Microsoft has extended its free consumer Windows 10 Extended Security Updates (ESU) program by a year, pushing the cutoff for critical security patches to October 14th, 2027. The change came without any actual announcement, appearing instead in an edit to Microsoft's Windows 10 ESU support page. Devices already enrolled roll over to the new date automatically, with no action required from users. The program was originally set to expire on October 12th, 2026, one year after Windows 10 reached end of support on October 14th, 2025. With the extension, however, users who can’t or won’t move to Windows 11 now have a second free year of patches.

Speaking to BleepingComputer, Microsoft said that the change reflects “our ongoing commitment to helping customers stay secure during the transition,” adding that the extra year gives users “more time and flexibility to find the best PC for their needs while keeping them protected.”

In terms of enrollment, nothing has changed: users can enroll for free by syncing their PC settings to a Microsoft account through Windows Backup, by redeeming 1,000 Microsoft Rewards points, or with a one-time payment of $30. Users in Europe can enroll at no cost simply by signing in with a Microsoft account, a concession Microsoft made after pushback from consumer advocacy groups over its original requirements. A single ESU license covers up to 10 devices tied to the same account.

Microsoft's consumer program is limited to personal devices, however. Systems joined to an Active Directory domain or to Microsoft Entra, or managed through Mobile Device Management, are corporate-controlled and therefore not eligible. Personally owned machines that are only Entra-registered — e.g., a work account added to a personal device, rather than the device itself being organization-owned — still qualify.

Windows 11 has surged to roughly 73% of desktop share against Windows 10’s 26%, so it’s clear that the broader migration is working. Those users still on Windows 10 are increasingly the difficult edge cases, with around 400 million active PCs unable to officially upgrade to Windows 11 because their hardware fails its TPM 2.0, Secure Boot, or supported-processor requirements.

Users of those machines face a choice of remaining on unsupported Windows 10 or upgrading their hardware outright. But thanks to the AI-driven memory shortage, doing so has never been more expensive: DRAM contract prices have roughly doubled since early last year (and are expected to double again) as Samsung, SK Hynix, and Micron divert wafer capacity toward high-bandwidth memory for AI accelerators.

IDC expects PCs, tablets, and smartphone prices to rise 10% to 20% through the end of 2026, with memory now accounting for a far larger share of a system's bill of materials than it did two years ago.

For users unwilling to buy new hardware at current prices, some third-party options remain. The security firm 0patch has pledged to provide unofficial Windows 10 micropatches through 2030, and Linux migration efforts such as the End of 10 initiative continue to court holdouts whose machines can’t run Windows 11.

People seem all too ready to anthropomorphize LLMs and AI chatbots like ChatGPT, Claude, and Gemini. Some humans even admit to ‘relationships’ with one or more of the various examples of machine intelligence. To illustrate how flawed this instinct could be, a Microsoft AI researcher built a tiny neural network inside Age of Empires II using goats, grass, and bridges. Adrian de Wynter shared his work in a paper dubbed If LLMs have human-like attributes, then so does Age of Empires II. The Microsoft researcher, based at the University of York, also talked to 404 Media recently about how he likes to turn absurdism up to 11 to make a point.

In the research paper, De Wynter doesn’t make the argument that LLMs do or do not actually have generalized anthropomorphic attributes. Instead, he illustrates that the AoEII goats can also power the kinds of models that lay behind today's most popular chatbots. That hammers home the argument that “in no case is a machine’s activity to be interpreted in terms of higher cognitive processes, if it can be fairly interpreted in terms of processes which stand lower in the scale of cognitive evolution and development.”

De Wynter also raises the well-known concept of confirmation bias. Those looking for human traits in tech like chatbots will tend to find them, he proposes. However, the big contrast between the absurdist goat example and the commercial LLM chatbot is the way people interact with them, the interface that makes the likes of Claude ‘conversation friendly.’ De Wynter’s research indicates that anthropomizing LLMs is a common trend in computer science papers. From 337 such papers De Wynter looked at, published in the last two years, he says that 57% assumed that LLMs could have human-like traits. This basic assumption could color the research, testing, and, of course, conclusions of these papers.

So, how did the Microsoft AI researcher build the goaty AoEII LLM? Well, he didn’t quite go as far as developing a full-blown LLM. Instead, De Wynter thought it sufficient to use AoEII’s scenario editor to build a working NAND gate, with a 1-bit perceptron, where the goats act as bits. This crude perceptron and the circuit to train it in-game are enough to demonstrate that the simplest building block of a modern neural network could be made this way. And if you think it is absurd that AoEII goats can embody consciousness, then it should be equally absurd to regard any of the well-known chatbots as anything more.

Companies behind the AI boom aren’t discouraging people from anthropomorphizing their wares. In many ways, they might benefit from these human perceptions. Chatbots they deploy are trained with natural language and use techniques to mimic the shape and tone of natural conversation. This makes it easy for users to project personality, emotion, or even consciousness onto them. Top AI company execs have leaned into the perception of their customers, publicly entertaining the idea that their systems could or might be exhibiting signs of consciousness. In his 404 Media interview, De Wynter also highlighted research indicating that people buy more products when they can empathize with them, and that includes AI/chatbot/LLM subscriptions.

Microsoft has quietly updated its consumer-oriented Surface lineup with Qualcomm's Snapdragon X2 chips. The Surface line, often announced with its own event, has been detailed in a blog post by corporate vice president for Surface Brett Ostrum. All three systems are on sale from Microsoft's website today. The 13-inch Surface Pro starts at $1,499, while the Surface Laptop line starts at $1,599 for the 13.8-inch machine and $1,699 for the 15-incher.

The new systems aren't particularly different on the outside, coming in platinum, black, and dune colors that Microsoft has used before. The 13.8-inch Laptop option will have one brand new color: a standout jade green.

All of the systems will have options between 10-core Snapdragon X2 Plus or 12-core Snapdragon X2 Elite processors, and range from 16GB to 64GB of RAM (some of the Surface for Business models Microsoft announced with Intel's Panther Lake processors start with just 8GB of memory).

The Surface Pro starts with 256GB of storage and goes up to 1TB, while the Surface Laptop 13.8 goes up to 2TB. The 15-inch Laptop starts at 512GB and goes up to 2TB.

While all of the devices use Microsoft's PixelSense Flow displays with variable refresh up to 120 Hz, but only the Surface Pro includes both LCD and OLED options. The touchpad on the Surface Laptop has new haptic feedback technologies, working with Windows for small pieces of feedback throughout Windows. On the Surface Pro, you can get similar feedback with the Slim Pen.

The Surface Laptops have 1080p cameras that Microsoft boasts are best in class with No. 1 rankings from DXOMARK. That judges color, texture, noise, and artifacts, but doesn't seem to consider resolution. Some premium PCs have 4K or higher webcams now.

Microsoft is promising up to 20 hours of battery life on the 13.8-inch Surface Laptop when measured with local video playback. That drops to 16 hours when tested with web usage. We'll have to see how that holds up in our labs.

All three devices maintain Microsoft's Surface Connect port, and come with 39W chargers in North America. Microsoft notes that these aren't available in Europe, the Middle East, and Africa, so buyers in those locales will need to bring their own.

Business-focused models using Intel chips will launch on July 14.

Update, June 16, 10:26 a.m.: Microsoft shared a change to their spec sheet. The 13.8-inch Surface Laptop Pro will start with 512GB in the United States.

Microsoft CEO Satya Nadella has claimed that the company's newest generation of AI data centers uses so little water that its annual consumption is roughly equivalent to that of a single restaurant. Speaking at Microsoft Build 2026 on June 2, Nadella made the claim while outlining Microsoft's "Community-First AI Infrastructure" strategy aimed to address growing concerns about the impact of data centers on local communities.

"The cooling loop is filled once, and the data center can operate effectively with zero water consumption," Nadella said during his keynote, while describing how new architectures are redefining data center water consumption. "The daily water usage over the course of an entire year is roughly equivalent to what a single restaurant would use."

While Nadella did not specify the size or type of restaurant used for comparison, the claim is striking given the scale of modern hyperscale AI facilities. Industry estimates suggest that restaurants can consume anywhere from several hundred thousand to more than a million gallons of water annually, while 100MW+ hyperscale data centers have historically required tens to hundreds of millions of gallons of water annually for cooling, depending on climate, workload, and cooling design.

Nadella's statement — not the first time Microsoft has used a restaurant comparison — is based on Microsoft's new closed-loop liquid-cooling architecture. Traditional data centers often rely on evaporative cooling systems that continuously consume water to remove heat generated by servers and networking equipment. In Microsoft’s new approach, over 90% of the facility's cooling relies on a closed-loop liquid cooling system that is filled during construction and then continuously recirculates the same water rather than constantly consuming a fresh supply. The remaining portion of the cooling system primarily relies on outside air and only uses additional water in the hottest conditions.

The system works by circulating cooled water through heat exchangers connected to the AI hardware. As the water absorbs heat, it is routed to a massive chiller plant where large cooling fans dissipate the heat before the water is recirculated back through the facility. Because the water remains in the cooling loop rather than evaporating and being discarded, ongoing water consumption is dramatically reduced. This can translate to savings of multiple billions of gallons of water across Microsoft’s data centers.

The current reality is much more subdued. The new cooling design and its water savings are currently implemented only at Microsoft's Fairwater AI data center campus in Mount Pleasant, Wisconsin. On the other hand, the company has stated that the new cooling approach will become the standard design for future AI-focused data centers. Microsoft has confirmed that multiple identical Fairwater facilities are already under construction elsewhere in the United States as part of a broader expansion of its AI infrastructure footprint. The rollout forms part of Microsoft's longer-term goal of becoming water positive by 2030, meaning the company aims to replenish more water than it consumes globally, as part of its community-first strategy.

While the new cooling design will substantially reduce water use in future facilities, critics note that Microsoft already operates a vast global network of data centers. Azure now spans more than 500 facilities across 80 regions worldwide, many of which were built before Fairwater's cooling architecture was introduced.

Microsoft has not announced a comprehensive retrofit program that would convert existing data centers to the new closed-loop design. As a result, the "restaurant-level" water footprint applies primarily to newly built facilities that use the Fairwater blueprint, rather than to Microsoft's entire global infrastructure estate.

The debate reflects a broader challenge facing the AI industry. Companies, including Microsoft and Google, are racing to build ever-larger AI clusters while facing mounting public pressure to reduce their environmental impact, as communities grow increasingly disapproving of large-scale AI infrastructure projects. Google recently announced a series of water stewardship commitments of its own, including a pledge to replenish more water than its data centers consume by 2030.

Microsoft has unveiled Project Solara, a chip-to-cloud platform designed to power a new generation of "agent-first" enterprise devices — hardware designed to run AI agents instead of traditional apps. Announced at the Microsoft Build 2026 Developer Conference on the 2nd of June, the platform, developed by Microsoft's Applied Sciences Group, features a lightweight edge OS called the Microsoft Device Ecosystem Platform (MDEP). Interestingly, the OS is built on the Android Open Source Project (AOSP) rather than Windows.

MDEP is paired with Azure-hosted agent services and persistent cloud-based state, meaning devices act as interfaces to AI agents running across Microsoft's cloud infrastructure rather than as fully self-contained computers. Together, the software stack forms what Microsoft describes as a chip-to-cloud architecture for enterprise AI devices, combining cloud-hosted agents with centralized security, management, and orchestration capabilities.

"The 'operating system' is liminal, transcending the device and the cloud. The system brings a lightweight window to the edge, where the agent manifests and where the state, via Azure, can encompass a constellation of specialized devices,” explained Steven Bathiche, Microsoft's Corporate Vice President and Technical Fellow in the Applied Sciences Group.

To populate that ecosystem with hardware, Microsoft has partnered with Qualcomm and MediaTek as its first silicon partners — Qualcomm for portable and wearable form factors and MediaTek for stationary devices. The company has no plans to manufacture end products itself. Instead, the company is releasing reference designs for OEMs to build from, alongside an "approved chipsets" requirement that gives Microsoft certification-level control over which hardware qualifies for the platform, similar to Google's GMS certification model for Android.

To demonstrate Solara, Microsoft unveiled two concept reference designs built on the platform. A stationary desk-mounted AI hub built around MediaTek IoT silicon and a wearable AI badge powered by Qualcomm hardware. The desktop companion features a display, a camera, a UWB (ultra-wideband) presence sensor that handles automatic login and lock, dual far-field mics, and two USB-C ports. Connected to an external display, the device can double as a Windows 365 cloud PC client.

Meanwhile, the wearable badge is equipped with a touchscreen, Hello for Business fingerprint sensor, far-field high-SNR microphone array, side-facing camera, and 5G, WiFi, Bluetooth, and GNSS connectivity — targeting front-line workers such as nurses, retail staff, and field workers. Microsoft confirmed that both devices are intended as reference designs for OEM partners rather than retail products.

Central to the platform is what Microsoft calls just-in-time UI — an adaptive interface layer that allows a single agent to render appropriately across different screen sizes and input modalities without requiring developers to rebuild the experience for each device. Microsoft positions this on a spectrum between conventional responsive design and fully generative UI, where AI constructs interfaces dynamically with no predefined structure; Solara currently targets the middle ground, prioritizing consistency while avoiding per-device redesign overhead.

“The same agent can render a custom experience on multiple screen sizes and modalities with little or no additional work from the developer. For us, that is the first proof point: a path to specialized devices without requiring developers to rebuild the experience from scratch each time,” said Bathiche.

Another notable aspect of Solara is Microsoft's decision to build MDEP on Android rather than Windows. AOSP scales naturally to the lightweight, constrained hardware that wearables and embedded devices run on — something Windows, with its memory and processing overhead, was never designed to do. It also sidesteps the application compatibility expectations that come with Windows. Because Solara devices are built around cloud-hosted agents rather than traditional software, Microsoft can optimize the platform for dedicated AI hardware without carrying decades of legacy PC baggage.

To manage multiple agents running simultaneously, Microsoft is also working on an agent dispatcher and agent task manager — components that automatically surface or activate the right agent based on context, rather than requiring users to launch each one manually. Neither component is shipping yet. Early agent integrations include Dragon Copilot for healthcare workflows and GitHub Copilot for developer task tracking — both exploring how persistent, context-aware agents behave differently on dedicated hardware than they do inside a browser or IDE.

The platform appears to be aimed at enterprise buyers in retail, healthcare, and field service sectors, where dedicated agent hardware makes more sense than repurposing a smartphone. Microsoft has already lined up pilots with Best Buy, CVS Health, Levi's, Target, and AccuWeather, with broader OEM deployment targeted across healthcare, hospitality, financial services, legal, and industrial verticals.

The Great Exploitation of 2026 continues apace, with security vulnerabilities being published at an alarming rate, and more often than not, being exploited in the wild almost before anyone has any time to react. Today, Microsoft in the unfortunate limelight, with a 9.8-rated remote execution vulnerability affecting Windows Server domain controllers (DC), versions 2012 to current. The exploit and its explanation are simple: any unauthenticated user in the same network can send a malformed UDP packet to a DC and potentially get system access — no previous access required. Even if an attacker doesn't go that far, it's trivial for anyone to force the DC to reboot, creating potential denial-of-service scenarios.

The vulnerability is CVE-2026-41089, and it's mercifully not a zero-day this time. The vulnerable service is Netlogon, and there's apparently no mitigation, with the only solution being to patch the affected systems. The patch itself arrives in the May 12 Patch Tuesday, but there's a fair chance that a lot of DCs remain unpatched, particularly but not only older versions. Systems administrators might also find specific patch links and remediation scripts handy.

If an attacker can finagle this vulnerability to get System-level of access to domain controllers, the consequences are pretty up to the imagination. The malfeasant can create any number of accounts with all sorts of access levels, including Kerberos Ticket-Granting Tickets, enabling access to most all data across the entire domain. Since DCs often operate as part of a larger network in medium-to-large enterprises, just one vulnerable machine is enough to make the entire network insecure. Cybersecurity boffins recommend that administrators treat this as a worm-style threat and patch all their linked DCs at once, to avoid playing a game of whack-a-mole with high odds for the moles.

Microsoft stated that the vulnerability was not made public at the time, and that no ongoing attacks were using it, but the situation has changed since the discovery date, as recent reports have confirmed that it's now being exploited in the wild. As far as proof-of-concept goes, there's a GitHub repository with some sample code that forces the LSASS service to crash after a minute or so.

The technical details are simple and somewhat facepalm-inducing. The crafted network packet that triggers the vulnerability doesn't have anything all that fancy about it; it just contains one field that's larger than it should be. Data serialization logic in the Netlogon service combines the attacker-supplied data with the server's hostname, resulting in a classic buffer overflow — the most straightforward type of vulnerability.

