for enterprises seeking predictable performance gains.

NVIDIA positions its roadmap, including the forthcoming Vera Rubin architecture, as the next step in expanding the scale and capability of frontier AI.

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Regulators question transparency after Mixpanel data leak

Mixpanel is facing criticism after disclosing a security incident with minimal detail, providing only a brief note before the US Thanksgiving weekend. Analysts say the timing and lack of clarity set a poor example for transparency in breach reporting.

OpenAI later confirmed its own exposure, stating that analytics data linked to developer activity had been obtained from Mixpanel’s systems. It stressed that ChatGPT users were not affected and that it had halted its use of the service following the incident.

OpenAI said the stolen information included names, email addresses, coarse location data and browser details, raising concerns about phishing risks. It noted that no advertising identifiers were involved, limiting broader cross-platform tracking.

Security experts say the breach highlights long-standing concerns about analytics companies that collect detailed behavioural and device data across thousands of apps. Mixpanel’s session-replay tools can be sensitive, as they can inadvertently capture private information.

Regulators argue the case shows why analytics providers have become prime targets for attackers. They say that more transparent disclosure from Mixpanel is needed to assess the scale of exposure and the potential impact on companies and end-users.

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SAP expands sovereign cloud vision with EU AI Cloud

SAP introduced the EU AI Cloud as part of a unified plan that aims to support Europe’s digital sovereignty goals.

The offering consolidates SAP’s existing sovereign cloud work under one structure and provides organisations with a way to meet strict regulatory and operational needs, ensuring full EU data residency.

Customers can select deployment options that match their level of required control, ranging from SAP’s European data centres to on-site infrastructure.

SAP is also expanding its partnership with Cohere to integrate advanced multimodal and agentic AI features through Cohere North.

Incorporation into SAP Business Technology Platform enables enterprises with data residency constraints to apply AI within core processes without undermining compliance or performance.

A collaboration that is intended to improve insight generation and decision support across a wide range of industries.

EU AI Cloud is backed by a broad ecosystem that includes Cohere, Mistral AI, OpenAI and other partners whose models and applications can be accessed through SAP BTP.

European enterprises and public bodies gain access to routes for developing and deploying AI tools while maintaining flexibility and sovereignty.

The range of options includes SAP Sovereign Cloud, customer-operated on-site deployments and, where chosen, commercial services on selected hyperscalers with sovereignty controls. The approach also includes Delos Cloud for organisations in Germany that require dedicated public sector safeguards.

SAP positions the initiative as a means to advance AI adoption in Europe, aligning with regional standards on data protection and operational independence.

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New ChatGPT Voice design aims to smooth AI conversations

OpenAI has rolled out an update to ChatGPT Voice that unifies voice and text in a single interface. Users can now speak, type or mix both without switching screens mid-conversation.

The redesigned chat window displays live transcriptions and responses in real-time. Users can scroll through earlier messages and view images, maps and other visuals while the exchange continues in one place.

Previously, voice required a separate mode that hid the main chat history and shared content. OpenAI says the unified layout should make longer, mixed-mode conversations feel more natural and less fragmented.

Voice and text can still be used interchangeably, but ending a voice session requires tapping ‘End’ before returning to text-only use. Those who prefer the old layout can re-enable a separate voice view in settings.

The revamped Voice experience is becoming the default on web and mobile apps as the update rolls out. OpenAI aims to make ChatGPT feel more like a flexible conversational assistant across various devices.

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Scarcity gives Europe an edge in the AI race

Europe’s constrained energy supply and strict regulations are emerging as unlikely strengths in the global race to expand AI infrastructure. Limited power access and careful planning are encouraging more resilient, future-ready data-centre designs that appeal to long-term investors.

Countries such as the Nordics, Spain and Italy are drawing interest due to stronger renewable capacity and shorter grid-connection times, while the UK, Germany and the Netherlands face greater congestion.

Shifting to a ‘first ready, first connected’ model aims to curb speculation and speed up delivery of viable projects.

Europe’s biggest opportunity lies in cloud-focused facilities and AI inference, which analysts expect to account for most AI demand and must often remain within regional borders.

Tighter rules may slow construction, yet they reduce the risk of stranded assets and support sustainable sites that strengthen Europe’s investment case.

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Snapdragon 8 Gen 5 by Qualcomm brings faster AI performance to flagship phones

Qualcomm has introduced the Snapdragon 8 Gen 5 Mobile Platform, positioning it as a premium upgrade that elevates performance, AI capability, and gaming. The company says the new chipset responds to growing demand for more advanced features in flagship smartphones.

Snapdragon 8 Gen 5 includes an enhanced sensing hub that wakes an AI assistant when a user picks up their device. Qualcomm says the platform supports agentic AI functions through the updated AI Engine, enabling more context-aware interactions and personalised assistance directly on the device.

The system is powered by the custom Oryon CPU, reaching speeds up to 3.8 GHz and delivering notable improvements in responsiveness and web performance. Qualcomm reports a 36% increase in overall processing power and an 11% boost to graphics output through its updated Adreno GPU architecture.

Qualcomm executives say the refreshed platform will bring high-end performance to more markets. Chris Patrick, senior vice-president for mobile handsets, says Snapdragon 8 Gen 5 is built to meet rising demands for speed, efficiency, and intelligent features.

Qualcomm confirmed that the chipset will appear in upcoming flagship devices from manufacturers including iQOO, Honor, Meizu, Motorola, OnePlus, and vivo. The company expects the platform to anchor next-generation models entering global markets in the months ahead.

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What the Cloudflare outage taught us: Tracing ones that shaped the internet of today

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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