Adobe is buying Semrush for $1.9 billion in a move to supercharge its AI-driven marketing stack. Reuters reports: Semrush designs and develops AI software that helps companies with search engine optimization, social media and digital advertising. The acquisition, expected to close in the first half of next year, would allow Adobe to help marketers better understand how their brands are viewed by online consumers through searches on websites and generative AI bots such as ChatGPT and Gemini. "The price is steep as Semrush isn't a massive revenue engine on its own, so Adobe is likely paying for strategic value. The payoff could be high too if Adobe can quickly turn Semrush's data into monetizable AI products," said Emarketer analyst Grace Harmon.

"While we are positive on Adobe restarting its M&A engine given the success that it has seen with this motion over the years... this deal likely does little to answer the questions revolving around the company's creative cloud business," added William Blair analysts.

pbahra writes: Saudi Arabia is betting that the future of Hollywood won't be built in physical stages but in datacenters. In a push to anchor itself in next-generation film production, Riyadh-based Humain has led Luma AI's latest Series C round, backing the shift towards cloud-based, AI-generated video rather than traditional studio infrastructure.. Humain's announcement says the new investment will accelerate Luma's development of world models capable of learning from video, audio and language to generate photorealistic scenes, environments and characters on demand. Supporters argue this could upend film-making by pushing much of Hollywood's production pipeline into high-performance datacenters rather than physical sets.

Nvidia blew past earnings expectations with soaring revenue and profit, easing fears of an AI bubble and reinforcing its position as the engine of the global AI boom. From a report: Nvidia's sales grew 62% year-over-year to $57 billion in the October quarter, ahead of the $54.9 billion Wall Street had projected, signaling that demand for AI chips remains strong even as more questions emerge about whether returns from the technology will keep up with the pace of AI infrastructure investments. It posted profits of $31.9 billion, up 65% from the year-ago quarter and also slightly above expectations.

"Blackwell sales are off the charts, and cloud GPUs are sold out," Nvidia CEO Jensen Huang said in a statement, a message that echoes his earlier arguments that fears of an AI bubble are overblown. The company also posted stronger-than-expected sales guidance of around $65 billion for the fourth quarter, another indicator that the AI spending spree isn't slowing anytime soon.

An anonymous reader quotes a report from ZDNet: At KubeCon North America 2025 in Atlanta, the Cloud Native Computing Foundation (CNCF)'s leaders predicted an enormous surge in cloud-native computing, driven by the explosive growth of AI inference workloads. How much growth? They're predicting hundreds of billions of dollars in spending over the next 18 months. [...] Where cloud-native computing and AI inference come together is when AI is no longer a separate track from cloud-native computing. Instead, AI workloads, particularly inference tasks, are fueling a new era where intelligent applications require scalable and reliable infrastructure. That era is unfolding because, said [CNCF Executive Director Jonathan Bryce], "AI is moving from a few 'Training supercomputers' to widespread 'Enterprise Inference.' This is fundamentally a cloud-native problem. You, the platform engineers, are the ones who will build the open-source platforms that unlock enterprise AI."

"Cloud native and AI-native development are merging, and it's really an incredible place we're in right now," said CNCF CTO Chris Aniszczyk. The data backs up this opinion. For example, Google has reported that its internal inference jobs have processed 1.33 quadrillion tokens per month recently, up from 980 trillion just months before. [...] Aniszczyk added that cloud-native projects, especially Kubernetes, are adapting to serve inference workloads at scale: "Kubernetes is obviously one of the leading examples as of the last release the dynamic resource allocation feature enables GPU and TPU hardware abstraction in a Kubernetes context." To better meet the demand, the CNCF announced the Certified Kubernetes AI Conformance Program, which aims to make AI workloads as portable and reliable as traditional cloud-native applications.

"As AI moves into production, teams need a consistent infrastructure they can rely on," Aniszczyk stated during his keynote. "This initiative will create shared guardrails to ensure AI workloads behave predictably across environments. It builds on the same community-driven standards process we've used with Kubernetes to help bring consistency as AI adoption scales." What all this effort means for business is that AI inference spending on cloud-native infrastructure and services will reach into the hundreds of billions within the next 18 months. That investment is because CNCF leaders predict that enterprises will race to stand up reliable, cost-effective AI services.

