Grand Theft Auto VI, or as its friends call it, GTA 6, will be a console-only game when it goes on sale on November 19. But while Rockstar Games has yet to confirm when PC gamers will be able to get in on the action, a new GamesBeat report claims that it will be within the first three months of 2027.

With GTA 6 launching on Xbox Series X|S and PS5 in around a month, PC gamers have been left wondering if they should consider picking up the console version — and even buying a whole new console to play it. But GamesBeat reports that might not be necessary, with a Q1 2027 release potentially sooner than a lot of gamers had worried may be the case.

Those gamers had plenty of reasons to be worried that a longer wait could be in the cards, too. GTA V was released on consoles around a year and a half before the PC version. Console gamers were able to put the game through its paces in September 2013, with PC owners waiting until April of 2015.

While far from official, the news comes from industry sources "familiar with the studio's plans," although they were given anonymity for obvious reasons.

It's perhaps no surprise that Rockstar Games is keen to open GTA 6 up to as many potential buyers as possible. It's thought to have cost upwards of $2 billion to create, and making that money back is a lot easier when you add PC gamers to your list of customers.

Rockstar Games will also likely want to get its money-making online version of GTA 6 into the hands of players as soon as possible, too. It won't be ready at launch, but is expected to debut in 2027.

While GTA games have historically been popular among console gamers, there are reasons to choose the PC version if it's available to you. The console version of GTA 6 is expected to run at just 30 FPS at launch, for example.

GTA 6's development hasn't been an easy one. The game itself is thought to be in the hands of "Cyberleek," someone who has already shared clips of the game and has threatened to leak the entire game if their demands are not met. Those demands include their memecoin reaching a $30 million valuation, perhaps hinting at their true motivation.

When Framework introduced the Laptop 12 early last year, it offered an affordable, repairable, and relatively capable laptop, especially aimed at students. Between a 2-in-1 convertible design, a touchscreen with an optional stylus, the slim frame, and a $699 starting price, it was an attractive option. The updated Framework Laptop 12 targets that same group, though it’s entering a very different market, with some of the biggest brands gunning to become frontrunners for the best college laptops. Framework still makes one of the best laptops on the market with the Laptop 13 Pro, but the entry-level market is a different beast, especially today.

Apple’s MacBook Neo has prompted a wave of more affordable Windows laptops, with Intel’s Wildcat Lake taking center stage in devices like Dell’s refreshed XPS 13. The Framework Laptop 12 provides competitive performance with these devices, though at a higher price point and with less premium amenities.

The 1080p, 60Hz display is a reminder that the otherwise-premium-feeling Laptop 12 is a budget device, and although the Laptop 12 starts at just $549 without memory or storage, it ends up around $200 to $300 more expensive than the competition when fully configured. The laptop begs a question: how much are you willing to pay for repairability?

Design

Like Framework’s previous Laptop 12 with 13th-Gen Intel CPUs, the updated version with Wildcat Lake comes in a variety of colors: Black, Gray, Lavender, Bubblegum, and Sage. Our review unit, as you can see, is the Lavender variation. At the time of writing, you need to purchase the DIY version to choose your color; the prebuilt version is currently only available in Sage.

Unlike Framework’s more expensive Laptop 13 Pro, you don’t have the option to customize the color of the bezels, and only Gray and Lavender keyboard options are available now (though, presumably, Framework will expand these options). USB-A and USB-C modules come in a wide array of colors, as well, though other expansion modules are limited to a standard silver color. Framework also offers an optional $59 stylus, matching the color options available for the Laptop 12.

The Framework Laptop 12 is a highly portable device, though perhaps not as thin and light as you’d expect out of a 12-inch laptop. It's 0.72 inches thick and clocks in at 2.8 pounds, which is thin enough and light enough, though not on the level of its enclosed competitors. The MacBook Neo weighs about the same at 2.7 pounds, but it’s covered in aluminum and it’s 0.5 inches thick. The XPS 13 with Wildcat Lake is much lighter at 2.2 pounds, thinner at 0.5 inches, and also finished with aluminum.

Considering the bulk of modularity, the fact that Framework managed to get the weight and thickness of the Laptop 12 close to closed-door competitors is remarkable. However, the fact remains that you’re often paying a premium with the Framework Laptop 12 compared to the Neo and XPS 13 and, in both cases, getting a laptop that feels less like a premium ultrabook out of the box.

Although the Framework Laptop 12 isn’t finished in aluminum, it still has a metal structure. On top is plastic, which is then coated with thermoplastic polyurethane to absorb impacts. That leads to a plastic feeling externally, though with a smooth, slightly grippy surface that feels good in the hands.

Framework offers an optional backlight on the keyboard (our review unit didn’t have one), as well as four module slots for expansion ports. The back two support Thunderbolt 4 and DisplayPort Alt mode, and all four support USB 3.2 Gen 2 speeds and USB-PD. A 3.5mm headphone jack is standard on the Framework Laptop 12, regardless of the additional modules you choose.

Specifications

Productivity Performance

This isn’t our first outing with Intel’s Wildcat Lake, so we went into this review with a good idea about what to expect from the Framework Laptop 12’s performance. Our test machine came with the highest-end chip Framework offers in this laptop, which is the Core 7 350. It’s a 6-core / 6-thread CPU with a maximum turbo clock of 4.8 GHz, and it can operate between 15W and 35W.

If you’re unfamiliar, Wildcat Lake is the younger, weaker sibling of Panther Lake. It uses Intel’s cutting-edge 18A node but with several cut corners. For starters, the 350 comes with just two faster P-cores (the remaining four are an LPE cluster). It also comes with just 6MB of last-level cache, half of what you get with Panther Lake.

The cores matter less here than the memory, however. Wildcat Lake exclusively uses single-channel DDR5 or LPDDR5X, regardless of capacity (support goes up to 64GB). In practice, that often means you need to overbudget your capacity, at least compared to something like the MacBook Neo with unified memory. Performance drops at 8GB with Wildcat Lake (see our Dell XPS 13 review).

The Core 7 350 comes in behind in single- and multi-core performance in Geekbench 6 compared to the A18 in the MacBook Neo (though multi-core to a much lesser extent). Compared to the 6-core Core 5 320 in the XPS 13, the Framework Laptop 12 is in lockstep with multi-core speed, and just shy of 5% ahead in single-core speed.

Compared to full-fat Panther Lake in the Framework 13 Pro, Wildcat Lake actually looks better than expected. The 13 Pro here is for context, not as a true comparison point; it costs a few thousand dollars. What’s interesting in Geekbench is how the X7 358H in the Framework 13 Pro scales, relative to the Core 7 350.

The X7 358H is a 16-core chip with a 4.8 GHz boost and access to up to 80W of total power (though much of that is allocated to the 12-Xe3-core GPU). Despite more than doubling total core count, and offering a doubling of P-cores, we’re not seeing twice the performance. And, even with access to less power, the Core 7 350 is within 5% of Panther Lake’s single-core performance.