Microsoft has been in security news quite often recently, mostly thanks to its ongoing spat with security researcher Chaotic Eclipse (aka Nightmare Eclipse), who published a heap of zero-days exploits after apparent negotiations with the company broke down. The situation is unclear, but has escalated to the point where Microsoft is now threatening Eclipse with legal action.

Microsoft has just announced the Surface Laptop Ultra, powered by Nvidia’s latest RTX Spark Superchip for laptops and desktop PCs, at Computex 2026. Claimed to be the most powerful Surface laptop device yet, the new Surface Laptop Ultra is essentially Microsoft’s answer to the current-gen MacBook Pro. The company has positioned the notebook primarily for AI development but also for creators and developers who seek powerful performance in a portable package.

Made in collaboration with Nvidia, the Surface Laptop Ultra will be one of the first devices featuring the RTX Spark Superchip. Nvidia’s new Windows on Arm platform is claimed to be more powerful and capable than any other on the market featuring 20 Arm CPU cores, a Blackwell GPU with 6144 CUDA cores, 128GB of unified LPDDR5X RAM, and up to 300 GB/s of memory bandwidth. The CPU and GPU are interconnected using NVLink C2C, while the large pool of unified memory can be dynamically allocated between the CPU and GPU. Offering up to 1 petaflop of AI compute, the RTX Spark is capable of running up to 120B parameter models locally.

As for the device itself, the new Surface Laptop Ultra will feature a 15-inch mini-LED PixelSense Ultra display with a resolution of 2880 x 1920, offering 262 pixels per inch. Microsoft claims that it can reach up to 2,000 nits of peak HDR brightness, which should be excellent for creators on the go. It also features a large haptic touchpad along with a good selection of ports, including HDMI, USB-C, USB-A, SD card reader, and a headphone jack. Weighing under just 4.5 pounds, it will be available in Platinum (silver) and Nightfall (black) color options. Microsoft claims all-day battery life on the laptop and an optimized internal layout with dual-fans to maintain proper thermals for sustained performance.

The new Microsoft Surface Laptop Ultra is expected to arrive later this year, with final pricing and availability to be announced closer to launch. With the ongoing RAM-apocalypse, it seems like a smart move by Microsoft to adopt Nvidia’s new Arm platform with unified memory. Beyond reducing the need for large pools of dedicated system and graphics memory, the architecture should also help improve efficiency and enable larger AI models to run locally without relying heavily on cloud resources. If Nvidia's performance claims hold up in real-world workloads, the Surface Laptop Ultra could emerge as one of the most compelling Windows alternatives to Apple's MacBook Pro for AI developers, content creators, and power users alike.

Some people are pretty excited that we are on the cusp of a new Windows PC era ignited by technologies from the mighty Nvidia and Arm. Our article on the teasers for the rumored wave of new N1X laptops makes it clear that companies like Nvidia and Microsoft are excited, at least. However, Microsoft veteran Steven Sinofsky is here to remind folks that it has been done before, with a similar level of simmering excitement, when the first Surface hybrid PC ran on Nvidia Tegra Arm silicon back in 2010/11.

Sinofsky shares some interesting media in the above embedded Tweet. There’s a slide from the promotional deck, shown at CES 2011, where the “strong partnerships” behind this Windows on Arm thrust would surely lead to unstoppable momentum. That’s what you may have believed if you swallowed the effusive presentations at the time.

This prior push for Windows on Arm didn’t exclusively support Nvidia Tegra. Sinofsky points out that Windows 8 on Arm also supported Qualcomm and TI processors. However, we saw Microsoft switch to a Qualcomm partnership focus in the years following. That collaborative effort also didn’t break through, even when the much-lauded Nuvia Oryon architecture arrived with the Snapdragon X family.

The former-President of the Windows Division (July 2009 to Nov 2012) also shares a video that should be preserved for posterity. Check it out to witness “an old school Windows Phone video of the first time Windows ran on Nvidia Tegra Arm using the desktop compositor which was a BIG deal. Sept 2010.”

The video appears to show a Tegra dev kit running Windows 7, with multi-window and Start menu manipulation, which looks rather lethargic to my eyes. However, that was a “first” achievement several months before CES 2011, and it would be over a year and a half until the Surface RT shipped to customers (October 2012).

Will the latest Nvidia and Arm thrust into Windows work out better? We’ll probably have a much better idea about that in the coming days at Computex. Sinofsky replies to some comments on his Tweet to say the result could be “a reliable platform for graphics compute,” using Windows. Pricing is also obviously going to be a sticky issue for any new platform looking to attract buyers right now.

Microsoft has uncovered an ongoing cryptojacking campaign that used SEO poisoning and, in some observed cases, AI chatbot-generated software recommendations to lure users into downloading GPU mining malware disguised as popular PC utilities. According to a detailed threat report published Tuesday by Microsoft Defender Experts and the Microsoft Defender Security Research Team, the operation specifically targeted users who likely own high-performance graphics cards, including gamers, hardware enthusiasts, AI users, and overclockers.

The campaign impersonated widely used utilities such as CrystalDiskInfo, HWMonitor, Display Driver Uninstaller (DDU), FurMark, K-Lite Codec Pack, and PDFgear. Victims searching for the software on traditional search engines — and, in some cases, via AI chatbot recommendations — were reportedly redirected to attacker-controlled download pages hosting malicious ZIP archives.

Microsoft says the attackers appear less interested in maximizing infection volume and more focused on compromising systems with powerful discrete GPUs suitable for profitable cryptocurrency mining. Once installed, the malware deployed persistent remote-access software using the legitimate ScreenConnect remote-management tool before silently loading GPU mining payloads such as lolMiner, gminer, and SRBMiner-MULTI.

The attack chain relied heavily on stealth techniques typically associated with more advanced malware operations. The downloaded archives bundled legitimate software installers alongside malicious DLLs that were automatically loaded through DLL sideloading. From there, the malware established six separate persistence mechanisms, added Microsoft Defender exclusions, checked for virtual machines and security-analysis tools, and used process hollowing to inject mining code into trusted Microsoft-signed .NET utilities such as MSBuild.exe, InstallUtil.exe, and RegAsm.exe.

Perhaps the most unusual aspect of the campaign, however, is Microsoft’s observation that some malicious domains may have surfaced through interactions with AI chatbots. According to the company, users requesting software download recommendations from large language model (LLM)-based assistants were, in some cases, presented with links to attacker-controlled domains embedded in generated responses. Microsoft stressed that the example was illustrative and “does not indicate a systemic issue with any specific AI service,” but noted that the activity appears consistent with emerging AI-assisted search-poisoning techniques.

According to Microsoft’s analysis, the operation has been active since at least March 2026 and involved more than 150 malicious domains masquerading as trusted utility-download portals. Many of the downloads were hosted on subdomains of gleeze.com, infrastructure linked to the Dynu dynamic DNS service, which has frequently been used in past phishing and malware campaigns.

The initial infection process itself was deceptively simple. Victims downloaded ZIP archives containing both the legitimate utility executable and a malicious DLL named autorun.dll. When the legitimate application launched, Windows automatically loaded the malicious DLL from the same directory via DLL sideloading — a long-standing Windows abuse technique that requires no software exploit and often produces no visible signs of compromise.

From there, the malware silently installed ScreenConnect, a legitimate enterprise remote-management platform also known as ConnectWise Control. Microsoft emphasized that ScreenConnect itself is not malicious, but rather is being abused by threat actors in the same way attackers increasingly misuse legitimate remote monitoring and management (RMM) tools to evade security scrutiny.

Once remote access was established, attackers deployed a binary called SimpleRunPE.exe, which Microsoft believes may partially derive from a publicly available GitHub proof-of-concept process hollowing project. The malware copied itself into hidden Windows directories as RuntimeHost.exe, created scheduled tasks and startup entries for persistence, and repeatedly re-added Microsoft Defender exclusions even if users or administrators attempted to remove them.

The malware also appeared engineered specifically to avoid detection by performance-conscious PC users. Microsoft says the miner monitored GPU utilization, system idle time, gaming activity, and streaming workloads, shutting down mining operations whenever heavy GPU activity was detected. In practice, this likely reduced obvious warning signs such as sudden frame-rate drops, overheating, or persistently loud GPU fans that might otherwise alert users to a compromise.

To further evade detection, the malware performed extensive anti-analysis checks before activating. The software scanned systems for virtual-machine artifacts, debugging tools, reverse-engineering platforms, packet analyzers, and forensic utilities, including Wireshark, ProcMon, x64dbg, dnSpy, IDA, and Ghidra. If any such tools were detected, the malware terminated itself.

Microsoft says the malware’s operators ultimately used the compromised systems to deploy one of several GPU-focused cryptocurrency miners, including lolMiner, gminer, and SRBMiner-MULTI. Rather than embedding the miners directly into the malware, the payload dynamically downloaded the most appropriate mining software after conducting extensive reconnaissance on the victim system, including GPU model, CPU specifications, installed antivirus software, memory configuration, and overall system activity.

The campaign highlights an alarming development in which attackers are now targeting not only search engines but also AI-assisted discovery systems. While traditional SEO poisoning has existed for years, the growing use of AI chatbots and LLM-powered assistants for software recommendations may be creating a new attack surface where malicious sites gain additional visibility through generated responses. Users need to be extra cautious, as even highly familiar utilities downloaded from seemingly convincing websites may carry hidden malware payloads, particularly when obtained through third-party mirrors or AI-provided links rather than official vendor pages.

Major tech companies are struggling to justify the skyrocketing prices of heavy AI usage, with even major tech firms like Microsoft and Uber looking at changes to their AI process. Following the recent viral post from Uber CTO Praveen Neppalli Naga that the company had blown through its entire 2026 AI budget in just a few months, Uber's Operations chief, Andrew Macdonald, said that token usage just didn't seem to have a direct correlation with useful consumer features.

Microsoft began revoking its developers' access to the Claude Code programming assistant earlier this month, with plans to move them over to the internal Copilot CLI tool by June 30. Although that has been framed as consolidating its teams onto the tools it's developing, it also comes right at the end of Microsoft's fiscal year, suggesting it may have also been a move to cut costs before the new year.

Worsening matters, Goldman Sachs estimates that Agentic AI could see token use increase by over 24 times in just the next few years. There appears to be a growing disconnect between AI needs, AI wants, and the reality of what AI companies can actually afford as costs mount.

Tokens and trade offers

We've been hearing reports for months about how companies and CEOs are struggling to find the tangible benefit of heavy AI deployment. Uber appears to be the latest AI boosting company to have this come to Jesus moment, following the CTO's explosive claims of annual budgets being wiped out in mere months. In the interview with Business Insider, Andrew Macdonald lamented that there just wasn't a clear correlation between the money Uber was investing in AI use and real consumer feature development.

Having talked to the senior engineers, he said there was no link between higher token usage and a proportional increase in consumer features with real benefits for their customers. Although he admitted more code was being shipped, it "was very hard to draw a line" between that and improvements in the software.

Meanwhile, after opening up its workers to Claude Code subscriptions in December last year, Microsoft is now clawing that back in what's seen by many as a financial move, as much as a consolidation. Microsoft also recently announced the switch of Copilot on GitHub to token-based billing, as the cost of running the tool ballooned earlier this year.

A major reason for this is the explosive growth in agentic AI use. These agents can eat up more than 1,000 times the tokens of a single AI chatbot.

Are more tokens really the answer?

Nvidia CEO Jensen Huang famously said in March this year that if an Nvidia engineer on $500,000 a year wasn't using at least $250,000 of tokens in that same period, he'd be alarmed. This isn't a rare sentiment, though. Many company CEOs are now bragging about the extent of their AI use, as if that alone equates to performance increases.

As Business Insider reports, Airbnb's CEO proudly told investors that 60% of the company's code was now AI-generated. Chime claimed it was shipping 84% AI code earlier this year, and even Google is claiming 50% of its code is AI-generated (though crucially, always checked by a human engineer).

Yet these numbers sound very similar to those of Uber. In the CTO's shocking report of budget runaway, they claimed over 80% of Uber software engineers were using agentic AI, and over 60% of the code was AI-generated. Even then, it's not worth the cost.

And those costs can be extreme if the guardrails are removed. OpenClaw creator and now OpenAI employee, Peter Steinberger, recently announced his team of three people had spent over $1.3 million in tokens in a single month running a suite of agentic AI tools.

This very much reinforces the idea that the cost of AI is rising above that of the workers it's supposed to be replacing. That makes many of the layoffs laid at the feet of AI efficiency and productivity increasingly shaky, unless these companies are simply racing to the bottom.

Or at least racing to new hardware. Goldman Sachs' recent AI agent report suggests that the massive efficiency gains coming from next-generation inferencing chips would make AI use so much cheaper that investment can continue unabated, and profit should follow, with AI agents increasing the revenue at AI companies enormously.

Faster, more efficient hardware will take too long

Nvidia will talk up its Vera Rubin platform at Computex and will officially launch it later this year. It improves AI performance by several times over, uses a new process node, and will reportedly offer as much as 10 times the performance per watt, making it dramatically more efficient than its predecessors.

Such huge gains would give the AI companies that first deploy these cards an enormous advantage over the companies still running Blackwell hardware, and even more so over older Hopper designs. But over 50% of the data center projects announced with Blackwell hardware in mind have been cancelled or delayed, and of those that do complete in the next year, just how keen are the developers going to be to replace those GPUs after they've barely gotten started?

In late 2025, Google, Oracle, and Microsoft all adjusted their plans for hardware in the other direction entirely, suggesting they would make it run for six years before replacing it. That seems impossible to square away with ambitious AI plans and hardware leaps every year.

More tokens on less efficient hardware

The reality is, even as some token costs are falling, the explosion in the number of agentic AI requires cannot be offset by hardware efficiency gains that are many years away from reaching effective deployment, if they ever get to the scale needed to catch up with this ramp-up in AI demand.

That means in the short term, even major companies like Microsoft and Uber are restructuring their use of AI to figure out how to continue using it at scale without nuking their budgets in the process. If those companies can't figure out how to afford it, it's increasingly difficult to imagine how the rest of us will be able to.

And if usage drops because of rising costs, the AI companies are never going to find the short-term profit they need to offset the enormous infrastructure spending they're still trying to justify.

There's been some drama unfolding lately in the Windows security world, and today's episode comes from yet another apparent run-in of researcher Nightmare-Eclipse (aka Chaotic Eclipse) against Microsoft. The company saw fit to ban Eclipse's GitHub account for as-of-yet unspecified reasons, forcing them to pack up and move shop to GitLab instead. Additionally, the Redmond firm had allegedly already deleted the Microsoft account Eclipse used for reporting the bugs.

In a blog post, Eclipse claims this action was vindictive, stating once again that Microsoft refused communication attempts and that they "got zero pennies from doing so", a likely allusion to unpaid bug bounties from the MSRC program. The initiative pays out up to $30,000 to $100,000 for per end-point zero-day depending on conditions, and a cool $250,000 if you can crack open Hyper-V. Already having six zero-day exploits under their belt, Eclipse claims that July 14 will bring a reckoning of sorts for the company, hypothetically in the form of more zero-day exploits being published.

Eclipse's dramatic dispute with Microsoft has been ongoing since early April, when they published the BlueHammer zero-day without warning. The language in their blog posts is unclear and passionate, directing cargo tanks of vitriol at Microsoft/MSRC. As a broad summary, Eclipse implies that Microsoft ignored or refused their zero-day reports and/or did not pay out bounties as requested, somehow causing financial harm in the process. Among other statements, Eclipse says "[they were] told personally by [Microsoft] that they will ruin my life and they did", that there's a dead-man switch of some sort, and that they "will make sure [Microsoft's] bones are shattered."

The saga has drawn speculation from other experts, like William Dormann from Tharros, who said that "MSRC used to be quite excellent to work with. But to save money, Microsoft fired the skilled people, leaving flowchart followers. I wouldn't be surprised if Microsoft closed the case after the reporter refused to submit a video of the exploit, since that's apparently an MSRC requirement now."

Microsoft has been mum on any details about these matters, so it's hard to tell if the situation is about an uncooperative researcher who doesn't follow standard disclosure rules or a company being difficult about security reports. Regardless, the move to ban Eclipse's GitHub account makes for poor optics, as it is being heavily criticized, and ultimately achieves nothing for security, since the code is out there anyway.

In this day and age, when AI-powered security research has arguably made the standard 90-day disclosure-to-patch window completely obsolete, and both time-until-exploit and unused exploits are both nearing zero, Microsoft and other software players would do well to adjust their policies.