An anonymous reader shares a report: It's too soon to be talking about the Curse of OpenAI, but we're going to anyway. Since September 10, when Oracle announced a $300 billion deal with the chatbot maker, its stock has shed $315 billion in market value.

OK, yes, it's a gross simplification to just look at market cap. But equivalents to Oracle shares are little changed over the same period (Nasdaq Composite, Microsoft, Dow Jones US Software Index), so the $15 billion loss figure [figure updated with stock price] is not entirely wrong. Oracle's "astonishing quarter" really has cost it nearly as much as one General Motors, or two Kraft Heinz.

An anonymous reader quotes a report from Security Affairs: On October 24, 2025, Azure DDoS Protection detected and mitigated a massive multi-vector attack peaking at 15.72 Tbps and 3.64 billion pps, the largest cloud DDoS ever recorded, aimed at a single Australian endpoint. Azure's global protection network filtered the traffic, keeping services online. The attack came from the Aisuru botnet, a Turbo Mirai-class IoT botnet using compromised home routers and cameras.

The attack used massive UDP floods from more than 500,000 IPs hitting a single public address, with little spoofing and random source ports that made traceback easier. It highlights how attackers are scaling with the internet: faster home fiber and increasingly powerful IoT devices keep pushing DDoS attack sizes higher. "On October 24, 2025, Azure DDOS Protection automatically detected and mitigated a multi-vector DDoS attack measuring 15.72 Tbps and nearly 3.64 billion packets per second (pps). This was the largest DDoS attack ever observed in the cloud and it targeted a single endpoint in Australia," reads a report published by Microsoft. "The attack originated from Aisuru botnet."

"Attackers are scaling with the internet itself. As fiber-to-the-home speeds rise and IoT devices get more powerful, the baseline for attack size keeps climbing," concludes the post. "As we approach the upcoming holiday season, it is essential to confirm that all internet-facing applications and workloads are adequately protected against DDOS attacks."

An anonymous reader quotes a report from Bloomberg: Amazon Web Services, Microsoft's Azure, and Alphabet's Google Cloud risk being dragged into the scope of the European Union's crackdown on Big Tech as antitrust watchdogs prepare to study the platforms' market power. The European Commission wants to decide if any of the trio should face a raft of new restrictions under the bloc's Digital Markets Act (source paywalled; alternative source), according to people familiar with the matter who spoke on condition of anonymity. The plan for a market probe follows several major outages in the cloud industry that wrought havoc across global services, highlighting the risks of relying on a mere handful of players.

To date, the world's largest cloud providers have avoided the DMA because a large part of their business comes via enterprise contracts, making it difficult to count the number of individual users, one of the EU's main benchmarks for earmarking Silicon Valley services for extra oversight. Under the investigation's remit, regulators will asses whether the top cloud operators -- regardless of the challenge of counting user numbers -- should be forced to contend with a raft of fresh obligations including increased interoperability with rival software and better data portability for users, as well as restrictions on tying and bundling.

Authorities in Iran have sprayed clouds with chemicals to induce rain, in an attempt to combat the country's worst drought in decades. From a report: Known as cloud-seeding, the process was conducted over the Urmia lake basin on Saturday, Iran's official news agency Irna reported. Urmia is Iran's largest lake, but has largely dried out leaving a vast salt bed. Further operations will be carried out in east and west Azerbaijan, the agency said.

Rainfall is at record lows and reservoirs are nearly empty. Last week President Masoud Pezeshkian warned that if there is not enough rainfall soon, Tehran's water supply could be rationed and people may be evacuated from the capital. Cloud seeding involves injecting chemical salts including silver or potassium iodide into clouds via aircraft or through generators on the ground. Water vapour can then condense more easily and turn into rain. The technique has been around for decades, and the UAE has used it in recent years to help address water shortages. Iran's meteorological organisation said rainfall had decreased by about 89% this year compared with the long-term average, Irna reported.

"Windows is evolving into an agentic OS," Microsoft's president of Windows Pavan Davuluri posted on X.com, "connecting devices, cloud, and AI to unlock intelligent productivity and secure work anywhere."

But former Uber software engineer and engineering manager Gergely Orosz was unimpressed. "Can't see any reason for software engineers to choose Windows with this weird direction they are doubling down on. So odd because Microsoft has building dev tools in their DNA... their OS doesn't look like anything a builder who wants OS control could choose. Mac or Linux it is for devs."