With Geekbench, Apple silicon tends to perform especially well, particularly in single-core tasks, so keep that in mind.

Even with a bit of extra clock speed, however, the Framework Laptop 12 with the Core 7 350 came in behind the Core 5 320 in the XPS 13 in Handbrake. Here, the Geekbench swing toward Apple levels out; the A18 was 8% ahead in Geekbench 6 multi-core, but it’s less than 3% ahead here in Handbrake.

The Panther Lake-based 13 Pro gives some much-needed context, showing compounding factors between higher core counts, higher power limits, and true dual-channel memory. Again, it’s a far more expensive laptop, and the Framework Laptop 12 performs in line with our expectations for laptops in this class.

Perhaps the biggest takeaway is how similar the Core 5 320 is, at least in this laptop. You get an extra 200 MHz on the CPU and 100 MHz on the GPU with the Core 7 350, which isn’t moving the needle a ton here given how limited Wildcat Lake is as a platform. That’s good news, as the Core 5 320 will save you $220 in the Framework Laptop 12 compared to the Core 7 350.

Unfortunately, many of our gaming tests for laptops won’t run on Linux, and given that devices are often shipped back, we can’t go back and retest a dozen devices. That’s not too important here, though. The Core 7 350 has just two Xe3 cores, as do other Wildcat Lake chips, which doesn’t provide enough horsepower to power most titles.

We were able to achieve 30 FPS in Civilization VI at 1080p, which underscores the limitations of the integrated graphics. Intel’s dual-core Xe3 is plenty capable of running Balatro, Vampire Survivors, or whatever 2D sidescroller is currently popping off on Steam. Otherwise, it’s there to give you a display output.

Display

The display is what separates the Framework Laptop 12 from the various other Wildcat Lake-based devices we’ve seen in the wake of the MacBook Neo, and not for the better. Color performance, especially, is weak in our testing, and although peak brightness is in line with similar laptops, the 60Hz refresh rate is a severe downgrade compared to other devices, as is the 1080p resolution.

For metrics, you can see the display peaked at 451 nits, right in line with the MacBook Neo and Framework 13 (non-Pro). However, gamut coverage is poor, with just 64.9% of the sRGB gamut measured, compared to wide-gamut coverage on the competing machines. This is a “budget” laptop, but it’ll easily run over $1,000 with most configurations, and the display is not worthy of that price.

The XPS 13 provides some important context. It doesn’t get as bright — though, it’s hard to split hairs over 50 nits — but it comes with a 120Hz refresh, a higher 2.5K resolution, and it’s a touchscreen like the Framework Laptop 12. That gap in display performance would be understandable with a big gap in price, but that’s not the case. In fact, the Framework Laptop 12 clocks in at $1,271 with a Core 5 320, 16GB of memory, and 500GB of storage. The XPS 13, meanwhile, is $1,000 for that configuration.

Framework naturally needs to cut corners at this price, and it needs to engineer its devices to be repairable and upgradable. So, it’s hard holding the Framework Laptop 12 to the standard of a device like the XPS 13 that doesn’t come with those serviceability upsides. Still, the display is a consistent reminder that this is a budget laptop, whereas with the XPS 13 and MacBook Neo, it’s easy to forget that when doing day-to-day web and office task, due to the premium screens and build quality.

Keyboard and Touchpad

The Framework Laptop 12 comes with a standard keyboard/touchpad combo unit, which is available in several different layouts. There’s currently just a gray and lavender option for the keyboard unit, though presumably Framework will expand its offerings to cover the other colors available on the Framework Laptop 12 (at least with an American English layout).

I achieve 85 WPM with 99% accuracy in a MonkeyType test, compared to 92 WPM at 97% accuracy on my desktop (using the keyboard I type on every day). The keys have standard 19mm spacing and generous 1.5mm of key travel, which makes it comfortable to type on, even considering the small footprint of the Framework Laptop 12.

The touchpad is naturally small given the size of this device, and it’s mechanical, leading to sharp dips during presses on the bottom corners and no responsiveness near the top. It’s a serviceable touchpad, what you’d expect to see on this class of device. Just don’t go in expecting to be spoiled with a large glass surface or haptics.

Upgradeability

Framework built its brand on upgradability, so it’s no surprise that the Framework Laptop 12 earns near-perfect marks here. Like other devices, you can ship the Framework Laptop 12 pre-assembled, or as a barebones system that can accept your own M.2 2230 SSD, DDR5 SODIMM, and operating system. Even then, you can swap out the keyboard, display, mainboard, and ports if you choose (though only within the Framework Laptop 12 form factor).

However, the Framework Laptop 12 brings up the important distinction between serviceability and upgradability. The Framework Laptop 12 is the gold standard (among all Framework devices) for serviceability.But the Wildcat Lake chip brings up concerns about upgradability with its single-channel memory interface.

You can upgrade the memory up to a 64GB DDR5-6400 SODIMM, but there’s only one physical memory slot on the board. Wildcat Lake exclusively uses single-channel memory; it’s not simply a single-channel configuration for a budget price point. You can upgrade to more capacity down the line, but you can’t simply add in a second SODIMM to double your RAM.

You won’t find a more serviceable laptop on the market (outside of the other options from Framework) than the Framework 12, but you primarily have two narrow upgrade paths: more storage and more memory capacity, but not a true dual-channel configuration. Hopefully Framework will continue this line in the future, allowing you to swap the mainboard.

On the serviceable end, however, Framework makes things simple. You get a matching Torx screwdriver with the laptop that can detach the bottom cover. The cover has eight captive screws, so you don’t need to worry about losing them, and it’s primarily there to keep everything together; you actually service the laptop from the top, under the keyboard.

Considering you’re meant to go inside the laptop, Framework has everything clearly labeled, along with QR codes that link to repair guides for various components. With our barebones kit of modules, the laptop was powered on and assembled within five minutes, and this is my first time ever assembling a Framework device from scratch.

Battery Life

Our typical laptop battery tests are based on Windows, and we can’t replicate the testing process on Linux. Framework assured us that Fedora 44 offers the best experience out of the box, so that is what we tested. Instead of a direct comparison, we designed a basic web browsing test loop to see how long the 50WHr battery would hold up away from a charger.

About 9 hours is the answer, with a 9:16 average across three runs. We ran the laptop through a series of live websites with the screen set to 150 nits, Wi-Fi on, and Bluetooth disabled for the test. Again, we can’t make direct comparisons with Windows laptops, but getting around a full day of work is solid for the small 50Whr battery. And with USB-C charging, you can pretty easily top off with a portable GaN brick.