Eclipse's technical track record is impressive. They published a string of zero-day exploits for Windows: BlueHammer gets access to the SYSTEM user via Defender, and RedSun does the same; UnDefend knocks Defender offline; GreenPlasma gets SYSTEM access via the CTFMon service, while MiniPlasma grants similar access via a flaw in the Windows Cloud Filter driver. Finally, there's YellowKey, a vulnerability in BitLocker that lets an attacker open up encrypted drives with next to no effort — precisely the action the technology was designed to prevent.

BlueHammer, RedSun, and UnDefend have all been confirmed to be undergoing active exploitation in the wild, and it's not hard to imagine the others are as well, as Eclipse's publications of full or partial proof-of-concept code made it trivial for an interested party to use them.

Many tech companies are pushing their employees to use AI tools and increase their productivity, but it seems that this initiative has begun to backfire. According to The Verge, Microsoft has been reportedly pushing its people to switch to its own Copilot CLI rather than Claude Code because it wants to use an internal tool rather than a third-party one. However, sources say the primary reason is that the cost of using Claude Code has been steadily increasing as more people use the AI tool.

Microsoft is not alone in this, as Fortune reports that other companies are also pulling back on AI usage. While it’s true that the cost of training AI models is falling, making AI tokens more affordable, people have started using more tokens in their day-to-day tasks. This is particularly true for agentic AI, which can use a thousand times more tokens compared to querying an LLM, depending on the number of steps needed to accomplish your instructions. For example, OpenClaw creator Peter Steinberger claimed that his team spent more than $1.3 million in token costs in just a single month. Because of this, it’s now apparent that using AI is more expensive than hiring people, especially since it offers only limited productivity gains at the moment.

Decreasing token costs, paired with increased usage, reminds us of the Jevons Paradox, in which increased efficiency has led to more people using a particular tool or technology. There are many examples of this throughout history — the introduction of efficient steam engines during the Industrial Revolution led more firms to deploy these tools to increase productivity. This is also evident in the airline industry: as planes became more fuel-efficient, lower ticket prices led to higher demand, and air travel demand is now on track to double by 2050, according to IATA.

It seems that this is also true with AI tools, especially as many companies are deploying them in a bid to increase productivity. Nvidia CEO Jensen Huang famously said that its engineers should use AI tokens worth at least half their annual salary each year to be fully productive, even going so far as to say, “Are you insane?” to managers who discouraged AI use. This phenomenon, called “tokenmaxxing,” has led many employees to use AI for just about anything to hit internal targets. This was evident at Amazon, where some team members admitted to using the tool for unnecessary tasks to inflate internal usage scores, and it has also been reported at other companies, such as Microsoft and Meta. Incidentally, these companies are among the biggest spenders on AI development.

It’s unclear yet whether these companies will change their policies now that increased token use, which comes with associated costs, has become an issue. AI is indeed a useful tool, but some companies are using it to replace people in a bid to cut labor costs. If the number of tokens needed to accomplish tasks outpaces the speed at which these tokens become cheaper, then that move might just backfire.

Microsoft announced Advanced Shader Delivery (ASD) for Xbox ROG Ally devices last year, bringing precompiled shaders to the handheld to improve load times. Since then, ASD has been included in the DirectX SDK, with both Intel and Nvidia already releasing their own versions of the tech. Today, AMD joins them as Microsoft expands ASD beyond handhelds to RDNA 3, RDNA 3.5, and RDNA 4 GPUs.

Forza Horizon 6 is the latest game to feature ASD on Windows 11 PCs, but you need the Microsoft Store/Xbox PC app version to take advantage of it. Using an RX 7600 GPU and a Ryzen 7 5800 CPU, Advanced Shader Delivery helped the game boot up 95% faster, taking only four seconds to load on first launch. Without ASD enabled, Forza Horizon 6 took nearly a minute and a half to load otherwise.

This is because every time you install a new game or go through an update, the game needs a fresh shader cache, which can take a few minutes to rebuild. Even if you don't touch the game, but your GPU drivers are updated, you need to recompile shaders for all of your games when you open them for the first time. This process is necessary because shader compilation is performed on-device and must account for hardware variability.

Microsoft's solution is to decouple shaders from drivers entirely and place them in a Precompiled Shader Database (PSDB) that lives in the cloud. Every time you download a game from the Microsoft Store or the Xbox PC app, ASD detects your specific configuration (game, GPU, driver) and downloads the precompiled shaders in advance. So, when you open the game, the shaders are already compiled, and you don't have to wait.

Consoles have done this forever, which makes sense considering they don't have to worry about different hardware configs. Even Valve has a version of precompiled shaders for Linux that it developed for the Steam Deck, but never ported to Windows. Since SSDs have made long load times a thing of the past, this has been one of the last remaining hurdles to instantaneous game launches.

Advanced Shader Delivery is available only on RDNA 3 and later GPUs and only on games downloaded via the Xbox PC app or the Microsoft Store. We don't know when other Windows marketplaces will adopt it, but at least 34 other games should support ASD right away, since they were part of the original announcement for the Xbox ROG Ally handhelds.

Moreover, you need to be enrolled in the Xbox Insiders program to get the Xbox Insiders Hub app, which is required to enable Advanced Shader Delivery, since Microsoft is classifying this as a preview. The company worked closely with AMD to develop it, which is why it's limited to RDNA 3+ hardware for now, because otherwise, it's supposed to be a universal solution for all GPUs on Windows 11 going forward.

Regardless, if you have an Nvidia GPU, the Nvidia app should have a feature called "Auto Shader Compilation" that does the same thing. It gives you more granular control over the size of the shader cache, too. If you're rocking an Intel GPU, then check out "Precompiled Shader Distribution" in the Intel Graphics app instead. Intel has implied that it's using its own cloud database for now, with the ASD standard being adopted later this year.

Microsoft has outlined a new feature of Windows called Cloud-Initiated Driver Recovery (CIDR). This newly introduced capability lets Microsoft remotely roll back a bad driver to a previously known good version on affected PCs. Moreover, it can work without user action or OEM intervention. It sounds like a magic bullet for a long history of Windows Update woes, but we’ll have to see if it works when the rubber hits the road. CIDR will only work with drivers distributed via Windows Update.

Windows Update can cause plenty of problems when a bad driver gets through testing and gets pushed to users. Indeed, buggy drivers have caused many a lost hour, gray hair, wrinkle, high blood pressure, and so on, among Windows veterans. Microsoft also notes that a bad driver often means a user has to manually intervene and roll back to “a low-quality driver for an extended period.” So, the new CIDR is cautiously welcomed.

Microsoft spells out the CIDR process in its Tech Community blog, and there we learn that recovery starts by the Windows developer triggering "a recovery action directly from the Hardware Dev Center (HDC) Driver Shiproom." Once a problematic driver is flagged, the system recovers the previously known-good version of a driver via the Windows Update pipeline. “This is handled through coordinated updates to the PnP driver stack and the driver flighting and publishing services,” says Microsoft.

Importantly, Microsoft notes that “recovery is delivered through the existing Windows Update infrastructure — no new client agent or partner tooling is required.” That should help CIDR work well with what we’ve already got and for it to become an established standard. Likewise, partners don’t need to get involved in CIDR, Microsoft will manage it. However, Microsoft asks that these partners “continue monitoring their driver quality metrics in the Hardware Dev Center dashboard and to respond promptly to any shiproom feedback on rejected submissions.”

CIDR is rolling out now for validation and testing, and it is expected to automatically support the Hardware Dev Center publishing process from September onwards.

Amazon is the latest hyperscaler where employees have been caught inflating AI token consumption to hit internal usage targets, following similar behavior documented at Meta and Microsoft last month, the Financial Times reports.

The company set targets requiring more than 80% of its developers to use AI tools each week and tracked consumption on internal leaderboards. Some employees told FT they had been using MeshClaw, an in-house agent platform that can initiate code deployments, triage emails, and interact with Slack to maximize their token numbers. Amazon said usage statistics would not factor into performance evaluations, but multiple employees said they believed managers were monitoring the data. One said there was "so much pressure to use these tools," another described how tracking created "perverse incentives."

The practice — dubbed "tokenmaxxing" — has become widespread enough to generate its own vocabulary and leaderboards, but beyond workplace culture, if a meaningful share of AI consumption is performative, how reliable are the demand figures that hundreds of billions in AI infrastructure procurement are being allocated against?

Combined 2026 capex from Amazon, Microsoft, Alphabet, and Meta is tracking between $650 billion and $700 billion, with some Wall Street projections exceeding $1 trillion for 2027, and every hyperscaler has told investors that inference capacity is being absorbed as fast as it can be deployed. Internal developer consumption is obviously part of that absorption, and it sits alongside paying external customers in the usage data that informs the likes of capacity planning, GPU orders, HBM procurement, and power infrastructure.

Tokenmaxxing doesn’t mean the demand is fabricated — enterprise AI adoption is broadening, and inference workloads are scaling into production — but there’s a distinction between adoption and consumption intensity. The former is a durable driver of demand, whereas the latter is gameable, and it’s currently being amplified by the incentive structures that these companies built. The water is further muddied by reports that AI is more expensive than actual workers.

Meta's internal leaderboard lasted days after public exposure, and Amazon recently restricted visibility of team-wide usage statistics. And when measurement shifts, the consumption intensity they incentivized will shift with them.

Nvidia CEO Jensen Huang has highlighted per-engineer token consumption as a key metric, stating he’d be "deeply alarmed" if a $500,000-a-year engineer was not consuming at least $250,000 in tokens. Nvidia's inference growth obviously depends on that consumption being a productive workload that persists and compounds because every inflated token is real GPU time.

Angie Jones, formerly VP of engineering for AI tools at Block, told LeadDev she expected the industry to pivot toward measuring efficient token usage rather than celebrating volume. In a cycle where GPU orders and power commitments are being placed years in advance, the quality of the demand projections behind them matters. The hyperscalers are building for a world where every knowledge worker consumes hundreds of thousands of dollars in annual compute. Whether that consumption proves productive or performative will determine how much of this year's $700 billion generates durable returns.

Microsoft Threat Intelligence said in an X post on Monday that it is investigating a compromise of the mistralai PyPI package after attackers reportedly injected malicious code that automatically executed on import, downloaded a secondary payload disguised as transformers.pyz, and launched malware on Linux systems — the latest incident researchers believe may be linked to the broader “Mini Shai-Hulud” software supply-chain campaign targeting developer ecosystems.

According to Microsoft, the compromised mistralai package version 2.4.6 contained malicious code inserted into mistralai/client/__init__.py that silently downloaded a file from a remote IP address to /tmp/transformers.pyz and executed it in the background whenever the package was imported on Linux machines.

The filename appears deliberately chosen to resemble Hugging Face’s widely used Transformers AI framework, potentially allowing the malware to blend into machine learning environments and evade suspicion. Microsoft said the second-stage payload functioned primarily as a credential stealer, but also contained country-aware logic and a destructive branch capable of executing rm -rf / under certain geographic conditions. The payload contained logic designed to avoid Russian-language environments, a behavior commonly observed in some cybercriminal malware campaigns, though such checks are not definitive indicators of attribution.

The disclosure comes amid a growing wave of software supply-chain compromises affecting both npm and PyPI ecosystems. Earlier Monday, security firm Aikido warned that malicious package versions tied to the popular TanStack JavaScript ecosystem had been compromised in two separate attack waves beginning around 19:20 UTC. Affected packages reportedly included @tanstack/react-router, @tanstack/history, and @tanstack/router-core, components collectively downloaded tens of millions of times per week.

Hours later, Aikido said several Mistral npm SDK packages had also been compromised as part of the same ongoing “Mini Shai-Hulud” campaign, including @mistralai/mistralai, @mistralai/mistralai-azure, and @mistralai/mistralai-gcp. The firm warned developers to immediately rotate GitHub tokens, npm credentials, cloud API keys, and CI/CD secrets if affected packages had been installed.

Microsoft has not publicly attributed the PyPI compromise to Mini Shai-Hulud. Still, the incidents share several characteristics, including malicious code inserted into trusted packages, staged payload downloads, credential theft, and automatic execution during installation or import. That overlap has raised concerns that attackers are increasingly targeting developer infrastructure itself rather than end users directly.

Modern development environments often contain high-value credentials, including GitHub personal access tokens, cloud deployment keys, SSH credentials, npm publishing tokens, and CI/CD system access. A compromised developer workstation or CI runner can therefore provide attackers with a path into much larger software ecosystems, allowing malicious updates to spread through legitimate package distribution channels.

The behavior observed in the compromised Mistralai package reflects that escalation risk. According to Microsoft’s analysis, the injected code silently used curl to retrieve the secondary payload before launching it as a detached background process designed to continue operating independently of the original Python session. The malware also reportedly suppressed execution errors and limited activity to Linux systems, the dominant operating system across servers, cloud environments, and many AI workloads.

Supply-chain attacks have become an increasingly serious concern across the software industry because of the sheer scale at which trusted dependencies are reused. A single compromised package can rapidly propagate into thousands of downstream applications, enterprise environments, and production systems. Major incidents in recent years have included the SolarWinds breach, the event-stream npm compromise, the 3CX supply-chain attack, and the XZ Utils backdoor attempt.

The latest wave appears particularly notable for simultaneously targeting AI tooling, cloud SDKs, and widely used frontend development frameworks. Researchers believe the campaign’s primary objective is credential theft, potentially allowing attackers to compromise additional packages, maintainer accounts, and publishing infrastructure in a cascading chain of ecosystem infections.

Microsoft advised organizations to isolate affected Linux hosts, block outbound connections to the malicious IP address, hunt for indicators including /tmp/transformers.pyz, pgmonitor.py, and pgsql-monitor.service, and rotate any potentially exposed credentials immediately. The compromises are still under investigation, and additional affected packages may emerge as maintainers and security firms continue auditing publishing infrastructure and compromised credentials.

A $1 billion data center that Microsoft and Abu Dhabi-based AI firm G42 planned to build in Kenya has stalled after the Kenyan government failed to meet Microsoft's demand for guaranteed annual capacity payments, Bloomberg reported Sunday. Kenyan President William Ruto put the scale of the project's power requirements into clear terms at a recent state event in Nairobi, saying the country would need to "switch off half the country" to keep the facility running.

The project, announced in May 2024 during Ruto’s visit to Washington, was supposed to bring a geothermal-powered data center to the Olkaria region in Kenya's Rift Valley. G42 was to lead construction, with the facility running Microsoft Azure in a new East Africa cloud region. The first phase targeted 100 megawatts of capacity and was expected to be operational by this year, with a long-term goal of scaling to 1 gigawatt.

President Ruto isn’t exaggerating about shutting off half the country’s power. Kenya’s total installed electricity capacity sits between 3,000 and 3,200 megawatts, and peak demand reached a record 2,444 megawatts in January, according to data from KenGen, the country’s government-owned electricity producer.

The full 1 gigawatt build would therefore have consumed roughly a third of the country’s total capacity, and even the first 100 megawatts would have required a significant share of the Olkaria geothermal complex's output, which currently generates around 950MW across all its plants.

John Tanui, principal secretary at Kenya's Ministry of Information, told Bloomberg that the project hasn’t been withdrawn and that talks are continuing, adding that the “scale of the data center they [Microsoft] wanted to do still requires some structuring.” A separate 60-megawatt project with local developer EcoCloud is also still under discussion.

Kenya’s Microsoft campus was set to be the first facility that Microsoft and G42 built together after Microsoft invested $1.5 billion in G42 back in 2024. That deal followed G42's agreement to divest from Chinese holdings and strip Huawei equipment from its systems under pressure from Washington. Microsoft President Brad Smith joined G42's board as part of the arrangement and described the Kenya project at the time as the “single biggest step forward” for digital technology in the country's history.

Meanwhile, Huawei is expanding its presence in Kenya, having launched a new fiber broadband service with Safaricom, Kenya’s largest telecom operator, last week. Africa currently hosts roughly 1% of the world's data center capacity.

Microsoft is spending $190 billion on capex in 2026, and the company adds approximately 1 gigawatt of data center capacity every three months globally. But power constraints are proving to be a universal bottleneck: nearly half of planned U.S. data center builds this year have been delayed or canceled due to shortages of electrical infrastructure.

A top Microsoft exec has admitted that Windows 11 still relies on a bunch of old code from the 1990s. It is refreshing for Microsoft Azure Chief Technical Officer Mark Russinovich to highlight this fact on social media, but it might not surprise as many folks as he thinks.