Davuluri "has since disabled replies on his original post..." notes the blog Windows Central, "which some people viewed as an attempt to shut out negative feedback." But he also replied to that comment... Davuluri says "we care deeply about developers. We know we have work to do on the experience, both on the everyday usability, from inconsistent dialogs to power user experiences. When we meet as a team, we discuss these pain points and others in detail, because we want developers to choose Windows..." The good news is Davuluri has confirmed that Microsoft is listening, and is aware of the backlash it's receiving over the company's obsession with AI in Windows 11. That doesn't mean the company is going to stop with adding AI to Windows, but it does mean we can also expect Microsoft to focus on the other things that matter too, such as stability and power user enhancements.
Elsewhere on X.com, Microsoft CEO Satya Nadella shared his own thoughts on "the net benefit of the AI platform wave ." The Times of India reports: Nadella said tech companies should focus on building AI systems that create more value for the people and businesses using them, not just for the companies that make the technology. He cited Bill Gates to emphasize the same: "A platform is when the economic value of everybody that uses it exceeds the value of the company that creates it."Tesla CEO Elon Musk responded to Nadella's post with a facepalm emoji.

Nadella said this idea matters even more during the current AI boom, where many firms risk giving away too much of their own value to big tech platforms. "The real question is how to empower every company out there to build their own AI-native capabilities," he wrote. Nadella says Microsoft's partnership with OpenAI is an example of zero-sum mindset industry... [He also cited Microsoft's "work to bring AMD into the fleet."]
More from Satya Nadella's post: Thanks to AI, the [coding] category itself has expanded and may ultimately become one of the largest software categories. I don't ever recall any analyst ever asking me about how much revenue Visual Studio makes! But now everyone is excited about AI coding tools. This is another aspect of positive sum, when the category itself is redefined and the pie becomes 10x what it was! With GitHub Copilot we compete for our share and with GitHub and Agent HQ we also provide a platform for others.

Of course, the real test of this era won't be when another tech company breaks a valuation record. It will be when the overall economy and society themselves reach new heights. When a pharma company uses AI in silico to bring a new therapy to market in one year instead of twelve. When a manufacturer uses AI to redesign a supply chain overnight. When a teacher personalizes lessons for every student. When a farmer predicts and prevents crop failure.That's when we'll know the system is working.

Let us move beyond zero-sum thinking and the winner-take-all hype and focus instead on building broad capabilities that harness the power of this technology to achieve local success in each firm, which then leads to broad economic growth and societal benefits. And every firm needs to make sure they have control of their own destiny and sovereignty vs just a press release with a Tech/AI company or worse leak all their value through what may seem like a partnership, except it's extractive in terms of value exchange in the long run.

A new "cold war" between America and China is "pushing leaders to sideline concerns about the dangers of powerful AI models," reports the Wall Street Journal, "including the spread of disinformation and other harmful content, and the development of superintelligent AI systems misaligned with human values..."

"Both countries are driven as much by fear as by hope of progress. " In Washington and Silicon Valley, warnings abound that China's "authoritarian AI," left unchecked, will erode American tech supremacy. Beijing is gripped by the conviction that a failure to keep pace in AI will make it easier for the U.S. to cut short China's resurgence as a global power. Both countries believe market share for their companies across the world is up for grabs — and with it, the potential to influence large swaths of the global population.

The U.S. still has a clear lead, producing the most powerful AI models. China can't match it in advanced chips and has no answer for the financial firepower of private American investors, who funded AI startups to the tune of $104 billion in the first half of 2025, and are gearing up for more. But it has a massive population of capable engineers, lower costs and a state-led development model that often moves faster than the U.S., all of which Beijing is working to harness to tip the contest in its direction. A new "whole of society" campaign looks to accelerate the construction of computing clusters in areas like Inner Mongolia, where vast solar and wind farms provide plentiful cheap energy, and connect hundreds of data centers to create a shared compute pool — some describe it as a "national cloud" — by 2028. China is also funneling hundreds of billions of dollars into its power grid to support AI training and adoption...

"Our lead is probably in the 'months but not years' realm," said Chris McGuire, who helped design U.S. export controls on AI chips while serving on the National Security Council under the Biden administration. Chinese AI models currently rank at or near the top in every task from coding to video generation, with the exception of search, according to Chatbot Arena, a popular crowdsourced ranking platform. China's manufacturing sector, meanwhile, is rocketing past the U.S. in bringing AI into the physical world through robotaxis, autonomous drones and humanoid robots. Given China's progress, McGuire said, the U.S. is "very lucky" to have its advantage in chips...