Audio

The stereo 2W speakers inside the Framework Laptop 12 are surprisingly powerful, considering the size of the machine, though the quality of the speakers and dual internal microphones is a clear cut corner to reach the more affordable price of the device. Thankfully, there’s a 3.5mm headphone jack built in (it doesn’t take a module slot), along with Bluetooth 6.0 support for wireless headphones.

The microphone poses a larger issue than the speakers. It’s heavily compressed, which helps make your voice come through clearly, though at the cost of heavy background noise (including keyboard and trackpad noise). You’ll want to use something like EasyEffects in Linux to clean up the microphone audio.

As for the speakers, they’re not as bad as they could be. As mentioned, they’re loud considering the size of the device, and they didn’t distort at full volume. They’re tuned for this type of device, as well. Rather than overemphasizing the highs or pumping too much low-end and exposing distortion, the speakers in the Framework Laptop 12 have a heavy emphasis on the upper midrange.

This range, somewhere between 500Hz and 4kHz, is typically described as “boxy,” and that emphasis works well for the small drivers in the Framework Laptop 12. It implies a low end that the drivers aren’t actually capable of producing. Further, the higher-end of this range, around 1kHz to 2kHz, is where many human voices fall, with sharp consonants pushing higher-end harmonics that come off as harsh. Again, the emphasis helps, allowing voices to come through clearly, without sounding tinny.

Heat

The Framework Laptop 12 stays fairly cool, even under load. The hottest point we measured on the laptop was the underside, directly in the middle, which peaked at 101 degrees Fahrenheit (about 38 degrees Celsius). Under normal usage in a browser with a handful of tabs open, there’s very little noticeable heat, even at this hottest point.

Up where your hands are, we measured 94 degrees Fahrenheit (about 34 degrees Celsius) between the G and H keys on the keyboard, and 86 degrees Fahrenheit (30 degrees Celsius) on the touchpad. That’s warm for your hands, but again, the heat only crops up during heavy load.

Webcam

It’s unsurprising for a laptop at the price of the Framework Laptop 12, but the webcam quality is poor. The camera oddly uses a 4:3 aspect ratio, and the 2MP sensor creates an image more reminiscent of a watercolor than a sharp, Full-HD picture. It struggles with low-light especially, with even moderate shadows in an otherwise brightly-lit room showing visible noise.

The image above was taken in my office in the middle of the day. A window behind me was fully open, about three and a half feet away, and I have a lamp serving somewhat as a key light about three feet off-screen to my left. I’m on the second floor of a two-story house, on a hill without any trees obstructing sunlight (and it was a sunny day). There was a generous amount of natural light in the room.

Yet, you’d think I was sitting in near darkness from the webcam image. The stark brightness from the window darkens my face, filling it with visible noise, as the camera struggles to handle the dynamic range. Sitting in front of an unobstructed window during the middle of the day is the time and place where you’re likely to have the webcam turned on, and it fails that test.

Software and Warranty

Framework offers a standard one-year limited warranty on the Framework Laptop 12, with an optional three-year warranty available for $89 extra. You can read over Framework’s limited warranty, but the limitations are fairly straightforward. Normal wear and tear, damage due to negligence or misuse, and use of third-party parts (or first-party parts from third-party sources) will void the warranty.

Broad warranty protection isn’t as important here as it is elsewhere, however. If, for example, your USB-C port stops working, you can just buy another one rather than going through the RMA process and potentially paying for a repair on the other side (even if you’re under warranty).

You’re free to bring your own OS, but Framework also offers the Framework Laptop 12 with either Windows 11 or Fedora 44 pre-installed. Framework normally uses Ubuntu; however, Fedora 44 has moved to the newer Linux 7.1 kernel, which has optimizations specifically for Wildcat Lake. Using a slower-moving distro like Ubuntu is fine, though you’ll want to make sure to manually upgrade your kernel (and packages) for the best performance if you’re not already using a distro with kernel 7.1 or newer.

Configurations

Framework offers three mainboard configurations: Core 3 204, Core 5 320, or Core 7 350. As we covered in the performance section, the Core 5 320 in the XPS 13 offered largely similar performance to the Core 7 350 in the Framework Laptop 12, so that seems like the sweet spot here. The Core 3 304 is effectively a single-core CPU, with just one P-core alongside a four-core LPE cluster, and it lacks a fingerprint reader, which is available with both other mainboards.

With the DIY edition, Framework ships the laptop without memory, storage, or expansion cards. There’s a single SODIMM slot for memory and a single M.2 2230 slot for the SSD. Framework offers up to 2TB of PCIe 4.0 storage at checkout, as well as up to 48GB DDR5-5600 (again, via a single SODIMM). Framework has USB-C, USB-A, HDMI, Ethernet, 10G Ethernet, DisplayPort, microSD, and SD card modules available, ranging from $10 to $99.

There aren’t any display options aside from the standard 60 Hz 1080p panel in our unit. For the keyboard and trackpad, Framework offers backlit and non-backlit options in various different native layouts.

Framework offers prebuilt versions of the Framework Laptop 12 at a discounted price. The Core 3 304 comes with 8GB of memory ($699), the Core 5 320 comes with 16GB (1,099), and the Core 7 350 comes with 32GB (1,399), and all three configurations use 512GB of storage. All of the configurations come with Framework’s standard expansion card bundle: two USB-C, a USB-A, and an HDMI module.

Dell starts higher with the XPS 13 at $799, but that’s with the Core 5 320 and 8GB of memory. Jumping up to 16GB, the XPS 13 is $999 with the Core 5 320, $100 less than the preconfigured Framework Laptop 12.

Bottom Line

The Framework Laptop 12 is caught between an unprecedented memory and storage shortage and a wave of budget-oriented Windows laptops that skip the repairability angle in favor of better trimmings out of the box. At the same price, it’d be a solid alternative with understandable downsides. The killer for the Laptop 12 is that you’ll likely spend more on it compared to other Wildcat Lake options.

With the Core 5 320, the Framework Laptop 12 is nearly $300 more expensive than the XPS 13, when both are configured with 8GB of memory and 500GB of storage. The Acer Swift Air 14 is $700, and a similarly configured Framework Laptop 12 is $1,074 before adding on the extra cost of a power adapter and modules. For many Wildcat Lake devices, we see prices top out around $1,000; with the Framework Laptop 12, you’ll often spend at least $1,000, assuming you push beyond the Core 3 304.

Modularity comes at a cost, which is more relevant in the case of the Framework Laptop 12 where $100 or $200 makes all the difference in value (it’s less relevant up at the Framework Pro 13, where you expect premium pricing). That extra cost is especially damaging here, when Framework’s competitors are offering better display performance (and more pixels) and all-aluminum bodies for less money.

There are situations where the Framework Laptop 12 is a great option, even compared to the other Wildcat Lake devices on the market. If you already have a SODIMM module you can harvest from other devices, along with an SSD, this is a cheap way to get some of Intel’s latest silicon. But for everyone else, unless you don’t mind paying significantly more for repairability, there are better options available that typically cost less, look better, and feel more premium.