As Russinovich eloquently puts it, those of us invested in the computer scene in the 90s “were thinking flying cars and moon stations by the year 2026, not Win32.” The admission that such old software tech is still the "bedrock" of Windows today may be the CTO strategically sharing a cold, hard truth, providing a 'let's be real' moment as part of Microsoft’s latest charm offensive. Sharing a candid confession indicates that the corporation is actually aware of the issues in its OS.

Remember, the firm is currently in the midst of a major transformation, targeting enthusiast hot button areas like Windows performance, overhead, and reliability. This drastic pivot was cautiously welcomed in contrast to Microsoft being widely slammed for boasting about Windows “evolving into an agentic OS” last November. Currently, Microsoft seems to be flailing around, trying to stop folks straying to pastures greener like Mac and Linux.

However, Win32 isn’t inherently labeled as ‘bad’ by the Microsoft CTO. Though it is ancient, it has probably stuck around for good reason. “I think one of the reasons it’s got this staying power is just a fundamental layer inside of Windows that so many apps have built on,” notes Russinovich. “So many technologies and ecosystems have been built on top of it that it’s kind of a bedrock.”

The CTO explains that Win32 has persisted even when facing targeted existential threats from within Microsoft, particularly in the Windows 8 era. “There’s been various times in Microsoft’s history where we thought we’d reboot the Windows API surface, like WinRT, that actually didn’t play out the way a lot of people expected it to.”

In closing, Russinovich highlights that Win32 was also the bedrock for tools like Sysmon and ZoomIt, which he actually wrote back in 1996. These tools are now “more relevant than ever in 2026,” as parts of Windows 11 and PowerToys, respectively, reckons the CTO.

Xbox CEO Asha Sharma announced on X on Tuesday that the company is winding down its Copilot for Gaming feature on mobile and canceling its planned console launch.

Sharma also unveiled a broad leadership overhaul, bringing in four senior executives from her former CoreAI engineering group at Microsoft, according to an internal memo reported by CNBC. Sharma called the Copilot pullback part of a push to "retire features that don't align with where we're headed."

Microsoft first unveiled Copilot for Gaming at GDC in March 2025, positioning the AI assistant as a real-time sidekick that offers gameplay tips, coaching, and session recaps. A beta rolled out to the Xbox mobile app, then expanded to the PC Game Bar in September, and the ROG Xbox Ally handheld. Then came a privacy backlash in October after a user discovered that it was sending screen-activity data to Microsoft's servers by default.

Sharma hasn’t addressed the status of Gaming Copilot on the PC Game Bar or the ROG Xbox Ally handheld, leaving the future of those versions unclear. In the memo, Sharma wrote that Xbox needs to "evolve how we work" and acknowledged the division spends "too much time inward instead of with the community."

She appointed four executives from CoreAI: Jared Palmer, formerly VP of product at CoreAI and a senior VP at GitHub, will serve as VP of engineering and technical advisor to Sharma; Tim Allen, previously CoreAI's VP of design, becomes head of Xbox design; Jonathan McKay, who held growth roles at OpenAI and Meta before leading CoreAI growth, takes on the same function at Xbox; and Evan Chaki, a CoreAI general manager, will lead a new team focused on simplifying development workflows. A fifth hire, David Schloss, joins from Instacart to oversee Xbox's subscription and cloud business.

Two senior Xbox executives are departing. Kevin Gammill, corporate VP of gaming ecosystem organization, is leaving the company. Roanne Sones, corporate VP of Xbox devices and ecosystem, will take a leave of absence after the summer, then transition to an advisory role.

Sharma took over as Xbox CEO in February after Phil Spencer retired following 38 years at Microsoft. Since then, she has axed the "This is an Xbox" marketing campaign, cut Game Pass prices, rebranded Microsoft Gaming back to simply Xbox, and outlined a back-to-basics strategy focused on console and community. The leadership changes arrive as Xbox continues to struggle financially: gaming revenue fell to $5.3 billion in the most recent quarter, down from $5.7 billion a year earlier, and hardware revenue dropped 33%.

A new Microsoft-backed AI study claims a 'Transformation Paradox' is holding back the adoption of AI in workplaces, with many users preferring to focus on current goals rather than AI innovation. According to the Microsoft study, only 1 in 5 workers are equipped to use AI tools and are in an environment where management clearly supports it. On the other hand, nearly half of the survey respondents are in an unclear situation, where both individual skill and conditions within their organization are still unclear when it comes to AI policies.

Many companies are deploying AI for the sake of it, with only a few reporting actual gains from its use. The Microsoft study seemingly investigated this phenomenon, and it found that the issue isn’t caused by the lack of adoption, but the policies behind it. “What emerges is a pressure point within the organization where the pull to perform collides with the push to transform,” the research paper said. “65% of AI users fear falling behind if they don’t use AI to adapt quickly, yet 45% say it feels safer to focus on current goals than to redesign work with AI. And only 13% of AI users say they’re rewarded for reinvention of work with AI even if results aren’t met.” Microsoft calls this phenomenon 'The Transformation Paradox' and says, "The same forces accelerating AI adoption are holding it back."

Some experts are hailing AI as the fourth industrial revolution, and say it will change how we execute many of our day-to-day tasks. However, this study is saying that it’s not just enough to give workers access to AI tools — instead, management must also change how it measures productivity and even be willing to revamp existing workflows and policies to take AI tools into account.

This rush to integrate AI without considering how it can be effectively used is leading to a lot of negative effects. Even OpenAI CEO Sam Altman said that many of the reported layoffs across the globe were being falsely attributed to AI, with some experts saying that it was, in fact, due to poor business decisions. Although it cannot be denied that this tool will lead to a massive disruption to the job market, one study suggested that AI firms making the most use of AI are hiring more people.

As the cost of using AI is increasing and is now comparatively more expensive than actual workers, using these tools as efficiently as possible has never been more important. And while executives can easily sign up their people for an AI subscription, Microsoft’s study suggests that until companies change their approach to their business from the top down, they won’t be able to maximize these tools and will be left behind by companies that do. We should note, though, that Microsoft sponsored this research paper and that it has invested billions in Copilot, OpenAI, and AI data centers, so it stands to gain from the wider adoption of AI.

Google, Microsoft, and Elon Musk's xAI agreed today to give the U.S. Commerce Department's Center for AI Standards and Innovation (CAISI) access to their AI models before public release, Bloomberg reports. OpenAI and Anthropic, which had existing evaluation partnerships with the center dating to 2024, renegotiated their deals to align with priorities in Trump's AI Action Plan, the agency said.

The agreements mean that every major U.S. frontier AI lab now participates in voluntary pre-release government evaluations. CAISI has completed more than 40 model assessments to date, including evaluations of unreleased state-of-the-art systems, according to the Commerce Department.

CAISI operates within NIST and was originally established in 2023 under Biden as the AI Safety Institute. The Trump administration renamed it last June, with Commerce Secretary Howard Lutnick calling the rebrand a move away from what he called regulation "used under the guise of national security." Despite the shift in rhetoric, the center's core function has remained largely the same: evaluating frontier models for cybersecurity, biosecurity, and chemical weapons risks.

"These expanded industry collaborations help us scale our work in the public interest at a critical moment," CAISI director Chris Fall said of the new agreements. Fall took over the center after Collin Burns, a former Anthropic and OpenAI researcher, was pushed out just four days into the job. The Washington Post reported last month that White House officials were concerned about Burns's Anthropic ties, given the administration's ongoing dispute with the company. Burns had relocated across the country and given up Anthropic equity to take the position.

The center still lacks permanent legal standing, and some lawmakers have introduced draft legislation to codify it, but nothing has passed. Trump's AI Action Plan, announced in July last year, directs CAISI to serve as part of an "AI evaluations ecosystem" and lead national security-related model assessments. It also instructs regulators to explore using evaluations when applying existing law to AI systems.

Anthropic's renegotiated deal with CAISI sits alongside a separate and hostile set of interactions with the federal government. The Pentagon designated Anthropic a supply chain risk in March after it refused to lower guardrails on autonomous weapons, though a federal judge later called that move "Orwellian." Both Defense Secretary Pete Hegseth and Trump have outlined a six-month phaseout period for government use of Anthropic's tools, and two active lawsuits remain unresolved.

The new CAISI agreements also come one day after reports that the Trump administration was considering a mandatory pre-release review process for AI models via executive order, with Anthropic's Mythos model cited as the catalyst. The voluntary agreements announced Tuesday, and any potential mandatory review framework, would run in parallel, though it remains unclear how they might interact.

Microsoft continues to make some of the earliest chapters of its operating system history open-source and freely available. Earlier this week, it announced that Tim Paterson's DOS listings, containing source code of the 86-DOS 1.00 kernel, various PC-DOS 1.00 pre-release kernels and utilities, and the Microsoft BASIC-86 Compiler runtime library, were available on GitHub. Microsoft VP Scott Hanselman tied the release to 86-DOS 1.00’s 45th anniversary. The exec confirmed that the code, transcribed from reams of old dot matrix printouts found in a garage, was perfect, "and recompiles byte for byte to the original binaries.”

If you head on over to the GitHub page to snag the code, you will see a photo of Tim Paterson standing in his garage with a pile of yellowed dot matrix printouts in the foreground. These pages contain the code for the software mentioned in the intro, and you can even see the original scans in PDF and PNG format via a link to the Internet Archive. These include the coder’s handwritten notes.

Probably more important to tinkerers, though, is the fact that the work of transcribing the printed code has been completed (for those three mentioned wares). Tips to compile and assemble the sources can also be found on Paterson’s GitHub.

From 86-DOS to MS-DOS

In case you aren’t familiar with the place of 86-DOS (or Tim Paterson) in Microsoft’s history, here's a short refresher. Microsoft took a shortcut and gained a foothold in the OS software market by purchasing 86-DOS from Seattle Computer Products and inventor Tim Paterson for a figure in the region of $75,000.

In the GitHub repository, you can see 86-DOS’s transformation into the PC-DOS 1.00 kernel, alongside code for some well-known utilities (still in use today) such as CHKDSK. As the Microsoft blog asserts, this work “offers rare insight into how MS-DOS/PC-DOS came to be, and how operating system development was done at the time, not as it was later reconstructed.”

So, we have another old DOS release to tinker with. In April 2024, we reported on Microsoft releasing the code for MS-DOS 4.00 under the generous MIT License, allowing tinkerers free rein. It did the same with MS‑DOS 1.25 and 2.11 in 2018. Also in 2024, we coincidentally covered a video demo featuring 86-DOS version 0.1C being taken for a test drive (via the Internet Archive), and now version 1.00 of this OS has hit GitHub, straight from the files squirreled away in Tim Paterson's (the creator’s) garage.

We’re still waiting for any version of Windows to be open-sourced. You have to dig through leaks if you are curious enough to want to investigate the source code for Windows XP, for example.

The U.S. Department of War has announced deals with "seven of the world’s leading frontier artificial intelligence companies" for operational use. According to the Classified Networks AI Agreements press release, SpaceX, OpenAI, Google, Nvidia, Reflection, Microsoft, and Amazon Web Services will deploy their LLMs across the Pentagon’s classified networks “for lawful operational use.” The government said that this move will help turn the United States military into “an AI-first fighting force” and will help with “decision superiority across all domains of warfare.”

It seems that the AI tools that these companies offer will, for now, be limited to data analysis and help make decision-making faster and easier as the U.S. faces complex situations. These tools are accessible via GenAi.mil, the Pentagon’s official AI platform, through the Department of War’s network and are widely available for its personnel.

“Over 1.3 million Department personnel have used the platform, generating tens of millions of prompts and deploying hundreds of thousands of agents in only five months,” the Pentagon said. “Warfighters, civilians and contractors are putting these capabilities to practical use right now, cutting many tasks from months to days.”

Nevertheless, there have been concerns about the use of AI in military applications. Anthropic has famously refused to budge on the Department of War’s demand to lower its safeguards, saying that doing so could mean that its AI products could be used for mass surveillance or to create autonomous weapons. This move resulted in President Donald Trump banning the company from federal agencies, even going as far as designating it a supply chain risk for refusing to bow to the federal government’s demands.

While AI is certainly useful for distilling massive amounts of information and spotting patterns that humans can miss, it’s still not a 100% reliable tool for making decisions that could have a global impact. A researcher discovered this when they pitted GPT-5.2, Claude Sonnet 4, and Gemini 3 against each other in a wargame, with 95% of the outcome ending in a tactical nuclear strike. Three scenarios even ended in a strategic nuclear strike that would have ended the world.

But even though these AI tools are limited to analysis and support, with a human operator at the helm still responsible for every decision, there’s also the risk of automation bias. This is a person’s tendency to follow a computer’s suggestion despite contradictory information, especially as AI systems can process a ton of data so much more quickly than any human could. However, the data the AI is relying on could be false, erroneous, or misinterpreted, so it’s crucial that humans apply their intuition and experience before accepting AI suggestions at face value.

The U.S. military isn’t the only one experimenting with and deploying AI technologies in operational use. China, for example, has been showing off a 200-strong AI drone swarm that can be controlled by a single soldier, as well as ground-based drone wolfpacks armed with machine guns and grenade launchers for urban combat. While we cannot stop these armed institutions from deploying AI tools for intelligence-gathering, reconnaissance, and decision-making on the battlefield, we can only hope that they do not ignore safeguards and never give AI the triggers to any weapon.

Google, Amazon, Microsoft, and Meta plan to spend a combined $725 billion on capital expenditure in 2026, a 77% increase over last year's record $410 billion, according to first-quarter earnings reports compiled by the Financial Times.

Google led with 63% cloud revenue growth and an 81% jump in net income to $62.6 billion, while Meta's stock dropped 6% after hours despite a 33% revenue increase, punished by investors for adding $10 billion to its spending forecast and offering no firm timeline on new AI models.

But in the earnings calls, at least two of the four companies explicitly blamed rising memory chip prices for pushing budgets higher, confirming what market data and industry executives have been warning about for months.

Memory costs inside the capex

Microsoft’s CFO, Amy Hood, told investors that rising prices for memory chips and other components accounted for $25 billion of the company's record capex budget. Microsoft set its 2026 spending at $190 billion, far above the $152 billion average analyst forecast. Hood warned that even with the additional investment, Microsoft expects to remain capacity-constrained on GPUs, CPUs, and storage through at least 2026.

Meta cited the same, with the company raising its full-year capex range to $125 billion to $145 billion, up from a prior ceiling of $135 billion. In its earnings release, Meta attributed the increase to "higher component pricing this year, particularly memory," alongside rising costs for land, power, and skilled workers needed to build data centers that now consume 70% of the world's memory output.

The timing of all this is hardly coincidental, with TrendForce having reported DRAM contract prices rising roughly 95% quarter over quarter in Q1 2026, with a further 58% to 63% increase projected for Q2. NAND is following a similar trajectory, with Q2 contract prices expected to climb 70% to 75%. Server DRAM and high-density DDR5 RDIMMs are absorbing the bulk of production capacity, and all NAND output for 2026 is already committed, according to Phison CEO Khein-Seng Pua.

Hood's $25 billion, therefore, helps to put a dollar value on what has previously been an abstract concern: If one company's memory cost inflation alone exceeds the entire annual capex of most semiconductor firms, the pressure on consumer DRAM and NAND supply becomes much easier to quantify.

Google Cloud's contract backlog

Meta and Microsoft aside, Google’s Cloud revenue hit $20 billion in the same quarter, growing 63% year over year, outpacing both Amazon Web Services ($37.6 billion, up $8.3 billion) and Microsoft's Azure-driven cloud segment ($34.7 billion, up $7.9 billion).

Google's cloud contract backlog reached $460 billion, roughly double the $240 billion reported at the end of Q4 2025. Amazon reported $364 billion in its own pipeline, which will expand further after a recent $100 billion computing contract with Anthropic over the next decade. Microsoft's commercial remaining performance obligations hit $625 billion, up 110% year over year.

Cloud boss Thomas Kurian attributed Google's growth to its strategy of building custom AI chips, foundation models, and products in-house, telling the Financial Times that this gives the company a cost and research advantage over competitors that have struggled to develop their own chips and frontier models. Google's 7th-gen Ironwood TPU, which packs 192 GB of HBM3E per chip with 7.37 TB/s bandwidth in pods of up to 9,216 chips, is central to that strategy, and Anthropic has committed to access up to one million of them. Google recently unveiled its 8th-gen TPUs, which are split into two distinct variants for training and inference.