If AI surpasses human intelligence and acquires the ability to improve itself, it could confer unshakable scientific, economic and military superiority on the country that controls it. Short of that, AI's ability to automate tedious tasks and process vast amounts of data quickly promises to supercharge everything from cancer diagnoses to missile defense. With so much at stake, hacking and cyber espionage are likely to get worse, as AI gives hackers more powerful tools, while increasing incentives for state-backed groups to try to steal AI-related intellectual property. As distrust grows, Washington and Beijing will also find it hard, if not impossible, to cooperate in areas like preventing extremist groups from using AI in destructive ways, such as building bioweapons. "The costs of the AI Cold War are already high and will go much higher," said Paul Triolo, a former U.S. government analyst and current technology policy lead at business consulting firm DGA-Albright Stonebridge Group. "A U.S.-China AI arms race becomes a self-fulfilling prophecy, with neither side able to trust that the other would observe any restrictions on advanced AI capability development...."
The article includes an interesting observation from Helen Toner, director of strategy for Georgetown's Center for Security and Emerging Technology and a former OpenAI board member. Toner points out "We don't actually know" if boosting computing power with better chips will continue producing more-powerful AI models.

So "If performance plateaus," the Journal writes, "despite all the spending by OpenAI and others — a growing concern in Silicon Valley — China has a chance to compete."

German Chancellor Friedrich Merz said Chinese suppliers such as Huawei will be excluded from the country's future telecommunication networks on security grounds as he pushes for more digital sovereignty. From a report: "We have decided within the government that everywhere it's possible we'll replace components, for example in the 5G network, with components we have produced ourselves," Merz told a business conference in Berlin on Thursday. "And we won't allow any components from China in the 6G network."

Europe is increasingly concerned about its reliance on foreign technology, ranging from Asian semiconductors to US artificial intelligence and cloud infrastructure, as trade and geopolitical tensions threaten critical supply chains. Germany last year ordered telecom operators to remove Huawei equipment from their core networks, citing risks to national security. Berlin is now considering using public funds to pay Deutsche Telekom AG and others to strip out Chinese gear, Bloomberg News reported last month.

An anonymous reader quotes a report from CNBC: Anthropic announced plans Wednesday to spend $50 billion on a U.S. artificial intelligence infrastructure build-out, starting with custom data centers in Texas and New York. The facilities, which will be designed to support the company's rapid enterprise growth and its long-term research agenda, will be developed in partnership with Fluidstack.

Fluidstack is an AI cloud platform that supplies large-scale graphics processing unit, or GPU, clusters to clients like Meta, Midjourney and Mistral. Additional sites are expected to follow, with the first locations going live in 2026. The project is expected to create 800 permanent jobs and more than 2,000 construction roles. The investment positions Anthropic as a major domestic player in physical AI infrastructure at a moment when policymakers are increasingly focused on U.S.-based compute capacity and technological sovereignty. "We're getting closer to AI that can accelerate scientific discovery and help solve complex problems in ways that weren't possible before. Realizing that potential requires infrastructure that can support continued development at the frontier," said CEO Dario Amodei. "These sites will help us build more capable AI systems that can drive those breakthroughs, while creating American jobs."

Google has unveiled Private AI Compute, a cloud platform designed to deliver advanced AI capabilities while preserving user privacy. As The Verge notes, the feature is "virtually identical to Apple's Private Cloud Compute." From the report: Many Google products run AI features like translation, audio summaries, and chatbot assistants, on-device, meaning data doesn't leave your phone, Chromebook, or whatever it is you're using. This isn't sustainable, Google says, as advancing AI tools need more reasoning and computational power than devices can supply. The compromise is to ship more difficult AI requests to a cloud platform, called Private AI Compute, which it describes as a "secure, fortified space" offering the same degree of security you'd expect from on-device processing. Sensitive data is available "only to you and no one else, not even Google."

Two of the world's biggest data center developers have projects in Nvidia's hometown that may sit empty for years because the local utility isn't ready to supply electricity. From a report: In Santa Clara, California, where the world's biggest supplier of artificial-intelligence chips is based, Digital Realty Trust applied in 2019 to build a data center. Roughly six years later, the development remains an empty shell awaiting full energization. Stack Infrastructure, which was acquired earlier this year by Blue Owl Capital, has a nearby 48-megawatt project that's also vacant, while the city-owned utility, Silicon Valley Power, struggles to upgrade its capacity.