Chinese tech companies have bought more than 1 million Nvidia gaming and workstation GPUs to plug gaps in demand for AI computing power, Financial Times reports. The report cites industry insiders who claim the buying spree highlights an ongoing and significant reliance on U.S. AI hardware, despite a burgeoning homegrown market.

The report firstly notes that China's national strategy for developing AI has led to a doubling of domestic AI chip production this year; however, the country cannot keep up with demand from its biggest tech companies. The report cites a shortfall of nearly 1.5 million chips, with only 3.5 million expected to be manufactured domestically while demand "far exceeds" 5 million. To compensate, China is purportedly turning to Nvidia's gaming and workstation processors, which are compliant with U.S. export controls, repurposing them for AI.

According to FT, the chips are "mostly" Nvidia's RTX Pro 6000D, RTX Pro 5000, and the RTX 5090, the latter of which is the best graphics card on the market for enthusiast gaming. As the report notes, these Blackwell chips can't compete with Huawei's Ascend 910C and other homegrown flagship offerings, but they are useful for "simpler AI workloads," such as prefilling.

This is significant pressure on a GPU market where prices for enthusiast cards have already skyrocketed. The RTX 5090's MSRP is $1,999; however, the card can now only be found at a handful (three) of third-party resellers for no less than $7,199, and has all but disappeared from the market.

The report highlights that demand for Nvidia's GPUs is driven in part by its CUDA software, which remains more favorable than Huawei's Cann alternative.

As for the enthusiast market, it was recently reported that Nvidia has halted RTX 5090 production, to be replaced by a 24GB RTX 5080 flagship. That would mark a significant step down from the 32GB the 5090 currently boasts, a troubling sign for enthusiasts that the enthusiast gaming GPU market appears to be receding, rather than advancing.

Anthropic's Frontier Red Team has demonstrated two components of a potential AI-powered worm that, if key issues with the practical implementation are resolved, could spread across consumer devices including inexpensive Android TV boxes and smart appliances, hypothetically without relying on datacenter infrastructure. The experiments show that AI agents can configure inference across different hardware platforms and orchestrate replication across a network. There are still some serious limitations, though, particularly around the gap between the capabilities of today's models versus the hardware constraints of potential targets.

In its October 12 report, titled "AI models may be capable of self-replicating without access to a datacenter," Anthropic examines a potential class of malware called a weight-based replicator. Rather than distributing conventional executable code, it would propagate AI model weights alongside the software infrastructure needed to run inference on compromised devices, and it's not pure theory, either.

The researchers demonstrated that Qwen3.5-9B can establish an inference server on eight of nine tested hardware types, spanning NVIDIA Jetson Nano devices, Apple Silicon Macs, Xeon servers, a Google TPU, AMD's MI300X, and at least one PC with an RTX 4090, among others. They also ran Gemma4-26B-A4B across 15 off-brand Android TV boxes costing approximately $55 each, achieving a combined generation rate of 0.39 tokens per second.

Anthropic also tested whether a model could orchestrate replication across a network. The experiment used eight Google Cloud nodes running Android 15 emulators. A seeded agent propagated between nodes through an unauthenticated Android Debug Bridge (ADB) port, transferring files and establishing an inference server on each target. GLM-5.2, a titanic model with 744 billion parameters over 1TB in size, completed the replication sequence across all eight nodes in four of five trials, reaching seven nodes in the remaining trial.

No other tested open-weight model was able to complete the sequence at all without orchestration from GLM-5.2, and they weren't able to meaningfully ask a larger model for help, either, despite being equipped with the capability. Naturally, GLM-5.2 wasn't actually replicating itself onto smart TV boxes; instead, it established an inference server for the much smaller Llama 3.1 8B on each target. GLM-5.2 ran on a separate inference server because the emulated nodes couldn't handle the larger model.

In other words, Anthropic demonstrated that a very large, externally hosted model can orchestrate a simplified replication sequence across machines with deliberately exposed ADB interfaces, and it showed that small models can set up inference, but it absolutely hasn't proven that a small model can independently replicate itself across consumer hardware. That distinction, admittedly fine, is nevertheless pretty important when the entire premise is that small models could soon spread without relying on datacenter infrastructure.

The experiments expose a central constraint of the research: models capable of reliably completing the replication sequence aren't currently small enough to run on inexpensive target devices, while models that fit within those devices' memory budgets, despite being capable of setting up inference, still can't reliably complete the entire process. This gap between the intelligence needed for reliable replication and the maximum model size that target hardware can support means that this threat model isn't really applicable right now, but Anthropic warns that gap could narrow, and potentially soon.

Using historical improvements in general AI capability (measured through the Epoch Capabilities Index), Anthropic projects that a model within the 30-billion-parameter class could reach the necessary capability level by the end of 2026. But once again, that's a hypothetical, and it still doesn't address the substantial efficiency problem.

Based on measured inference performance and the token requirements of its setup experiments, Anthropic estimates that establishing an inference environment would take approximately 28–51 hours for Qwen3.5-9B and 71–150 hours for Gemma4-26B-A4B at the observed throughput of its cheap Android TV boxes, and it’s worth noting that the boxes it used are configurations with 4GB of RAM, a relative luxury among these cheap set-top boxes. A model-driven replicator could take days to establish an inference environment on a new host, whereas conventional malware can execute its payload within seconds when its assumptions about the target hold. A conventional worm can spread to tens of thousands of vulnerable targets in minutes.

Model weights also impose substantial bandwidth and storage costs. Anthropic acknowledges that compromised hosts could download weights from external repositories rather than receiving them directly from an infected device, and that not every compromised machine would need to host a model. Nevertheless, distributing multi-gigabyte payloads and maintaining communication between machines running a sharded model would generate tremendous network traffic, making the activity very easy to detect.

Anthropic estimates that a hypothetical fleet comparable in size to the infamous Kimwolf botnet, which infected more than two million devices at its peak, could support approximately 133,000 instances of Gemma4-26B-A4B if every 15 devices collectively hosted one model. At the measured throughput (which benefits considerably from LAN latency), Anthropic says that such a fleet would provide roughly 40 Hopper H100-equivalents of inference capacity.

This is a very messy comparison that takes significant liberties with the data, but even at that it must be said that it's not particularly intimidating. We're talking about two million infected devices that must remain infected and operable for months (or years; infecting 2 million devices would take around 6,300 agent-years even with the fastest 28-hour stand-up speed) to produce less AI inference throughput than a few blades of previous-generation GPUs.

Anthropic notes that a real replicator could exploit other types of hardware, deploy different models across heterogeneous devices, and avoid loading model weights onto every compromised host. Those possibilities certainly complicate the comparison, but arguably they complicate it beyond the bounds of this discussion.