Alphabet raised its capex guidance to between $180 billion and $190 billion, up $5 billion from its previous guidance of $175 billion. CFO Anat Ashkenazi said he expects capex to “significantly increase” in 2027, causing shares to rise by some 7% after hours. It’s worth noting that $37.7 billion of Alphabet’s net income of $62.6 billion came from unrealized gains on non-marketable equity securities, primarily the company's Anthropic stake, according to the earnings release filed with the SEC. Strip that out, and operating performance was still strong, with a 36.1% operating margin, but the total net income number overstates recurring profitability.

Custom silicon and the GPU question

These capex figures reflect more than GPU purchases, because each hyperscaler is now deploying or developing custom accelerators to reduce dependence on Nvidia for inference-based workloads.

Amazon's Trainium3, built on a 3nm process with 144 GB of HBM3E and roughly 4.9 TB/s of bandwidth, is what CEO Andy Jassy described as "nearly fully subscribed" for 2026, and Meta has announced four generations of its MTIA inference chip, all fabbed at TSMC alongside Broadcom, even as it signed GPU deals worth roughly $110 billion combined with AMD and Nvidia. Meanwhile,. Microsoft's Maia 200 is deploying in U.S. Central data centers.

This pattern is likely to extend beyond accelerators as CPU demand for agentic AI workloads drives a parallel supply crunch with CPU lead times currently stretching to six months. Intel has reported billions in unmet Xeon demand, and Arm CEO Rene Haas has stated that agentic workloads require roughly 120 million CPU cores per gigawatt of data center capacity, four times what traditional AI training clusters need. Per Intel CFO David Zinsner, data center CPU-to-GPU ratios have already moved from 1:8 to 1:4, with further convergence expected to reach or go beyond parity.

Despite record spending, all four companies have acknowledged supply constraints that additional capital alone can’t resolve. Nvidia has booked an estimated 800,000 to 850,000 wafers of TSMC's CoWoS advanced packaging capacity for 2026, consuming over half of the total output and leaving AMD, Broadcom, and Google's TPU program competing for the remainder. CoWoS remains oversubscribed through at least mid-2026, and TSMC's U.S. packaging fabs aren’t expected to reach volume until 2028.

Power infrastructure is another bottleneck, with large power transformer lead times extending to roughly 128 weeks, and the IEA estimating that approximately 20% of planned global data center projects could be at risk of grid-related delays. TrendForce recently downgraded its full-year server shipment growth forecast from 20% to 13% because power management ICs and baseboard management controllers needed to assemble complete servers are stretching to 35- to 40-week lead times. Samsung's planned closure of its S7 eight-inch wafer fab in Korea will tighten PMIC supply further.

‘The bear thesis is garbage’

Meta's stock slipped by 6% after-hours following the earnings, erasing roughly $113 billion in market value. That drop reflected both the $10 billion capex increase and CEO Mark Zuckerberg's lack of a firm schedule for releasing improved AI models to follow the recently launched Muse Spark. Dec Mullarkey, managing director of SLC Management, told the FT that investors are concerned about whether Meta's historically capital-light business is becoming far more capital-intensive.

"The bear thesis is garbage," countered Brent Thill, an analyst at Jefferies, arguing that revenue growth across the sector justifies the spending. Zuckerberg offered little to settle the debate. Asked about Meta's AI agent development, he told investors he cared more about quality than deadlines, adding that most AI agents available today are not good enough for everyday users.

Amazon kept its $200 billion capex plan unchanged, and Microsoft CEO Satya Nadella said ending his company's exclusive contract with OpenAI was beneficial, claiming royalty-free access to OpenAI's frontier models and IP through 2032.

Microsoft announced yesterday that Xbox Mode is rolling out to Windows 11 PCs, bringing the controller-optimized, full-screen gaming interface to desktops, laptops, and tablets for the first time. The feature, which consolidates games from multiple PC storefronts into a single dashboard, launched in select markets on April 30 and will expand to more users over the coming weeks.

Xbox Mode replaces the standard Windows desktop with an Xbox-style interface designed for gamepad navigation. It pulls together installed titles from Steam, Epic Games Store, Battle.net, and the Xbox Game Pass catalog into one unified library. Users can browse, launch, and switch between games without touching a mouse or keyboard, then return to the regular Windows desktop whenever they want.

The feature runs on top of Windows 11 and, when active, suppresses background distractions and presents a streamlined UI modeled on the Xbox console dashboard. Microsoft is marketing it as an optional layer that doesn’t lock users out of the full desktop environment, and switching between the two is seamless.

Xbox Mode originated as the Full Screen Experience, a feature initially exclusive to the Asus ROG Xbox Ally handheld. That version leaked to other handhelds via registry tweaks in September 2025, and Microsoft officially expanded it to all Windows 11 handhelds two months later. The jump to desktops and laptops was confirmed at GTC 2026 in March, alongside the reveal of Project Helix, Microsoft's next-generation Xbox console built on a custom AMD SoC.

The expansion to full-sized PCs puts Xbox Mode in direct competition with Valve's Steam Big Picture mode and, more broadly, with SteamOS itself. Valve's operating system has attracted a following among handheld and living-room PC gamers for its low-overhead, controller-first design. Xbox Mode's advantage is native access to every Windows-compatible game and storefront without the compatibility layers that Linux-based SteamOS requires.

Xbox Mode is also a building block for Project Helix, the next-gen Xbox that Microsoft confirmed will run both console and PC games on a custom AMD SoC, and development kits are expected to ship in 2027. Rolling the same interface across existing Windows 11 hardware gives Microsoft a head start on software maturity before that console arrives.

Xbox Mode is being deployed via Windows Update in a phased rollout. To get access as early as possible, users need to open their settings, navigate to Windows Update, and toggle on "Get the latest updates as soon as they are available." Once the update reaches a given device, Xbox Mode can be launched directly from the PC.

Microsoft didn’t specify which markets are included in the initial wave or provide a timeline for full global availability. The company said it plans to continue evolving the feature based on user feedback.

Google, Amazon, Microsoft, and Meta collectively plan to spend $725 billion on capex in 2026, up 77% from last year's record $410 billion, according to first-quarter earnings compiled by the Financial Times. Google delivered the strongest results, with cloud revenue jumping 63% year over year to $20 billion, while rising memory chip prices pushed spending forecasts higher at both Microsoft and Meta.

"The AI economy is healthy," Brent Thill, an analyst at Jefferies, told the Financial Times, adding that recent revenue growth justified the enormous capital outlays. "The bear thesis is garbage."

Microsoft set its calendar-year 2026 capex at $190 billion, well above the $152 billion average analyst estimate. The company’s CFO, Amy Hood, attributed $25 billion of that figure to rising memory chip and component costs. She told investors that despite the additional spending, Microsoft expects to remain capacity-constrained through at least 2026 as it works to bring GPU, CPU, and storage infrastructure online faster.

Meta increased its full-year projection by $10 billion to a range topping $145 billion. The company cited higher component pricing, particularly for memory, alongside growing competition for land, power, and skilled workers needed to build data centers. Revenue grew 33% to $56.3 billion.

Dec Mullarkey, managing director of SLC Management, told the Financial Times that investors are growing uneasy with Meta's escalating infrastructure costs, questioning whether a historically lean business is becoming far more capital-hungry. “Investors continue to be concerned about how Zuckerberg’s once capital-light money machine may be morphing into a capital-intensive incinerator,” he said.

Alphabet posted an 81% increase in net income to $62.6 billion on revenue of $110 billion. Google Cloud reached $20 billion in quarterly revenue, growing faster than Amazon Web Services ($37.6 billion total, adding $8.3 billion year over year) and Microsoft's Azure-driven cloud segment ($34.7 billion total, adding $7.9 billion).

The company's cloud contract backlog reached $460 billion, roughly double the $240 billion reported at the end of Q4 2025. Google Cloud boss Thomas Kurian credited the company's strategy of building custom AI chips, foundation models, and products in-house for giving it a cost and research advantage over competitors. Alphabet's capex guidance rose by $5 billion to as much as $190 billion, matching Microsoft. Shares climbed 7% after hours, putting Alphabet on track for a record $4.3 trillion market valuation.

CEO Mark Zuckerberg offered no firm schedule for releasing improved AI models to follow the recently launched Muse Spark. Asked about the pace of Meta's AI agent development, Zuckerberg told investors: "There's a lot of agents out there that people are building for different things, but there aren't that many that I would want to give to my mother."

In early 2025, OpenAI announced Stargate, a joint venture with Oracle and SoftBank, which aimed to invest $500 billion in AI data centers in the United States. But after more than a year of challenges and disagreements, it seems that the startup has abandoned the original idea of directly owning infrastructure alongside its two partners. According to the Financial Times, OpenAI now prefers to rely on third-party providers and lease capacity in the long term.

This is a sensible idea for the startup, which is burning through cash and has reportedly missed internal revenue targets in recent months. But it has also caused chaos among its partners and put its reliability into question. According to the report, OpenAI has "in practice... abandoned the joint venture," choosing instead large bilateral deals with Oracle and more. One person involved with Stargate reportedly said the company had "sidelined first-party data centres," while OpenAI itself admitted that Stargate is merely an "umbrella for our compute strategy."

Stargate’s initial goal was to build 20 data centers, with the first project at Abilene, Texas, already operational. However, the three partners reportedly squabbled among themselves for months as they could not agree on who would have ultimate control of the planned data centers. In the end, SoftBank agreed to own and develop the Texas data center, while OpenAI would design and operate it on a long-term lease.

Other Stargate projects located in other areas have also been hit by uncertainties. The UK government signed a deal with OpenAI, among other partners, to build a data center in the UK, but the startup has put it on hold earlier this month. It cited “restrictive regulations” and “high energy costs” as the reason behind the move, but UK AI Minister Kanishka Narayan told the Financial Times that the “only thing that has changed [since] the moment of those commitments…has been the financing environment for OpenAI.”

It has also done the same for another Stargate project in Narvik, Norway, with Microsoft stepping up to take over the lease for the site. OpenAI will then lease compute capacity from Redmond, instead of getting it directly from Nscale, the British company that developed the site and also worked on the canceled UK project.

All these changes have got some partners “feeling let down and misled by OpenAI,” a person familiar with Microsoft’s decision said. Thankfully, the software giant has stepped in on some of the projects that the startup has supposedly abandoned. One source told the publication that money is not unlimited, no matter what Sam Altman might say, while another said that they prefer Microsoft over OpenAI as a tenant, as “they are more creditworthy.”

Even though OpenAI has made a name for itself in AI, the startup has not turned a profit since it was founded in 2015. Many institutions believe in its potential, though, with the firm securing $110 billion in its latest funding round — the biggest amount secured in Silicon Valley history and $10 billion more than what the company initially targeted. Still, some analysts estimate that it could run out of cash by mid-2027 with the massive amounts of money it’s been throwing around to secure more compute.

Anthropic CEO Dario Amodei criticized moves like this, saying that some of his company’s rivals are pushing infrastructure investments too far. However, OpenAI says that it’s ahead of the exponential compute curve, allowing it to have an advantage over everyone else. For example, Anthropic has had to limit access to some features on its various products due to limited resources, and Amodei has had to spend more on securing capacity to satisfy the increasing demand

The biggest difference between startups, like OpenAI and Anthropic, and their more established rivals, like Microsoft, Google, Meta, and Amazon, is cash flow. The startups still rely on external funding to fuel their growth, while the big tech companies have billion-dollar revenue that they can rely on to pour into expensive hardware and infrastructure projects.

Microsoft and OpenAI have once again renegotiated the terms of their deal with one another, but it might be what's best for both of them. OpenAI and Microsoft have announced an end to their exclusive arrangement, and a re-jigging of how they handle model oversight, revenue sharing, and cloud deployments. Microsoft will no longer pay OpenAI for what it makes from Copilot, but OpenAI no longer has to exclusively use Azure servers for ChatGPT, opening it up for further deals with other cloud service providers.

What this means for the ever-nebulous AGI clause that both companies were so keen to retain access to and control over, if and when it materializes, remains to be seen. It's an intriguing move that leaves the immediate future of both companies' AI efforts uncertain, but perhaps it's better than Microsoft's legal department firing all barrels at OpenAI over its recent deal with Amazon.

Where's the ROI?

One of the biggest questions of the AI industry over the past year and a half has been the source of profit. Not the infrastructure investment, or the circular deals and token IOUs, but the real profit. For the investors who pumped tens of billions of dollars into OpenAI, Anthropic, and xAI, and for the shareholders who ballooned Microsoft, Google, and Meta's stock prices off the back of these mega deals and unprecedented investment plans.

Microsoft CEO Satya Nadella hinted at this in January, when he said at the World Economic Forum that AI companies needed to find a clear use for the technology or risk losing the "social permission" to continue the work.

That seems to be more of a pressing issue for Microsoft by April, when it announced that Copilot use on GitHub would move to token-based billing — that is, charging users for the amount of tokens they use, rather than on a per-request basis. No longer would shorter requests with shorter responses cost as much as longer, more in-depth queries. From June, this will result in users paying more when Copilot is verbose in its responses, or when it has to analyze more data before making its suggestions.

Microsoft is already doing that with Azure agents, and it's also set to raise the price of Microsoft 365 with its Copilot integration by several dollars a month for most tiers.

According to internal documents reportedly shared with journalist Ed Zitron, this move came because Microsoft had faced a more-than-doubling of its Copilot-related costs from January this year. He also claims Microsoft will take further steps to tighten controls and increase earnings from individual AI users, including reducing rate limits and forcing users onto different models, which could more than double costs.

Things aren't much better at OpenAI, either. It was projected in January to be on track to run out of money entirely by the end of 2027, and despite announcements of enormous investments in the company, it's projected to burn through tens of billions over the coming years. All while somehow planning to turn a profit by the end of the decade, but to manage that, it would need to earn hundreds of billions of dollars a year. OpenAI's annualized revenue run rate is reportedly sitting at roughly $2 billion per month, or $24 billion a year.

OpenAI also performed several major pivots and navigational shifts in recent months. We learned about its chip manufacturing ambitions in February, it announced it was building a GitHub competitor in March, the company warned that it would shutter the Sora text-to-video generation tool in April, and it bought a podcast for over $100 million that same month.

Even OpenAI's own financial officer has said she doesn't see how OpenAI can afford its own promised infrastructure spending, as it misses key revenue targets in 2026, according to a new WSJ report.

It's very hard to see how any of this takes OpenAI from a heavy-loss-making company to one that's incredibly profitable in just a few years.

Don't drop the bag

OpenAI was under pressure in 2025. To secure the promised investment of billions from Japanese investment firm Softbank, it needed to convert to a for-profit company and settle its disagreements with Microsoft. It managed that just in time, finally securing a long-term partnership agreement with Microsoft in the Fall. The Softbank money came rolling in, and just a few months later, the deal was renegotiated again.

But rejigging the deal may be OpenAI's way of securing the next round of funding — the $50 billion promised investment from Amazon in February, which Microsoft was none-too-pleased about. But in doing so, it's lost one of its limited revenue streams from Microsoft's Copilot earnings, and will still have to pay Microsoft 20% of its own limited earnings.

That Amazon investment could come alongside another $60 billion from Nvidia and SoftBank (though not the $100 billion Jensen originally promised), if all goes to plan. That would also value the company at around $730 billion, making a potential IPO incredibly profitable for Altman and anyone else holding OpenAI shares at the time of a public offering.

But even with OpenAI more than halving its compute ambitions from $1.4 trillion in expenditure to $600 billion by 2030, that's still contingent on increasing its own revenue to $280 billion a year by that same date. As of the time of writing, OpenAI hasn't even managed to earn 10% of that, while having close to a billion active users (though crucially, it also missed that milestone by the end of 2025), and it is losing mindshare to competitors like Anthropic.

Regardless, OpenAI seems keen to push forward with its IPO plans. At this stage, that may be the only real avenue left for it to get anywhere close to its ambitious goals. Even with shifting goalposts, the timeline for its profitability is shrinking rapidly, and it still hasn't made a clear path toward it.

Microsoft is currently facing a lawsuit from the UK Competition Appeals Tribunal (CAT) after it was alleged that the company is charging higher wholesale prices for Windows Server for customers using Amazon AWS, Google Cloud, or Alibaba Cloud. This makes Azure, Microsoft’s cloud services provider, cheaper than the competition as its competitors have to eventually pass on the increased costs to their clients, reports Reuters. Competition lawyer Maria Luisa Stasi filed the case at the Competition Appeal Tribunal in late 2025, representing nearly 60,000 businesses that used Microsoft software on competing cloud services, with her team suggesting that the claim is worth about USD 2.8 billion (or about GBP 2.1 billion).