The fate of the two facilities highlights a major challenge for the US tech sector and indeed the wider economy. While demand for data centers has never been greater, driven by the boom in cloud computing and AI, access to electricity is emerging as the biggest constraint. That's largely because of aging power infrastructure, a slow build-out of new transmission lines and a variety of regulatory and permitting hurdles. And the pressure on power systems is only going to increase. Electricity requirements from AI computing will likely more than double in the US alone by 2035, based on BloombergNEF projections. Nvidia's Jensen Huang and OpenAI's Sam Altman are among corporate leaders that have predicted trillions of dollars will pour into building new AI infrastructure.

An anonymous reader shares a report: Microsoft, eager to boost downloads of its Copilot chatbot, has recruited some of the most popular influencers in America to push a message to young consumers that might be summed up as: Our AI assistant is as cool as ChatGPT. Microsoft could use the help. The company recently said its family of Copilot assistants attracts 150 million active users each month. But OpenAI's ChatGPT claims 800 million weekly active users, and Google's Gemini boasts 650 million a month. Microsoft has an edge with corporate customers, thanks to a long history of selling them software and cloud services. But it has struggled to crack the consumer market -- especially people under 30.

"We're a challenger brand in this area, and we're kind of up and coming," Consumer Chief Marketing Officer Yusuf Mehdi said in an interview. Mehdi hopes to persuade key influencers to make Copilot their chatbot of choice and then use their popularity to market the assistant to their millions of followers. He says Microsoft is already getting more bang for the buck with influencers than with traditional media, but didn't provide any metrics.

[...] Using non-techies as spokespeople is meant to reinforce Microsoft's campaign to sell its chatbot as a life coach for everyone. Or as Consumer AI chief Mustafa Suleyman wrote in a recent essay, an AI companion that "helps you think, plan and dream."

Singaporean super-app company Grab has dumped 200 cloudy Mac Minis and replaced them with physical machines, a move it expects will save $2.4 million over three years. From a report: Grab is Southeast Asia's leading rideshare and food delivery outfit and therefore needs to build apps for iOS to connect with customers. In a Thursday post, the company explains it builds those apps using Continuous Integration and Continuous Delivery/Deployment (CI/CD) infrastructure that runs on Apple Mac computers.

The company started with a single on-prem Mac Pro -- its post shows 2013's cylindrical model based around an Intel Xeon processor -- but eventually reached over 200 Macs, running in the cloud at an unnamed US cloud provider. "At the beginning, it was a no-brainer to rent when our demand for macOS hardware increased from 1 Mac Pro to 20 times that size," Grab's post explains. "However, when that grew to over 200 machines, the total cost became significant."

An anonymous reader shares a report: On Wednesday, Reuters reported that Google is planning to build a large AI data center on Christmas Island, a 52-square-mile Australian territory in the Indian Ocean, following a cloud computing deal with Australia's military. The previously undisclosed project will reportedly position advanced AI infrastructure a mere 220 miles south of Indonesia at a location military strategists consider critical for monitoring Chinese naval activity.

Aside from its strategic military position, the island is famous for its massive annual crab migration, where over 100 million of red crabs make their way across the island to spawn in the ocean. That's notable because the tech giant has applied for environmental approvals to build a subsea cable connecting the 135-square-kilometer island to Darwin, where US Marines are stationed for six months each year.

[...] Christmas Island's annual crab migration is a natural phenomenon that Sir David Attenborough reportedly once described as one of his greatest TV moments when he visited the site in 1990. Every year, millions of crabs emerge from the forest and swarm across roads, streams, rocks, and beaches to reach the ocean, where each female can produce up to 100,000 eggs. The tiny baby crabs that survive take about nine days to march back inland to the safety of the plateau.

An anonymous reader quotes a report from MIT Technology Review: The US- and UK-based company Quantinuum today unveiled Helios, its third-generation quantum computer, which includes expanded computing power and error correction capability. Like all other existing quantum computers, Helios is not powerful enough to execute the industry's dream money-making algorithms, such as those that would be useful for materials discovery or financial modeling. But Quantinuum's machines, which use individual ions as qubits, could be easier to scale up than quantum computers that use superconducting circuits as qubits, such as Google's and IBM's. "Helios is an important proof point in our road map about how we'll scale to larger physical systems," says Jennifer Strabley, vice president at Quantinuum, which formed in 2021 from the merger of Honeywell Quantum Solutions and Cambridge Quantum. Honeywell remains Quantinuum's majority owner.