The research does identify a meaningful security concern: AI agents could make malware more adaptable to unfamiliar environments and reduce the amount of target-specific engineering required. A hybrid approach, combining conventional code for routine operations with AI-driven reasoning when unexpected conditions arise, could offer some of those benefits without requiring every compromised device to run an inference engine continuously. This is definitely concerning, but we've already seen AI agents using frontier intelligence write their own code to compromise secured systems, so that specific angle on this research isn't exactly groundbreaking.

Anthropic's experiments are useful in that they provide evidence that autonomous software configuration and simplified network replication are increasingly feasible, but turning those capabilities into a materially more dangerous class of malware will take improvements in model reliability, hardware compatibility, deployment efficiency, and the ability to overcome real-world security controls, which the firm didn’t test. There’s a ton of data and some interesting findings not discussed here in the actual paper, so if you’re interested in the research you should go check it out.

A person claiming to be responsible for the recent hack of Denmark’s national registry claimed that they were able to gain access because of an IT company’s weak password. According to The Register, Pays ApS, an IT and data services company that lets customers reference the Danish Central Register of Persons (CPR) was the source of the hack, with the hacker saying that one of the accounts they breached was only protected by a ‘123456’ password.

Copenhagen has confirmed the hack, with a government official saying that the breach was discovered 12 days after it happened when an invoice revealed an unusual amount of activity from the company. The Danish government said that 8.8 million records have been illicitly retrieved, although the hacker claimed that they do not intend to sell or leak the information. While the government did not mention which company the hacker exploited, Pays ApS managing director Sophie Laursen confirmed that the hacker used the company’s access to the database to exfiltrate the data.

This incident shows that a system’s security is only as strong as the weakest link, with the Danish database getting compromised through a third-party user’s poorly chosen password. Given that CPR essentially contains information on virtually every Danish citizen, one would expect that it would require users to at least have a more complicated password, if not two-factor authentication. This isn’t the first time that an incident reveals shortcomings in government database protection, though — Indonesia realized that it had no backups when a ransomware attack in 2024 affected over 230 public agencies, while South Korea lost 858 terabytes of data after a catastrophic fire at a government data center last year.

We expect the Danish government to overhaul its password policies in the near future, especially now that AI is making it easier and more efficient for hackers to hit their targets. Recent incidents like the attacks on South Korean banks and against the Taiwanese government were reportedly conducted with the help of AI agents. Hackers also breached OpenAI using Claude tools, showing just how potent AI has become as a hacking tool in the wrong hands. But with a password like “123456,” potential hackers wouldn’t need to use any AI tools to break into weakly protected systems.

Nvidia has today announced that its somewhat controversial DLSS 5 technology — AI-powered neural rendering for gaming — is now two times faster than the current model, marking a 10x performance leap since March. The model is also now smaller and uses up to 20% less VRAM.

Nvidia says it has achieved this through a combination of "systematic pipeline optimizations and neural model refinements." As mentioned, the latest performance jump over the current model is a 2x leap, which means that the transformation DLSS applies to games through lighting and beyond will now run at higher frame rates or more intense settings.

Nvidia says the DLSS 5 October update shrinks the overall DLSS 5 model's footprint by nearly a quarter to 118 million parameters, and reduces VRAM usage at 4K by 20%. As such, the company claims that at similar visual fidelity, the GPU overhead versus the September model has been halved. Elsewhere, Nvidia says the change can boost frame rates by up to 1.4x.

The new faster model will debut in NBA 2K27 on October 16; you can see a comparison in the video below:

Nvidia confirmed it will bring DLSS 5 to Hogwarts Legacy next month. The technology continues to be supported on RTX 50-series GPUs, as well as GeForce NOW and the new RTX Spark lineup.

Nvidia is also introducing a new faster Performance Mode for Frame Generation on RTX 50 Series, as well as RTX 40 series GPUs, and RTX Spark laptops. The company says that a new "Preset C" mode replaces the AI model previously used "to calculate optical flow for elements like UI or ray-traced effects" with a new algorithm that is faster and lighter, boosting DLSS Frame Generation, MFG, and Dynamic MFG. The company says this is worth 35% in terms of speed on the RTX 5060.

Last week, OpenAI shared over 400 results for longstanding mathematical formulas that have troubled humans for decades; now researchers say it could take years for humans to validate and prove all the AI-driven work. But while analysts try to check the work of the unnamed OpenAI internal frontier model that found these alleged solutions, mathematicians argue this kind of AI-powered research and release threatens the field itself.

There's even the claim that by leaping from a prompt to a solution without a clear working in between, there is little benefit to these solutions in the first place. Mathematicians and the field itself may not be able to build on the results, as they don't know how they were achieved, nor has the development of such solutions produced new fields of mathematical understanding.

To make matters worse, there are suggestions that the growing confluence of mathematical and cybersecurity capabilities of frontier AI could bring into question the sanctity of cryptography itself. Alongside raising serious concerns for national security and modern digital systems, it could also put trillions of dollars worth of cryptocurrency at imminent risk.

Over 722 manuscripts dropped

The official count for OpenAI's maths solution release was 722 manuscripts, but with only 300 of the results formalized — digitizing human-readable formulas so they can be computer-verified — it's very difficult to know what's legitimate research. Some of the researchers The Verge spoke to found nonsense explanations within the reports, formulas that don't make sense, and some research that has already been completed by others.

The burden of proving the veracity of OpenAI and its model's claims is very much on the mathematical community, too. OpenAI didn't release the name of the model it used to generate these results, nor the prompts that generated them — despite those recommendations from the Advisory Group on Mathematicians and Artificial Intelligence (AGMAI).

OpenAI has at least published changelogs for its GitHub repository of the results, making it clearer where mistakes were made. But with several retractions and corrections already, it seems clear that it didn't check over the results in any great detail before releasing them.

It's this brashness, the pace of releases, and OpenAI's seeming disinterest in remotely slowing down its progress in the field that have so many mathematicians up in arms.

A looming threat becomes immediate

Mathematics isn't the first field to suffer a major upheaval because of AI. Writers first felt the looming threat with the release of ChatGPT in 2022, and both visual and musical artists faced the same concerns shortly after. Artificial intelligence is impacting almost every industry in some way, but while there are some potential benefits for its use in the field of mathematics, researchers within the field are concerned about the impact this may have on the collaborative nature of the field and how it might discourage future mathematicians from exploring it.

Speaking to Business Insider, mathematics professor at NYU, Tristan Buckmaster, said that OpenAI's release had upended the world of many early-career mathematicians, suggesting it had wiped out their whole research programs. Alongside their own research being invalidated by some of OpenAI's solutions, he suggested that some were now fearful that, by using AI tools, researchers had inadvertently contributed to the results, raising the potential of them not using advanced tools in the future and being less likely to talk about their research publicly.