The company argued that Stasi did not show a concrete way of computing for any alleged losses, so the case should be thrown out. However, the London tribunal certified the case, and it’s now proceeding to trial. Microsoft is planning to appeal the decision and told the publication, “We also dispute the underlying allegations by the class representative, and today’s decision makes no final determination on those claims.”

During a previous hearing, Microsoft said that its strategy of integrating Windows Server with Azure while also licensing it to rivals will help competition. However, the British Competition and Markets Authority (CMA) discovered that this licensing practice is “materially disadvantaging AWS and Google” in mid-2025, with the government body opening another investigation into the company’s licensing practices. Other regulators in the U.S. and Europe are also looking into Microsoft and other cloud computing firms. Some sources said that the Federal Trade Commission (FTC) started scrutinizing claims late last year that the company has put punitive licensing terms in its productivity suite that make it harder for customers to switch to rival platforms from Azure.

This isn’t the only legal trouble that Microsoft faces in the UK. The company is currently appealing a ruling handed down by the same authority, which said that reselling perpetual licenses, including those of Microsoft Office and Windows, is legal and valid. This stemmed from a lawsuit by ValueLicensing, after it argued that Microsoft’s contract, which prohibited reselling of licenses issued before, is against the law. It follows a similar argument in a UsedSoft complaint filed against Redmond more than a decade ago, but Microsoft used a copyright infringement argument this time. It said that Word and other apps contained graphics that are protected by creative work, which the UK tribunal rejected.

After several years of subsequent price rises and management restructuring that led many gamers to believe the Xbox brand was on its way out, Microsoft has pulled off a surprise move. The company announced today in a press release that it would bring the price of Game Pass Ultimate back down from $29.99 to $22.99, while the PC Game Pass goes from $16.49 to $13.99 a month.

It's not all good news, though, as those who subscribed to Game Pass for the sole purpose of playing Call of Duty (CoD) will now have to wait around a year for new titles to appear on the platform. The change does not affect existing CoD releases, and all other day-one game releases will continue.

The now-nullified decision to include CoD in a monthly subscription was widely deemed as particularly gutsy. The game sells tens of millions of copies a year. At $70 a pop for the standalone title, it's possible the company was leaving hundreds of millions, if not billions of dollars, on the table.

Even still, in the broader scheme of things, this development is quite the volte-face for Microsoft, which repeatedly hiked the price of both the consoles and subscriptions over the past couple of years. Those decisions led to wide speculation that the company could be preparing for the end of the Xbox brand, in light of a minority market share versus the PlayStation.

As a quick recap, Microsoft raised the price of the Xbox twice in the 2025 calendar year alone, with the first raise in May and the second in September. The Game Pass subscription had seen a dollar hike in 2024 along with added limitations, and salt was further rubbed on the wound in 2025 with a 50% raise with nary any benefits — a move that led to so many cancellations that the Microsoft website was reportedly having issues processing them.

This Game Pass price drop is the first big commercial move since Asha Sharma took over the division. The choice of executive was a move out of left field, as she was previously managing the Core AI business. Nevertheless, Sharma is reportedly spearheading an effort to revitalize the brand, and bringing down subscription prices to more reasonable prices is a decision that will definitely be appreciated by gamers.

Microsoft really wants users to embrace its Edge browser. Its latest effort involves unveiling a pleasingly rotund $2M prize pot to tempt users over. That figure includes a grand prize of $1M in cash, some alluring Mercedes-Benz automobiles, and “thousands of instant prizes.” Sadly for Microsoft/Edge, it has taken over a month for the media to become aware of this new barnstorming Rewards package with NeoWin flagging it as a surprise “new promotion in Edge” this Thursday.

Head to the rewards.bing.com link at the top of this article, and you will be asked to sign in to join the rewards program. There are T&Cs, privacy, and official rules smallprint links to digest. But basically, you will be agreeing to “receive emails about Microsoft Rewards, which include offers about Microsoft and partner products.” There is no monetary fee for entering the sweepstakes. But you can use Microsoft Rewards points balances to accrue more entries. The unfeasibly large maximum entry limit is 465 entries per person/account/email address/mobile phone number.

Sharing links to the prizes event page can also net you more entries and chances to get something from the prize pot. As this rewards program has been running for a month, we can see multiple folks across the world who have already won this and that. For example, someone in Spain won an Acer Copilot+ PC, an entrant from the U.S. snagged a $50 Xbox Gift Card, and someone from Mexico managed to lasso a ROG Xbox Ally handheld. Is the chance of this kind of prize worth the potential spammy email avalanche? That’s up to you.

The official rules say that the sweepstakes are open to U.S. residents, as well as those in Canada and a multitude of South American and European countries. We see New Zealand, Japan, and South Africa are listed, too. No, we don’t know what happened to Australia.

If you want to convert the $1,000,000 grand prize to your local currency – perhaps you are an optimist – Microsoft has already done the work for you. It is “approximately $1,380,000 CAD / £740,000 GBP / €860,000 EUR / Fr. 800,000 CHF / kr 10,100,000 NOK / $18,000,000 MXN / S/ 3,400,000 PEN / ₡498 000 000 CRC / Q7,000,000 GTQ / $1,730,000 NZD / ¥157,000,000 JPY / Kč 20,800,000 CZK / lei 4,350,000 RON / R 16,500,000 ZAR.” Some unfortunate countries will face Microsoft withholding 30% of the prize value in tax.

Three cars are up for grabs to appeal to the petrolheads among you. The rules suggest that winners will pop to their local Mercedes-Benz dealer, where a budget of $100,000 (or local equivalent) will be all yours to play with. You can’t buy a key fob and get the remainder in cash, though, so canny winners should max out their Merc specs to the last cent.

Installing this month's Windows Server security update has knocked some enterprise domain controllers into continuous reboot cycles, Microsoft confirmed in a release health dashboard entry.

The company says the April 2026 patch, KB5082063, triggers crashes in the Local Security Authority Subsystem Service (LSASS) on non-Global Catalog domain controllers used in Privileged Access Management (PAM) deployments, leaving Active Directory authentication and directory services unavailable on affected servers.

Microsoft's dashboard lists Windows Server 2016, 2019, 2022, 23H2, and 2025 as vulnerable to the fault, with the LSASS crash occurring during the startup sequence, which is what turns the failure into a loop: each automatic reboot re-enters the same faulty authentication codepath rather than recovering into a stable state.

The problem is only affecting managed enterprise environments that run PAM for Active Directory privilege delegation, and Microsoft said personal devices outside IT-managed domains aren’t exposed. The company hasn’t yet published a patch and has instead directed affected administrators to Microsoft Support for Business for mitigation guidance that can be applied if KB5082063 is already deployed.

KB5082063 now has three acknowledged bugs within a week of release, and Microsoft has warned separately that the same update prompts some Windows Server 2025 machines for a BitLocker recovery key after installation. The company is investigating reports that KB5082063 fails to install entirely on a subset of Windows Server 2025 systems.

April security updates have disrupted Windows Server domain controllers for three consecutive years. In March 2024, Microsoft shipped an emergency out-of-band fix after that month's Patch Tuesday caused DC crashes outright. The April 2024 patch cycle then broke NTLM auth across Windows Servers and forced unplanned DC restarts, which Microsoft corrected in a May 2024 rollout.

In June last year, the company released another correction for Active Directory authentication problems introduced by the April 2025 security update. This month's LSASS crash follows the same MO for the third year running: a general Patch release followed by post-deployment failure reports from enterprise admins, and a scramble for mitigation while the fix is prepared.

With KB5082063 still on the release channel and no patch date published, admins have three choices: delay the April update, isolate a test DC to validate patch behavior before wider rollout, or escalate through the Microsoft Support form Business to obtain the mitigation steps the company is providing case-by-case.

Microsoft’s Clippy was put out to pasture a quarter century ago. This hapless, and some would say ‘irritating,’ productivity assistant would no longer be enabled by default in Office, starting April 11, 2001. Nowadays, it is easy to remember Clippy with some fondness through rose-tinted retro spectacles. But, in its era, Clippy’s repetitive catch-all catch phrases such as “It looks like you’re writing a letter” and “Would you like help with that?” would soon erode any tolerance you might have for cute character-based digital assistants.

Clippy (more properly called Clippit) was a digital assistant introduced with Microsoft Office 97. The plan was to bring a friendly agent to the screen to interface with Office help content, as explained by Wikipedia. Several characters were designed to offer this help, with Clippy (Clipit) as the default choice. Among the alternatives were caricatures of Albert Einstein, William Shakespeare, and Rocky the dog, as well as several animated inanimate objects (like the unpopular paperclip).

Some esteemed figures in the computer industry think that the introduction of Clippy might have been a "tragic misunderstanding" of research conducted at Stanford University on breaking barriers in human-machine interaction. Indeed, there must have been something seriously wrong with a ‘helpful’ project like this for it to attract so much ire and ridicule among users and tech commentators.

As per our headline, Clippy was officially retired on April 11, 25 years ago, when Microsoft announced it would be disabled in Office by default. In Office XP, it would still be there as a dormant and optional feature. However, with Microsoft Office 2007, there was no longer any way to summon help from Clippy or his friends.

Rose-tinted retro spectacles

Clippy’s infamy has been sealed with its place in Time magazine’s 50 worst inventions. However, the mists of time have taken the edge off the pain of working with such a useless assistant, as it is now often viewed as being part of an amusing, heart-warming era in computing.

Microsoft has played on this softening of public opinion, or even nostalgia, for Clippy in several marketing campaigns since the animated paperclip and his friends were discarded. Most recently, it resurrected Clippy as an Emoji in Microsoft 365 – after overwhelming popular demand.

Last year, as the wave of new AI assistants began to grate on the public nerves, we also observed some fondness for Clippy being rekindled in a project by software engineer Felix Rieseberg – a locally hosted, LLM-based, AI-enhanced Clippy, complete with Office 97-era-appropriate UI.

Despite the sting of Clippy's clear failure, Microsoft keeps coming back to digital assistants as the future of computing. We had Windows Cortana foisted upon us from 2014 to 2023.

Now we have Copilot everywhere, in every corner of our Windows 11 PCs and Microsoft apps. A recent count indicates that there are at least 80, and probably over 100 Copilot apps…

As optimists, we hope Copilot will be reined in, as far as Windows goes, thanks to Microsoft’s latest stated initiative to focus on OS performance, reliability, and RAM usage. This telegraphed change is also supposed to lead to fewer Copilot interactions.

Microsoft's promises of a better Windows are moving one small step closer to fruition, starting with the Windows Insider Program. In a blog post authored by Microsoft product manager Alec Oot, the company promised a simpler channel structure and more control over which features Insiders get to try.

The channel structure is being simplified down to two primary channels. The previous Beta Channel will go into the more simply named "Beta" branch, while what was previously the Dev Channel will go the "Experimental." These are where you go for first access to the newest features. Though Oot explains that in the Experimental channel, "what you see may change, get delayed, or not ship at all."

If you're in the existing Canary Channel, things will get slightly more complicated, with 29500-series builds going to Experimental (Future Platforms), while 28000-series builds will transition to Experimental (26H1). Future Platforms will be the earliest preview build you can get, and one Oot writes that it is "not aligned to a retail version of Windows."

Features and gradual rollouts

On the Beta channel, there's another big quality of life change for Insiders. Microsoft is stopping gradual feature rollouts. If Microsoft announces a feature and you download the update, you'll get it. This differs from the previous practice of gradual rollouts. While the company says the gradual rollouts are designed to assess how features perform before releasing widely, they acknowledge that it made the program "unpredictable," and it could mean that "you don't get the new features that motivated many of you to join the Insider program to begin with."

For the Experimental channel, there will be flags for new features, so Insiders can enable the ones they want to try and disable those they don't.

Windows Insider for Business will see the same changes as the consumer program, while the Windows Server version will continue unchanged. Release Preview will hang around as an advanced option for those who want to try production builds shortly prior to their general release.

Upgrading in place

Moving between Windows Insider channels or leaving the program has been historically different, with very few points to stop and get off the ride without needing to wipe your PC and clean install Windows.

Microsoft now says it is working on the ability to hop between versions without losing all of your software and settings.

"This will allow, in most cases, Insiders to move between Experimental, Beta, and Release Preview on the same Windows core version, or leave the program without a clean install," Oot writes. "An [in-place upgrade] takes a bit more time than your normal update but migrates your apps, settings, and data in-place."

The Experimental (Future Platforms) build will still require a clean install, as it doesn't line up with any retail production builds of Windows.

Oot writes that these changes are set to begin in "the coming weeks."

Last month, Microsoft promised a slew of features to improve Windows 11, including a more flexible taskbar, a less aggressive Windows Update, improvements with RAM issues, and a better File Explorer. To assess upcoming fixes, Microsoft will need its slew of Insiders. Hopefully, a streamlined program makes it easier for enthusiasts to join the program and leave feedback before changes come to everyone else.

France is accelerating its digital sovereignty plans. In an official press release this week, the country’s DINUM announced its “exit from Windows in favor of workstations running on the Linux operating system.” (machine translation).

The DINUM is an important section of the French state, headed by the Interministerial Directorate for Digital Affairs, so this will mark a key changeover in the machinations of government, eliminating U.S.-based commercial interests from workstation computers. We assume some French flavor of Linux will be adopted to satisfy the stated objective of migrating to sovereign solutions. Joining the DINUM in this mission for digital sovereignty are France’s Directorate General for Enterprises (DGE), the National Cybersecurity Agency of France (ANSSI), and the State Procurement Directorate (DAE).

Moving to Linux is described as one of three “concrete initial steps” that have recently been committed to, to reduce France’s extra-European digital dependencies. The plan is expected to be formalized in the fall. By then, stakeholders should know what “workstations, collaborative tools, antivirus software, artificial intelligence, databases, virtualization, and network equipment” will be needed to move ahead with this digital sovereignty initiative.

On the topic of applications, not just the underlying OS, France recently announced that it had moved 80,000 National Health Insurance Fund employees to open-source alternatives to platforms like Microsoft Teams, Zoom, and Dropbox. These commercial platforms have been put into forced retirement by the new Tchap, Visio, and FranceTransfert services (and others), delivering a set of modern collaborative productivity tools dubbed La Suite.

Last month, the French government also “announced the migration of the health data platform to a trusted solution by the end of 2026,” says the source press release.

We know why – but why?

French Ministers are very keen on reducing reliance on technologies that depend on or are controlled by outside interests. “We must become less reliant on American tools and regain control of our digital destiny,” wrote David Amiel, a Minister of Public Action and Accounts, in a statement pinned to the above-linked PR. “We can no longer accept that our data, our infrastructure, and our strategic decisions depend on solutions whose rules, pricing, evolution, and risks we do not control.” It is interesting to see Amiel single out the U.S. for his statement about how the French state “must break free.”

Anne Le Hénanff, Minister Delegate for Artificial Intelligence and Digital Technology, echoed Amiel’s sentiments by asserting that “Digital sovereignty is not an option, it is a strategic necessity."

One wonders whether the growing cultural rift between the U.S. and its traditional European allies has added momentum to the digital sovereignty movement in France.
The implications for software and services businesses across the Atlantic don’t look great. As a leading member of the EU, France’s decisions and direction can exert a strong influence on others in the bloc. Moreover, if the move to Linux is seen as a success, it could also influence other government departments, and organizations that work closely with the government, and so on, all the way down to individual users.
Perhaps 2026 is set to be l’année de Linux?

The ROG Xbox Ally, one of the first Xbox handheld devices from Microsoft in collaboration with Asus, is now available at a $100 discount on Amazon and Best Buy. Launched at a retail price of $599, you can grab the ROG Ally X for $499, a price which we haven’t seen since January of this year and still matches one of the biggest drops since launch.

The ROG Xbox Ally and the ROG Xbox Ally X are more or less similar to the original ROG Ally and Ally X, with a slightly refreshed design including large Xbox controller-style contoured grips, and updated internals including AMD’s latest-gen Ryzen Z2 series chips optimized for handheld consoles.

• Check out this deal at Amazon

The ROG Xbox Ally is powered by the entry-level Ryzen Z2 A processor, which is the entry point into AMD's Ryzen Z2 lineup with a four-core/eight-thread CPU based on AMD’s Zen 2 architecture, an RDNA 2 GPU with eight cores, boost clock speeds of 3.8 GHz, and a configurable TDP range of 6W to 20W. In terms of memory, you get 16GB of LPDDR5X-6400 along with a 512GB M.2 2280 SSD, and a 60Wh battery.

The display on the ROG Xbox Ally measures 7 inches, offering a 1080p resolution, a 120 Hz refresh rate, 500 nits of brightness, and support for VRR (variable refresh rate) and FreeSync Premium. It is a standard IPS LCD panel, not OLED, but overall, in our testing, we found the display's performance to be fairly good and identical to the original ROG Ally.