Located at Quantinuum's facility in Colorado, Helios comprises a myriad of components, including mirrors, lasers, and optical fiber. Its core is a thumbnail-size chip containing the barium ions that serve as the qubits, which perform the actual computing. Helios computes with 98 barium ions at a time; its predecessor, H2, used 56 ytterbium qubits. The barium ions are an upgrade, as they have proven easier to control than ytterbium. These components all sit within a chamber that is cooled to about 15 Kelvin (-432.67 ), on top of an optical table. Users can access the computer by logging in remotely over the cloud. [...] Helios is noteworthy for its qubits' precision, says Rajibul Islam, a physicist at the University of Waterloo in Canada, who is not affiliated with Quantinuum. The computer's qubit error rates are low to begin with, which means it doesn't need to devote as much of its hardware to error correction. Quantinuum had pairs of qubits interact in an operation known as entanglement and found that they behaved as expected 99.921% of the time. "To the best of my knowledge, no other platform is at this level," says Islam.

[...] Besides increasing the number of qubits on its chip, another notable achievement for Quantinuum is that it demonstrated error correction "on the fly," says David Hayes, the company's director of computational theory and design, That's a new capability for its machines. Nvidia GPUs were used to identify errors in the qubits in parallel. Hayes thinks that GPUs are more effective for error correction than chips known as FPGAs, also used in the industry. Quantinuum has used its computers to investigate the basic physics of magnetism and superconductivity. Earlier this year, it reported simulating a magnet on H2, Quantinuum's predecessor, with the claim that it "rivals the best classical approaches in expanding our understanding of magnetism." Along with announcing the introduction of Helios, the company has used the machine to simulate the behavior of electrons in a high-temperature superconductor. Quantinuum is expanding its Helios line with a new system in Minnesota. It's also started developing its fourth-generation quantum computer, Sol, set for 2027 with 192 qubits. Then, a fifth-generation system, Apollo, is expected in 2029 with thousands of qubits and full fault tolerance.

Financial Times: Deutsche Bank is exploring ways to hedge its exposure to data centres after extending billions of dollars in debt to the sector to keep up with demand for artificial intelligence and cloud computing. Executives inside the bank have discussed ways to manage its exposure to the booming industry as so-called hyperscalers pour hundreds of billions of dollars into building infrastructure for their AI needs that is increasingly funded by debt.

The German lender is looking at options including shorting a basket of AI-related stocks that would help mitigate downside risk by betting against companies in the sector. It is also considering buying default protection on some of the debt using derivatives through a transaction known as synthetic risk transfer (SRT).

Deutsche's investment banking business has "bet big" on data centre financing, according to one senior executive. However, the scale of expenditure on AI infrastructure has prompted concerns that a bubble is forming with some likening the enthusiasm to that which preceded the dotcom crash. Sceptics have pointed out that billions of dollars have been deployed in an untested industry with assets that quickly depreciate in value due to the rapid change in technology.

An anonymous reader shares a report: Microsoft officially ended mainstream support for Windows 10 last month, nudging users to upgrade to Windows 11. While that led to almost an overnight technological revolution in Japan, elsewhere, it has caused a lot of confusion. Certain versions of Windows 10, like Enterprise LTSC -- and those enrolled in the ESU program -- are still scheduled to receive security updates through at least 2027, but they're starting to see out-of-support messages in Settings.

Various users over the past few days reported that they're being subjected to end-of-life warnings in Windows, despite already qualifying for extended security updates through the ESU program. Windows 10 Enterprise LTSC 2021 and âIoT Enterprise are business-oriented editions of the OS, so they're already supported up to 2032, but even they saw these incorrect messages. This widespread bug started to occur after the KB5066791 updates were pushed on October 14, 2025.

Microsoft has already acknowledged this mishap and said, "The message, 'Your version of Windows has reached the end of support, might incorrectly display in the Windows Update Settings page," confirming it as a mistake. The company has already released a cloud config fix that should remove the message, but you need to be connected to the internet for that, and a restart is also required.