This could cause huge problems for mathematics as a whole, argued mathematics professor at Northwestern University, Bryna Kra. Highlighting how collaborative maths is, with researchers sharing ideas, research data, and formulas, she is now extremely concerned that OpenAI has made mathematicians more secretive, reducing their ability to work together towards solutions and build on each other's research.

Professor of mathematics at the University of California, Terence Tao said on Mastodon that "many fewer seminars, workshops, collaborations, or other activities are being generated from these results compared to traditional breakthroughs." He argued mathematics may need to pivot to value "progress more holistically," by elevating the role of community building over raw solutions.

Researchers have described an atmosphere of extreme anxiety, that whatever they're working on could be invalidated overnight. That can undermine job applications, grant proposals, and those building the early components of their academic careers. Understanding and developing core mathematical capabilities at a high level can take years. AI dumps eradicating years of effort in such a haphazard fashion risk making it seem a near-pointless endeavour.

With swirling rumors of yet more releases from OpenAI, and potentially companion releases from other AI labs chasing the same headlines, the morale in many mathematical fields is extremely low.

Cryptography

With how much mathematics underpins key components of our digital world, it's no surprise that major changes in the pace of its development could have a domino effect elsewhere. One proposed potential minefield is the fertile ground of cryptography.

Associate professor of computer science at Johns Hopkins Whiting School of Engineering, Matthew Green, said on social media that he believes the congruence of mathematical developments and cybersecurity capabilities could result in AI that can defeat encryption as we know it.

While that raises potential concerns for all manner of fields that rely on encryption to protect the security of sensitive data, it could open up the cryptocurrency industry to wholesale theft, potentially impacting trillions of dollars of digital tokens.

Not everyone agrees with Green that this is an inevitability. British cryptographer — and one of the few people accused of being Bitcoin developer Satoshi Nakamoto — Adam Back, described these claims as nonsense and that there was little suggestion that just because AI can do certain mathematics now, that they'll be able to defeat encryption at some unnamed date in the future.

Ethereum creator Vitalik Buterin urged calm too, stating on Twitter/X that nobody should rush to move their tokens to a new wallet or panic over wallet security. However, he did argue that AI had the potential to one day be a far more dangerous threat to the sanctity of cryptocurrency than quantum computing.

While it doesn't appear that cryptography is a field AI is set to invalidate just yet, it's clear that it poses a potential threat to mathematical researchers and the core underlying 'way of doing things.' Much like it has just about everywhere else.

Researchers are adjusting to it, but the dust isn't likely to settle anytime soon, and in the meantime, OpenAI and its contemporaries may just move on to a new field to focus on as it continues to chase relevance and profitability.

Epic Games has reportedly delayed a shooter based on Disney’s Marvel and Star Wars franchises, with its developers told to use more AI. According to Bloomberg, the yet-to-be-named game was supposed to be released in March of 2027, but its launch date has been pushed back to an unspecified date. Aside from that, the company also told the people working on the project to switch to an “AI first” production model. One of the game directors was quoted telling staff that there will be “no more handwritten code” and that the game’s art would now be “generated with full AI workflows.”

Around the same time this news came out, Epic boss Tim Sweeney posted an update on X that seemingly confirms the change. “We have a huge pivot underway here at Epic, moving developers around to retool for maximum AI acceleration,” the Epic founder said on the platform. “The aim isn’t to do the same stuff with fewer people, but to enable everyone here to build MORE and BETTER stuff, and to bring the benefits to all teams using Unreal.” Sweeney has previously criticized Steam for putting AI tags on games, calling it “irresponsible of Valve.” He says that AI is just a tool and that it’s useful for handling boring, menial, and repetitive tasks like finding errors in code or rigging 3D models. “We’re embracing AI-accelerated development, led by Epic developers who are the visionaries and creative drivers for everything we do,” Epic Games communications director Jake Jones told the publication.

The announcement still reportedly left some of the developers working on the project in a state of astonishment. They were hoping that the directive wasn’t serious or that Epic Games would change its mind about the decision, while others jokingly asked if they should ask Claude to fix its own errors. The delayed title was supposed to be the first in a series of games involving Disney intellectual property, which had invested $1.5 billion in the game developer and publisher in 2024. However, Bloomberg reports that progress on the game has suffered because it lacked the number of people required to keep the schedule on track. It seems that the company is trying to make up for lost time by pushing its people to use AI in the hopes that they’ll be able to work much more quickly.

AI is indeed quite a useful tool, with some developers using it to build surprisingly complicated vibe-coded games, like this GTA clone set in Taipei or this decompiled version of Call of Duty: Modern Warfare 2. One group even used Gemini for their free game demo, leading to a cost of $1,000 a day in AI usage bills. Despite that, many creators and developers have been against the use of AI in the industry, with one major gaming convention in the UK outright banning games that were built mostly using AI.

Buying some RAM or storage right now means burning a massive hole in your wallet; individual component prices have reached and surpassed all-time highs, with the best ways of grabbing either of these components at a more reasonable price limited to combo deals or prebuilt gaming PCs. That's where today's deal strikes. You can pick up a gaming PC at Walmart with a large 64GB of memory and a 4TB SSD, along with a host of other powerful components, and avoid paying the standalone component tax. Grab the CyberPowerPC Gamer Supreme with RTX 5070 Ti for $2,739.99. Although still a chunk of change, it's a far cry from the original cost of $4,179.99, saving you a massive $1440 (34%).

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This CyberPowerPC packs an AMD Ryzen 9 9950X processor, an Nvidia RTX 5070 Ti graphics card, 64GB of DDR5 RAM, and a 4TB SSD for storage. A great spec list if you're looking for a PC for video editing, or if you just want to have a trillion browser tabs open.

Nvidia's RTX 5070 Ti graphics card comes with 16GB of superfast GDDR7 VRAM and is perfect for 1440p gaming, even performing well at 4K. If you're thinking of a new PC for video editing, the RTX 5070 Ti is also a competent choice.

For multithreaded applications, the 9950X from AMD is an absolute beast, one of our best-performing processors in our benchmark testing quite. It's also not too shabby as a gaming processor, but it falls behind the X3D CPUs in performance due to the lack of stacked 3D V-cache and lower memory. See our benchmark chart below for how the 9950X compares to other AMD processors and the competition from Intel.

We haven't reviewed this specific CyberPower gaming PC, but we have tested individual parts like the GPU and CPU. For more in-depth details and benchmark testing, check out our full reviews of the AMD Ryzen 9950X and Nvidia RTX 5070 Ti.

CXMT expects to launch its first 4F² product, a server DDR5 RDIMM, by the end of the year, company president Cao Kanyu said in remarks reported by Yicai. The memory will be built on a denser cell layout, not yet commercialized, using vertical transistors to reduce the cell’s footprint by about one-third on paper. No speeds or capacities have been announced yet for the new product.