The device is powered by Windows 11, but can directly boot into the Xbox Full Screen Experience, which feels significantly better for handhelds than standard Windows. It looks similar to the Xbox app, featuring a home screen with recently played games, along with access to your Game Pass and game library from various platforms like Steam, Epic Games, Battle.net, GOG Galaxy, and Ubisoft Connect.

At $100 off and $499 at Amazon (and Best Buy), the ROG Xbox Ally (see our Ally X review) is now a far more tempting buy than it was at launch. While it may not be the most powerful handheld on the market, it’s more than capable for casual and mid-tier gaming. If you’ve been waiting for a price drop to jump into handheld PC gaming, this deal makes a lot of sense.

If you're looking for more savings, check out our Best PC Hardware deals for a range of products, or dive deeper into our specialized SSD and Storage Deals, Hard Drive Deals, Gaming Monitor Deals, Graphics Card Deals, Gaming Chair, Best Wi-Fi Routers, Best Motherboard, or CPU Deals pages.

An artificial intelligence (AI) aficionado has put together a chart featuring all the Copilot things that Microsoft has released since AI became the next big thing. At the latest count, Ty Bannerman notes that there are 80 different, separately marketed Copilot products and tools. Charting these Copilot things wasn’t a trivial task; even Microsoft doesn’t appear to maintain a definitive list. When I first noticed this story, there were 78 Copilots in Bannerman’s charts, but now it has expanded to 80.

The AI strategy, design, and implementation expert says that the idea of charting the expanse of the Copilot universe came to him when someone asked what Microsoft Copilot is. He knew it meant at least 75 different things, in so many contexts, at the time. “Apps, features, platforms, a keyboard key, an entire category of laptops - and a tool for building more Copilots,” tallied Bannerman in his blog. “All named ‘Copilot’.” His chart contends this is "What happens when you name everything Copilot."

Last week, the AI aficionado charted the number of Copilots as 78. However, since yesterday, I note the number has increased to a nice round 80. Thanks to the power of the internet / social media, Bannerman had learned of the existence of Gaming Copilot and Microsoft Dragon Copilot. The latter of those isn’t designed for residents of Westeros, but an AI clinical assistant.

Copilot says there are ~95 to 120+ Copilots

So, we have a chart of 80 Copilots, and who knows what the final figure may be, and how many more Bannerman can uncover?

Since I’m typing on a laptop with a Copilot key, I prodded it and asked the thing itself. Who better to ask? The answer was that “the ecosystem is well north of 100,” if you include things like every app-embedded Copilot, enterprise, and Azure-adjacent tools, etc. I then asked it to add them all up, and it concluded there were “~95 to 120+ Copilots.”

Is that too many? Well, even on this PC, I was surprised to find two Copilot apps in my system tray a few weeks ago. One pops up the usual chatbot box, the other was actually Copilot 365, which, when clicked, asked me to sign in with my (non-existent) Microsoft 365 credentials before I could use it. It has been eliminated.

The corporation's promise of major improvements to Windows 11 performance, reliability, and fewer Copilot interactions can't come soon enough.

Several delisted Xbox 360 games briefly reappeared on the Xbox Store this week before being pulled again, according to the Better xCloud datamining account, which monitors Microsoft's cloud gaming backend for changes. This follows Xbox Vice President Jason Ronald's commitment at GDC 2026 in March to revive the company's backward compatibility program as part of Xbox's 25th anniversary later this year.

The titles spotted include Aegis Wing, Prince of Persia: The Sands of Time, and Mars: War Logs, all of which had been removed from the store previously. The Prince of Persia title resurfaced with its original release date, along with an apparent placeholder price of $100, and the 2003 shooter Armed and Dangerous also reappeared and vanished shortly before the latest batch. Mars: War Logs was delisted around the same time.

One or two accidental relists might mean nothing, but the pattern across four titles in quick succession has understandably caught attention. The Better xCloud account, run by the developer behind the browser plugin of the same name, first flagged Armed and Dangerous as a possible mistake before noting that subsequent appearances looked intentional.

At GDC 2026 in San Francisco, Ronald told attendees that the game preservation team would be "rolling out new ways to play some of the most iconic games from our past" as part of Xbox's 25th anniversary celebrations. Microsoft discontinued its backward compatibility program in 2021, citing licensing issues and technical limitations that prevented further titles from being added to the catalog.

The program originally launched in 2015 and brought hundreds of original Xbox and Xbox 360 titles to Xbox One and later Xbox Series X|S. At its peak, the catalog included over 600 titles spanning two console generations. Since the hiatus, fan demand for its return has remained high, with the community-run Xbox Game Preservation website tracking which Original Xbox titles players most want to see come back. Top-requested games on the site include Jet Set Radio Future, Sonic Heroes, and The Simpsons: Hit & Run.

All this raises questions about how backward compatibility will work on Project Helix, Microsoft's next-generation console powered by a custom AMD SoC. Microsoft has confirmed that Helix will play both Xbox console and PC games, and Ronald described the machine as delivering an "order of magnitude" leap in ray tracing performance at the same GDC presentation.

Speculation has centered on the possibility that Microsoft's preservation team is working to bring Xbox 360 emulation to Windows PCs, which would keep older titles accessible on both Helix and standard Windows 11 machines, but Microsoft hasn’t confirmed that.

Microsoft is force-updating devices running Windows 11 24H2 to the latest 25H2 update. With support for version 24H2 officially ending on October 13, 2026, the move seems to be a part of the company’s effort to keep all devices updated to the latest version of its operating system, at the same time make the entire update experience more streamlined.

According to Microsoft’s Windows 11 25H2 support page, the automatic rollout specifically targets systems running Home and Pro editions of Windows 11 version 24H2. However, devices that are managed by organizations or IT departments are excluded at the moment. Notably, the rollout will be handled by an “intelligent” update system that leverages machine learning to determine when a device is ready to receive the update.

Curiously, there seems to be a lack of transparency around how Microsoft’s machine learning system decides when a device is ready to receive the automatic update. The company has not shared any specifics about the criteria or any data points that are being used, which does raise some questions, especially for users who prefer greater control, especially at the system-level.

As this is a forced update, users will not have an option to completely opt out. There is, however, limited control over when the update is installed, as Microsoft will let users postpone for a specific period of time. For those who prefer taking matters into their own hands, the update can also be installed manually by heading to Settings > Windows Update and clicking on “Check for updates,” provided the device meets the eligibility requirements.

Since we are on the subject, Microsoft pushed an emergency update for Windows 11 earlier this week following a faulty preview update that failed to install on a large number of systems. The original update (KB5079391) was released in late March, which reportedly triggered widespread installation issues with error code 0x80073712, which typically indicates missing or corrupted files. Microsoft acknowledged the issue and has since pulled the broken update and replaced it with a new out-of-band patch (KB5086672). This updated release not only resolves the installation problems but also includes all the improvements and features originally intended for the March update.

A former president of Microsoft’s Windows Division has been reminiscing about the lean and efficient coding regime at Microsoft in the 1980s. Steven Sinofsky surprised some commenters, who were talking about modern software’s RAM and resource use, by recalling that from 1980 to 1990 “every Microsoft eng got a stop watch,” adding that “Extras were in the supply room.” Stopwatches were used for “everything,” Sinofsky went on to explain. “Scroll speed. Boot. Exit. Save. Compilation. Print.”

Core products of the ‘stopwatch era’ would be MS‑DOS, Windows, Word, Excel, and Office – as well as programming languages and tools. Windows work would involve versions one through three, but of course, this period predates Windows 95; the clue is in the name. Sinofsky indicates that the same resrouce efficieincy based ethic continued to at least the year 2000, though. “From 1980-2000 half of software engineering was managing resource (clock time, disk, and RAM) usage,” he said on social media.

Do people prefer ‘whizzy spinning’ things to raw speed?

However, the ex-president of Windows told of one retrograde action implemented in software purposefully. Despite his stopwatch indicating otherwise, user feedback the dev team received was that the compile speed under Windows for VC++ 1.0 was slower than prior releases. Implementing a “whizzy spinning line counter made of random numbers… slowed the compile speed down a few pct points but perception improved,” noted Sinofsky. Moreover, despite not liking reworking purely for perception, and actually slowing raw performance, he reluctantly kept the whizz in.

Interestingly, another well-known Microsoft / Windows veteran, Dave W. Plummer, responded to say that he was denied a free stopwatch in 1993. Actually, that is outside the freebie window, as told by Sinosfsky. Microsoft told Plummer that a stopwatch would be “too expensive,” he recalls. Humorously, Plummer says that “While I clearly resent it enough to bring it up 30+ years later, it went a long way toward setting the fiscal accountability I brought to the career.”

Microsoft’s new performance pledge

Sinofsky’s tale comes at an interesting point for Microsoft, particularly its Windows OS, which has been under heavy criticism for losing focus. Specifically, there’s a growing wave of resentment regarding the OS’s poor core performance, general resource hungriness, and devs throwing too much AI in the mix.

A couple of weeks ago, Microsoft’s managers finally decided to face up to this reality and penned a surprisingly detailed blog post, promising that the situation would change over the course of this year. It has now pledged to implement performance, overhead, and reliability improvements across a swathe of core services like Explorer and Windows Update. It will also improve resource use and be more purposeful about where Copilot integrates.

Microsoft’s signaling regarding its newfound efficiency thrust is still fresh, so we can only wait and see if any or many of these improvements materialize. But we’d like to know if, as part of the plans, devs will be given free stopwatches.

A retro computing connoisseur has installed and booted Microsoft Windows 3.1X on a Ryzen 9 9900X and RTX 5060 Ti PC system. That’s a 1992 OS working on a bare-metal 2024 Zen5 CPU and 2025 Blackwell GPU. The full story contains a few nuances, but basically, a system and OS separated by over 30 years of huge advances kind of play nicely together.

In the video by Omores, above, you can see we start by inspecting a Spanish-language Windows 3.1X backup floppy disk set, which the TechTuber had access to. But there’s some important background to understand, before the first 3.5-inch installer disk starts ticking away in its drive.

A key part of this system, not yet mentioned, is its motherboard. This Asus motherboard’s ‘classic BIOS’ functionality doesn’t get in the way of users tinkering with old OSes like Windows 3.1X when the built-in Compatibility Support Module (CSM) is enabled. Moreover, we noticed Omores initially prepared the system using a Windows 95 boot floppy to create the bootable DOS FAT16 partition necessary for setup.

With that done, the retro enthusiast began the Win3.1X install from his USB-attached floppy. There was no problem using this drive, as it was recognized as Drive A: by the installer, and the 1992 media hadn’t suffered from any kind of deterioration, even hidden bit rot.

The first hurdle shows up after the transition from the DOS prompt to Windows 3.1X startup, as the GUI system crashes straight away. It is explained that this is because there is a clash between the OS’s Enhanced Mode and Omores’ modern hardware.

There is an easy workaround, though, as Win 3.1X could be run in Standard Mode. Intended for pre-i386 systems, Standard Mode is useful for this project due to its greater compatibility. A mode switch was all that was needed to get Win 3.1X up and running on this modern system.

Poking around the freshly booted Win 3.1X UI operating in a rather low resolution, Omores commented that the graphics were a bit “glitchy,” but there are supplementary patches and drivers that can improve it.

Adding the graphics driver VBESVGA from PluMGMK on GitHub made a big difference. The UI was scaled up to the display’s native 1920 x 1080 pixels properly. Moreover, the RTX 5060 Ti graphics card now worked without any irksome issues. The tinkerer had used this driver with previous projects, but sounds surprised by how well the driver has matured. It was previously “picky with Nvidia cards” and slightly glitchy, he comments. The driver has seen 44 releases, observes Omores, but it remains in beta.

With graphics fixed, the TechTuber’s attention switched to trying to get Enhanced Mode working for benefits such as virtual memory and improved multitasking. Omores’ chosen sound card also required Enhanced Mode.

So AHCIFIX.386 (from the same GitHub source as VBESVGA) was also installed. Installation was a simple file copy plus the adding of a line to System.ini. With that done, Omores fits his Ensoniq ES1370 audio PCI card. Though other cards he’s tried have Windows 3.1 drivers, this is the only one the TechTuber knows that works on modern hardware with original drivers and MIDI support. Please note that other brand cards using the same chip aren’t compatible, in the TechTuber’s experience.

If you are interested in following in these retro footsteps, the video description includes a link to a Windows 3.1 update script, which will help you go from floppies to a fully working Enhanced Mode system running on bare metal.

Virtually all hyperscale cloud service providers (CSPs), as well as some of the leading developers of AI accelerators nowadays, have their own custom-silicon programs that are focused not only on developing AI accelerators, but also on custom general-purpose CPUs usually based on the Arm instruction set architecture (ISA). Over the next several years proliferation of custom CPUs based on the Arm ISA inside AI servers will increase to 90%, leaving x86 and Arm around 10%, according to Counterpoint Research.

x86 processors from AMD and Intel have long dominated general-purpose servers, which is why most of the AI servers initially relied on Opteron and Xeon processors. However, Arm-based custom CPUs that are tailored for specific data-intensive AI workloads are more cost and power-efficient. Furthermore, given the fact that AI workloads are emerging workloads, backward compatibility with x86 is not vital. To that end, AWS, Google, and Microsoft have developed their own proprietary Arm-based processors for their own workloads, whereas Meta is the alpha customer for Arm's own AGI processor.

As a result, adoption is unfolding across multiple hyperscalers in parallel. AWS is expanding the role of its Graviton processors across Trainium-based systems, while still retaining x86 in some configurations for compatibility reasons; Google's next-generation TPU infrastructure relies on its Axion Arm CPU; while Microsoft has paired its Azure Cobalt Arm CPU with its Maia accelerators from the beginning to build a vertically integrated AI infrastructure. Meta is also set to begin deploying Arm's own AGI CPUs shortly.

"The transition from x86 to Arm in AI servers is not a single switch," said Neil Shah, vice president of research at Counterpoint Research. "It has played out generation by generation, configuration by configuration. Hyperscalers are making deliberate choices based on their specific deployment needs, writing compatible and interoperable software, and the economics are very encouraging. The transition is expected to accelerate meaningfully in the second half of 2026, driven by the broad deployment of in-house Arm CPUs alongside next-generation ASIC platforms across major hyperscalers."

Nowadays, the majority of CPUs powering AI servers are still x86, but this is going to change shortly, and by 2030, 90% of AI servers that use custom processors will rely on Arm, leaving only 10% for x86 and RISC-V. It should be noted that loads of AI servers will continue to rely on off-the-shelf EPYC and Xeon processors from traditional suppliers, though broad adoption of Arm by hyperscalers for their custom silicon programs should be a signal for AMD and Intel to make their custom CPU programs more appealing to customers.

"Our analysis projects Arm-based CPUs will account for at least 90% of host CPU deployments in custom AI ASIC servers by 2029, up from around 25% in 2025, a structural shift driven by the accelerating rollout of in-house Arm CPU programs across major hyperscalers," Shah added.

AMD builds its own vertically integrated AI platforms featuring x86 EPYC processors, Instinct MI-series AI accelerators, Pensando DPUs, and Pensando NICs, so it is reasonable to assume that these CPUs are tailored for AI workloads. Meanwhile, Intel is developing custom Xeon processors for Nvidia's next-generation AI platforms, which suggests that these processors will also be optimized primarily for AI workloads. All in all, while Arm will get significantly bigger in the AI server realms over the next four to five years, x86 will continue to command a sizeable share of this market.

The trade-war between the U.S. and China has forced server makers out of the People's Republic, greatly reducing reliance of American companies on producers from Tianxia. However, China remains the world's largest producer of electrical equipment that is required to build power infrastructure inside and outside of AI data centers. To that end, shortages of power delivery equipment, including devices from China and other countries, are slowing project timelines, Bloomberg reports.

Despite the unprecedented level of investment in AI infrastructure — Alphabet, Amazon, Meta, and Microsoft are expected to spend more than $650 billion in 2026 to expand AI capacity — close to half of the planned U.S. data center builds this year are projected to be delayed or canceled, according to Bloomberg. One major reason behind these setbacks is the availability of key electrical components — such as transformers, switchgear, and batteries — that are used both at data center sites and outside of them, as AI companies must expand grid infrastructure to supply enough power to their data centers. Meanwhile, grid infrastructure is also stressed by electric vehicles and electrified heating systems.

Approximately 12 gigawatts (12 GW) of data center capacity is expected to come online in the U.S. in 2026, according to data by market intelligence firm Sightline Climate cited by Bloomberg. Yet only about one-third of that capacity is currently under active construction because of various constraints.