Cao spoke about the new RDIMM at the Integrated Chips and Chiplets Conference on Saturday. A 4F² cell is 2F by 2F at about two-thirds the area of current 6F² cells at the same feature size, and designs so far all stand the transistor up. The company has produced research and patent filings on the technology with papers in 2021, 2023, and 2025, and an 8Gb full-array research example was demonstrated at IEDM 2023.

Cao said CXMT’s version, the Vertical Surrounded Gate (VSG) transistor, has a channel that stands vertically with the gate wrapped around it, allowing stronger gate control with less leakage. Most importantly, standing the transistor up shrinks the cell. CXMT now has more than 300 published patent families tied to 4F², he added. The report says the industry as a whole is moving toward 4F² with 3D solutions that decouple DRAM and CMOS processes, combining them with wafer-level hybrid bonding, which allows logic and cell density to be optimized independently. Cao also covered CXMT’s own hybrid-bonding work, which began in 2019, with published patents.

Aside from this announcement, China’s primary DRAM maker has been in the news lately for its manufacturing and market-share gains. Its fifth-generation G5 DRAM technology platform, announced Sept. 20, is in mass production. TrendForce puts CXMT’s share of global DRAM revenue at 9.5% in the second quarter, up from 7.6% in the first, good for fourth place. Last November, CXMT showed off DDR5-8000 and LPDDR5X-10667. It has revealed itself as a manufacturer to be taken seriously by the biggest existing players.

Samsung showed off a 16Gb, 10nm-class 4F² DRAM design in its ISSCC 2026 paper in February. That one also used vertical-channel transistors (VCT), with the array bonded on top of the periphery using wafer-to-wafer hybrid copper bonding. The company claims the bonding raises dies per wafer by more than 20% with the same design rules. In April, The Elec reported that Samsung had a working 4F² VCT die on its sub-10nm “10a” process, with mass production targeted for 2028. Later South Korean reports clouded that date: the VCT version has since been split off as “D0a-V” with no timeline, and there is no firm timeline for adopting 4F².

SK hynix laid out plans at VLSI 2025 for a 4F² vertical-gate platform and 3D DRAM at nodes of 10nm and below, with circuitry bonded under the cell array. The April report also puts SK hynix’s 4F² debut at the 10b node, one step after Samsung’s 10a. Micron’s plans remain less clear, with no widely reported 2026 statement.

The announcement is perhaps more interesting for what wasn’t mentioned: capacity, speed, die density, process node, named customers, or intended volume. All we have is a date and a purported cell design, admittedly well-supported by the literature, but no product that has been tested by anyone outside of CXMT. Beyond Cao’s talk, CXMT hasn’t posted a release about the product in its Chinese or English newsrooms.

South Korean reports have said that CXMT’s initial products may only partly use 4F² and that producing stable units at volume is a separate challenge. With about 11 weeks left in the year, it will be interesting to see what CXMT actually delivers.

Cryptocurrency enthusiasts are often advised to acquire a hardware wallet like one of the Ledger models, theoretically adding the ultimate layer of security. And yet not even that approach is 100% safe, as a currently unfolding investigation revealed that Ledger resellers in Southeast Asia and Europe are carrying hacked wallets laden with eSIM and LTE modules for exfiltration of recovery phrases. At least $93 million (and going) has already reportedly been siphoned off users' balances. Hardware sold directly by Ledger is so far unaffected.

The first booby-trapped wallet originated from reseller Cryptobilis, which has currently ceased all sales of hardware wallets of all brands. The offending unit came from a store in Malaysia, though Cryptobilis also sells in Indonesia and the Philippines. Researcher Mark Karpelès has been looking into hacked wallets for a while now, and one of them came via Amazon Japan, bought from a Chinese seller and shipped from Malaysia. Cryptobilis also sells other brands of wallets such as Trezor, Coolwallet, and Tangem, though so far there is no news of contamination beyond Ledger.

Ledger recommends that users who bought wallets from Cryptobilis in the past 90 days do not perform their initial setup, as that's where the private key exfiltration reportedly occurs. To those who have already done so, Ledger recommends moving their assets to a new wallet with a new seed. The data theft is performed by hiding a flexible PCB under the display assembly to capture the pixels showing the private key entered during the first setup. The information then heads off to the aforementioned eSIM+LTE combination for exfiltration.

Meanwhile, new reports have come in from Europe, as techie Johannes, seemingly located in Germany, found at least two hacked wallets at MediaMarkt, a well-known tech and appliances retailer. He bought one unit and found that it had the same exact hardware modifications as its Asian counterparts, suggesting that the Asian and European events may be related. Johannes then bought a second one at a different MediaMarkt location, and sure enough, it was also modded.

Notably, most hacked wallets found so far are confirmed to be brand-new units instead of returns. Malfeasants will often buy new hardware and return it to the store with modifications, so that the next unsuspecting customer gets bit.

Johannes had a MediaMarkt employee at one of the stores look up the wallets' stock information, and at least the one unit came from Aqipa GmbH, a Europe-wide distributor — meaning the blast radius may be much wider than MediaMarkt or Germany. Since this is a recent development, Ledger hasn't published any guidance, though we imagine it'll be similar to the aforementioned steps.

In his blog post, Mark Karpelès notes that earlier iterations of hacked wallets with eSIM cards had hand-made implants, but that, concerningly, the hardware bolt-ons inside the latest finds appear to be manufactured to order. If true, this might mean that there's a production line somewhere intercepting Ledger wallets and manufacturing hacked wallets in bulk.

Ledger publishes instructions detailing how users can verify the physical integrity of their wallets, including pictures of every component, for every model of wallet the company offers, so they can closely inspect for add-ons. Likewise, prospective users should only download software from the official Ledger website URL — a task made harder by numerous scam sites with booby-trapped software, pretending to be the official ones.

A pre-built desktop or gaming laptop is one of the best ways to sidestep some of the worst pain of AI-driven price increases when it comes to PC gaming. If you're on the hunt for a powerful gaming laptop, this Gigabyte Gaming A16 Pro is now just $1,449 at Walmart.

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This laptop comes with a 16-inch IPS display clocking in at 2560 x 1600. It's powered by Intel's Core 7 240H, a Raptor Lake-H refresh CPU with 10 total cores. However, the star of the show is undoubtedly the mobile RTX 5070 Ti GPU, which will excel at gaming on the go.

AI development has seen the price of individual PC parts skyrocket in recent months. 32GB of DDR5 6000 RAM now costs $450, with storage and graphics cards also enduring significant price hikes. One of the best ways to dodge these hikes is to buy a laptop, where increases are trickling down more slowly.

With 10 cores (six performance and four efficient cores), the CPU in this rig is ideal for both gaming and productivity on the go. Paired with the RTX 5070 Ti gaming GPU, it will have no trouble running most games at the 2560 x 1600 resolution. The RTX 5070 Ti has 12GB of VRAM and 5,888 CUDA cores, making it ideal for this resolution.