Electrical infrastructure represents less than 10% of total data center cost, but it is as vital as compute hardware. A delay in any single element of the power chain can halt the entire project, which makes transformers, switchgear, and similar devices critical items despite their relatively small share of CapEx.

Due to high demand, lead times for high-power transformers have expanded dramatically in the U.S.: delivery typically took 24 to 30 months before 2020, but waiting periods can stretch to as long as five years today, according to Sightline Climate cited by Bloomberg. For AI data centers, this is a catastrophe as their deployment cycles are under 18 months.

To address shortages, companies are turning to global markets. As a result, Canada, Mexico, and South Korea became the biggest suppliers of high-power transformers for AI data centers to AI data centers. At the same time, imports of high-power transformers from China surged from fewer than 1,500 units in 2022 to more than 8,000 units in 2025 through October, according to Wood Mackenzie data cited by Bloomberg.

The volatility of exports from China does not end with transformers, as the PRC accounts for over 40% of U.S. battery imports, while its share in certain transformer and switchgear categories remains near 30%, according to Bloomberg.

Without resolving constraints in transformers, switchgear, and batteries, even trillions of dollars in AI investment may not translate into actual AI capacity, as deployments will depend on power infrastructure availability, not capital or compute hardware constraints.

Despite a decade of reshoring initiatives, U.S. manufacturing capacity for electrical equipment remains insufficient, which means that AI companies continue to rely on imports even amid tariffs and national security concerns. Meanwhile, tensions between China and the U.S. threaten to further disrupt supply chains, which will raise costs and could delay deployments of advanced AI data centers.

Space watchers enthralled by the live stream from NASA’s Artemis II Orion spacecraft have noticed that even astronauts can have trouble with Microsoft software. BlueSkyer Niki Grayson clipped an amusing segment of the live stream, where a puzzled astronaut asks for support from Mission Control because they “have two Microsoft Outlooks, and neither one of those are working.”

right now the astronauts are calling houston because the computer on the spaceship is running two instances of microsoft outlook and they can't figure out why. nasa is about to remote into the computer

— @nikigrayson.com (@nikigrayson.com.bsky.social) 2026-04-02T19:03:37.132Z

Grayson was agog at NASA inflicting Outlook on astronauts. “I'm so sorry we've sent these souls to the moon and they're using Outlook?” they quipped.

The clipped NASA Artemis II stream shared above is currently still live, and you can watch it in full here. As it is live, there is no transcript provided on the video page. So I asked Google's Gemini to find the portion of the livestream where Outlook bugs were discussed.

Google confirmed the quote from Grayson’s clip. It credited Commander Reid Wiseman talking to Mission Control in Houston at this time. “I also see that I have two Microsoft Outlooks, and neither one of those are working if you want to remote in,” said Wiseman at around 13 and a quarter hours into the livestream. Houston agreed to remote in to take a look at the issue.

About an hour later, the astronauts received the welcome news that Outlook was back online. However, it would appear offline... Nice piece of software. “For Outlook, we were able to get it open. It will show 'offline,' which is expected,” said the Capsule Communicator at Mission Control, at around 14 hours 20 minutes into the stream.

Microsoft Outlook anomaly in space

To some readers, even choosing Outlook as a part of a spacecraft’s communications portfolio would seem to be an anomaly. However, it is a standard part of the "Commercial Off-The-Shelf" (COTS) software astronauts use for their day-to-day operations.

To be clear, the spacecraft and primary flight systems will run on specialized radiation-hardened hardware and rigorously maintained software. COTS just complements this with a friendly layer, like Windows and Outlook, so astronauts can check schedules, indulge in personal communications, and so on, in a familiar way.

Toilet troubles in space

While skipping through the live stream to locate the Outlook conversations, I also heard a discussion between Artemis II Orion and Mission Control about the spacecraft's toilets.

Reports suggest that a blinking fault light on the toilet signaled that a mechanical failure occurred about two hours into the mission. Specifically, we understand that a urine extraction fan jammed.

The fan’s purpose is to pull the urine away into a collection container, avoiding urine microgravity issues. Thankfully, one of the astronauts managed to clear the jam and get the fan spinning. NASA has confirmed the toilet is back online, although we’d like to know what brand of fans the space agency uses…

After rolling out an optional non-security update for Windows 11 last week, Microsoft was forced to pull it due to widespread installation issues. The cumulative update KB5079391 included several quality improvements; however, users reported that it failed to install, showing error code 0x80073712. To replace the faulty preview update, the company has now issued an out-of-band KB5086672 emergency update for affected Windows 11 25H2 and 24H2 systems.

According to Microsoft, the latest update (KB5086672) for Windows 11 “supersedes all previous updates and includes all protections and improvements from the March 2026 Windows security and non-security preview updates, as well as this installation fix.” It is available for devices running Windows 11, including those that have already installed KB5079473 or a later update. Users can also manually download the new update from the Microsoft Update Catalog.

Some key features of the optional KB5079391 update (which should now be available with the latest KB5086672 fix) include enhanced Narrator capabilities with improved image descriptions and Copilot integration. It also brings a refreshed design for account-related dialog boxes that align with Windows 11’s modern look and dark mode, as well as enhancements to File Explorer with reliable file unblocking and support for voice typing during file renaming. There are several display-related updates too, such as support for monitors with refresh rates going beyond 1000 Hz, improved auto-rotation and HDR reliability, and improved power efficiency for USB 4-connected monitors during sleep.

Microsoft has faced repeated criticism over problematic Windows 11 updates in the past, with the company promising to make changes and improve the OS. Earlier this year, the January security update KB5074109 caused widespread issues for gamers, particularly those using Nvidia GPUs. With reports of frame rate drops, visual artifacts, and instability, Nvidia itself advised users to uninstall the update as a temporary fix.

The same update also introduced a more serious issue for some users, with reports of systems failing to boot altogether. According to an AskWoody forum post, some devices encountered an “UNMOUNTABLE_BOOT_VOLUME” error after installing the security update. The affected devices ended up with a message that said “Your device ran into a problem and needs a restart. You can restart.” Additionally, some PCs refused to shut down or hibernate, and another bug resulted in Cloud-based apps, like Outlook, OneDrive, and Dropbox, not working.

Iran's Islamic Revolutionary Guard Corps has issued a direct strike threat to a slew of U.S. tech companies, including GPU giant Nvidia, Microsoft, Apple, Google, Meta, IBM, Cisco, and Tesla, just days after the regime identified the companies as 'legitimate targets.' As reported by CBS News, the IRGC issued an updated and more direct threat via Telegram on Tuesday.

Per the report, the group claimed that it would begin targeting some 18 U.S. and finance companies, specifically their Middle Eastern presences. As noted, the IRGC has already threatened these companies; however, Tuesday's statement represents a marked escalation in rhetorical threat.

The IRGC reportedly stated that the U.S. has "ignored our repeated warnings about the need to stop terrorist operations, and today, a number of Iranian citizens were martyred in your and your Israeli allies' terrorist attacks; Since the main element in designing and tracking terror targets are American ICT and AI companies, in response to this terrorist operation, from now on the main institutions effective in terrorist operations will be our legitimate targets."

Strikingly, the IRGC warned employees of the named institutions, which also include J.P. Morgan, to "leave their workplaces immediately to save their lives." Residents around these terrorist companies in all countries in the region should also leave their places within a radius of one kilometer and go to a safe place," Iran's armed forces stated. WION further reports the statement, which said: "These companies should expect destruction of their facilities in response to each act of terror in Iran." According to that outlet, strikes could begin as soon as 8 pm Tehran time on April 1.

As noted in our previous coverage, companies like Nvidia and Intel maintain significant Middle Eastern presences. 13% of Nvidia's global workforce resides in Israel, where the company has its second-largest R&D center beyond U.S. shores. Similarly, Intel employs some 9,355 people in Israel.

Beyond these specific threats of military force against U.S. tech institutions, the Iran conflict continues to have widespread ramifications in the tech industry. AWS data centers in Bahrain and the UAE have been struck by drones, and significant stress on the global Helium supply could have devastating consequences for chipmaking.

Microsoft and Nvidia have announced an AI-powered collaboration to accelerate the development and deployment of nuclear power plants that will power AI data centers in turn.

The partnership, described in a Microsoft blog post, combines generative AI, digital twin simulation, and Nvidia's Omniverse platform to streamline the nuclear lifecycle from permitting through operations. The effort targets what Microsoft's blog calls an infrastructure bottleneck: expensive, years-long permitting processes, fragmented engineering data, and manual regulatory review that delay new nuclear plant construction.

The companies say their collaboration will span four phases of nuclear development. In design and engineering, digital twins and high-fidelity simulations allow engineers to reuse proven design patterns and model the downstream effects of changes before construction begins. For licensing and permitting, generative AI handles document drafting and gap analysis across the tens of thousands of pages typically required for regulatory submissions.

Construction gets 4D and 5D simulation, adding time scheduling and cost tracking to standard 3D spatial models. Much as Nvidia is doing to optimize its next-generation data center designs before a single shovel of dirt is moved, the idea is to virtually build a nuclear power plant before breaking ground, tracking physical progress against the digital plan, and catching potential schedule collisions early. In operations, AI-powered sensors and digital twins provide anomaly detection and predictive maintenance.

The technology stack powering this effort includes Nvidia's Omniverse and AI Enterprise platforms and Earth 2, PhysicsNeMo, Isaac Sim, and Metropolis models alongside Microsoft's Generative AI for Permitting Solution Accelerator and Planetary Computer, all running on Azure.

The idea of letting generative AI anywhere near safety-critical nuclear infrastructure might give the average reader pause, but it's already happening in the real world. Aalo Atomics, an Austin-based startup building modular nuclear reactors for data centers, has said that it reduced its permitting process workload by 92% using Microsoft's Generative AI for Permitting solution, saving an estimated $80 million annually.

"Two things matter most: enterprise-scale complexity and mission-critical reliability," Yasir Arafat, chief technology officer at Aalo, said in the blog post. Aalo is currently building its Aalo-X experimental reactor at Idaho National Laboratory, with a target of achieving criticality by mid-2026.

Two additional companies, Everstar and Atomic Canyon, are also building on the collaboration. Everstar, an Nvidia Inception startup, is bringing domain-specific AI for nuclear to Azure to manage project workflows and governed data pipelines, while Atomic Canyon's Neutron platform is now available in the Microsoft Marketplace, giving nuclear developers access to these capabilities through standard enterprise procurement.

Given that the time span of new reactor construction stretches many years in the United States (fourteen years in the case of Southern Company's Vogtle Unit 3, for just one example), there's ample room for acceleration of the construction of those plants. Whether the growth of AI data center power demand will be sustained long enough to see Nvidia and Microsoft's efforts bear fruit will remain to be seen.

In early February, reports of Samsung laptops, Galaxy Book4 devices in particular, affected by a weird storage issue started to pop up. Users were seeing error messages on their laptops saying "C:\ is not accessible," locking them out of their system's main drive. At first, this felt like a Windows Update problem since the timing coincidentally aligned with one, but deeper investigation revealed otherwise.

Microsoft and Samsung both came to the conclusion that the Galaxy Connect app that comes preinstalled in these devices was the culprit. The app is used to share or mirror your display to Samsung Galaxy phones, but apparently it interacted with Windows in a way that forced the OS to revoke permissions in the background. The exact details of what went wrong weren't disclosed.

But we do know that it would become impossible to access the drive once you faced the issue. You'd also be prevented from opening Office apps, system tools, web browsers, Quick Assist, and more that was stored on the C: drive. Administrative tasks or any other specific user operations might be affected, too, and users weren't able to uninstall updates or collect logs due to permission failures.

Around the same time, the February 2026 security update for Windows 11 had come out, leading some to believe it must've broken something, but that's not the case. Reports of this issue actually began emerging before the patch rolled out. Since the problem was discovered, Microsoft already logged it as a known issue on its website around ten days ago, and by March 16, it was marked as "externally resolved."

Microsoft has published a full recovery article for affected users that includes detailed steps to gain back control of your C: drive. To ensure something like this doesn't happen again, the company also pulled the Galaxy Connect app off the Microsoft Store and Samsung, and in the meantime, replaced it with an older version that's not broken. So, at the moment, only those already affected need to take action.

Microsoft has blocked the registry trick that allowed Windows 11 users to enable native NVMe support on their PCs, according to members of the My Digital Life forum, who first noticed the change in recent Windows 11 Insider builds.

The trick, which ported a Windows Server 2025 feature to consumer PCs running Windows 11 24H2 and 25H2, had delivered up to 85% higher random write performance in earlier benchmarks. Unfortunately, the four FeatureManagement registry overrides that previously activated the native NVMe stack no longer function.

The native NVMe driver (nvmedisk.sys) replaces the legacy storage path that has routed NVMe commands through a SCSI translation layer since before NVMe SSDs existed. Microsoft originally shipped the driver in Windows Server 2025 last December, claiming up to 80% higher IOPS and 45% lower CPU utilization under high I/O loads. The driver binary was already present in Windows 11 but disabled by default.

Within days of the Server 2025 announcement, enthusiasts discovered that toggling specific registry keys forced Windows 11 to load the native driver. Benchmarks varied by drive and CPU, but gains in random I/O were consistent. AS SSD testing by Neowin also showed substantial write speed improvements, and StorageReview's server-side FIO benchmarks measured up to 64.89% faster 4K random reads.

The registry trick came with caveats, though. Third-party SSD management tools like Samsung Magician and Western Digital Dashboard were not compatible with the new driver, and BitLocker could trigger recovery prompts after the driver swap.

While the registry method is dead, users can still enable native NVMe through ViVeTool, according to Deskmodder, a third-party utility that toggles hidden Windows features. The relevant feature IDs are 60786016 and 48433719. This does require an elevated command prompt, and a reboot is still necessary for the change to take effect. The same compatibility risks naturally apply, and users running BitLocker should suspend protection before attempting the change.

It’s not yet known when native NVMe support will be rolled out to Windows 11 25H2 and 26H2 users.

OpenAI keeps cutting deals left and right, one of the latest ones being a massive partnership with Amazon that ought to see a total of $188 billion circle between both companies. Sam Altman may have cut that one a little too close, according to Microsoft, which is reportedly considering releasing the lawyers over an API exclusivity clause.

Sources from the Financial Times (FT) say the key item in this discussion is OpenAI's Frontier multi-agent platform targeted at large enterprises. Broadly speaking, Frontier offers to make it easy for large enterprises to effectively use AI by wiring up multiple agents ("workers") with shared memory and business content.

Microsoft is apparently taking umbrage with the situation, despite its position in the partnership having been repeatedly revised. Redmond was originally OpenAI's sole cloud services provider, but eventually changed to having the right of first refusal over said services, and was further weakened in October 2025.

The PR about that latest agreement states that "API products developed with third parties will be exclusive to Azure. Non-API products may be served on any cloud provider." Under that logic, OpenAI has the freedom to develop and implement new products, but if they offer them as APIs, they have to go through Azure.

Redmond believes that OpenAI's offering access to Frontier via Amazon Web Services (AWS)'s Bedrock platform would be in breach of the agreement. Getting even more technical, the dispute may well come down to the definition of a "stateless" versus "stateful" when applied to AI models.

Even though it appears to remember your information, a standard chatbot is actually stateless — adding a new question requires the bot to re-process the entire conversation again. A storage and orchestration layer to facilitate something like Frontier is arguably a "stateful" implementation, more specifically a "Stateful Runtime Environment."

According to FT's sources, Microsoft thinks that running Frontier on AWS instead of Azure would breach either the spirit or the letter of the contract. This is illustrated by a report that Amazon is pointedly instructing its staff to never say that SRE "enables access" or "calls on" ChatGPT as a backend, instead preferring vaguer terms like "powered by," "enabled by," or "integrates with."

The whole stateless/stateful discussion has reportedly been a hot topic among lawyers from both camps, though FT states that a Microsoft employee referring to the situation isn't mincing words, saying that "we know our contract," and that "we will sue them if they breach it. If Amazon and OpenAI want to take a bet on the creativity of their contractual lawyers, I would back us, not them."

Predictably, OpenAI's position is the opposite, as the firm seemingly believes the Amazon deal is compatible with the Microsoft agreement. FT further reports that Amazon and OpenAI are building an unspecified system meant to work around the contract.

Nevertheless, FT points out that this latest development may cast a pall over OpenAI's upcoming IPO by placing doubts in prospective stockholders' hearts. That would be a nightmare scenario for the company, as the magnitude of its ongoing investments means that the flow of money cannot stop.