For the price, this laptop also has a generous supporting cast, notably 32GB of DDR5 RAM (a rarity in cheap gaming laptops these days), and a 1 TB SSD for storing your games.

Otherwise, you get HDMI 2.1 connectivity, USB 3.2, USB-C with DisplayPort, 3.5mm audio connectivity, and Wi-Fi 6E, as well as Bluetooth v5.2.

This would be an ideal laptop for someone looking to do some gaming on the go while also supporting productivity workloads, possibly a college student. It would also make a great upgrade for anyone currently using an older-generation laptop.

While Sony remains committed to phasing out physical media, Nintendo is taking the opposite approach. In a recent interview with the Brazilian YouTube channel Coelho no Japão, Bill van Zyll, Nintendo's VP and General Manager for Latin America, confirmed that the company has no plans to abandon cartridges.

"Historically, we’ve been very agnostic, right?" stated van Zyll in the interview.

The Nintendo executive firmly continued, "We go off what the consumer prefers, and take that into account very heavily. We also have a platform that was just launched. We're barely just over a year into NS2. It's got both digital and physical – that capability. There's no plans to ditch physical. We know how much the fans like it as well, so our position has been to be agnostic."

In an era where the gaming industry is rapidly shifting toward digital distribution, it is comforting to see at least some companies still supporting physical media. The core issue with digital purchases is that you do not truly own what you buy; instead, you are purchasing a license to access the game, unlike owning a cartridge or game disc. Some storefronts, such as GOG or itch.io, offer DRM-free downloads of the titles you purchase, but only a handful of them exist.

However, even cartridges cannot completely escape the march toward digitalization. With the release of the Nintendo Switch 2, Nintendo introduced game-key cards, physical cards that contain a license to download the full game data. Modern AAA game releases have exceeded the storage capacity of traditional cartridges or discs. For instance, Black Myth: Wukong and the upcoming Grand Theft Auto VI use this code-in-a-box model.

On the Nintendo Switch and Switch 2, cartridges max out at 32GB and 64GB, respectively. That is not much capacity by modern standards, so publishers turn to game-key cards as a compromise for a physical release. Compared with fully digital releases, game-key cards bind the license to the card, so owners can still trade or sell them like normal cartridges.

Owning physical copies can sometimes cost more than going digital, especially for Nintendo’s first-party titles. Effective as of May 2026, physical versions of first-party Nintendo titles sell for $10 more than their digital counterparts. The price increase was due to manufacturing, packaging, and distribution costs for cartridges. However, Nintendo frames the pricing adjustment differently, claiming it lowered digital game prices by $10 to pass the savings on to consumers.

Nintendo has announced plans for the Switch 2 to mirror its predecessor's lifespan, about six to seven years. No one anticipated Sony's decision to phase out game discs, so Nintendo's future remains uncertain, even though the company pledged to continue physical releases. With the Switch 2 launching just last year, we can at least look forward to another six good years of physical media.

At OCP 2026 today, Intel has given Crescent Island a proper name: the Intel GPU D-Series. For the first time, the company also shared a theoretical peak performance target for the chip: 1.3 PFLOPS of FP8. It also disclosed the final memory bandwidth to expect from these AI inference accelerators: 1.5 TB/s. This new information adds to the slow drip of disclosures Intel has made about Crescent Island throughout 2026.

We already knew that Crescent Island is the first chip to be built on Intel's Xe3P graphics architecture (or massively parallel computing architecture, really, as the chip lacks most or all of the graphics-specific functional units that would characterize a true GPU). Intel will release GPU D-Series products in an air-cooled PCIe form factor with a TDP of 350W and up to 480GB of LPDDR5X memory.

For reference, each of the 72 Rubin GPUs in Nvidia's Vera Rubin NVL72 rack-scale system can push a theoretical 17.5 PFLOPS of FP8 throughput, but each of those chips requires liquid cooling and likely has a TGP measured in kilowatts. In any event, it should be clear that the GPU D-Series is targeting an entirely different performance envelope and infrastructure requirements than Rubin.

Intel GPU D-Series products, in contrast, are meant to be deployed in traditional air-cooled rack servers scaling up to eight GPUs, like Nvidia's HGX systems. In such a configuration, Intel says that GPU D-Series chips could power inference on models spanning more than one trillion parameters. Intel also highlights the chip’s suitability for “large language models, long-context inference, and concurrent inference services," creating a foundation for "multi-tenant AI services, robotics, and other latency-sensitive workloads."

In order for that kind of distributed inference deployment to work, in which multiple GPUs will presumably act as one, Intel will also need a robust software stack. The company is highlighting the “common Xe software foundation” it’s already built for AI across its Xe Cores in iGPUs and discrete GPU products.

To bring Xe accelerators into the data center, Intel says it’s working with “a broad ecosystem of OEMs, ODMs, neoclouds, independent software vendors, appliance providers, and AI-native companies.” To that end, Intel says customer sampling of GPU D-Series products is in progress, although it didn’t provide any details of a broad launch.

It’ll remain to be seen whether the Intel GPU D-Series is the product that finally gives Intel an AI accelerator toehold after the failure of the Data Center GPU Max family (code-named Ponte Vecchio) and its mothballed follow-ons, as well as a series of silicon acquisitions that failed to coalesce into a coherent AI strategy.

But in a world that’s hungry for every compute cycle for inference, a product with a proven architectural shape that’s targeted specifically at that workload in an accessible thermal and electrical envelope might be just the recipe Intel needs to start getting traction as AI models keep advancing in intelligence and agentic workflows assume ever-greater importance in the computing vision of the future.

Bambu Lab has officially teased its S1 3D scanner, ahead of its planned release in November 2026. No details of the product have been released yet, but FCC filings and Bambu Lab’s partnership with SCANOLOGY may hint at the scanner’s capabilities and shared technology.

3D scanners are a niche within a niche, and not necessarily within the 3D printing niche either. 3D scanning is used in many fields, like game asset creation, texture assets, archaeology, prosthetics, and museum archiving; and the rise of 3D printing has created a small but growing demand in the form of reverse engineering automotive and various niche parts. However, because of PC requirements, the intensive and technical scan cleanup, and resurfacing in CAD programs, it remains a small niche; a niche currently being served by brands such as Creality with their CR-Scan line of 3D scanners, Revopoint’s Pop series, mini, and all-in-one MIRACO scanner, and SHINING3D’s Einstar prosumer-level 3D scanner.

Speculations in Bambu Lab’s own forums found FCC filings for a label and drawing of the scanner. The label shows a 60W-rated input, leading some to speculate a shared platform with SCANOLOGY’s 3DeVOK MT Gen2, a wired composite 3D scanner released in 2026, using both blue and IR lasers, and also has a rated input of 60W. The input rating doesn’t necessarily confirm that they share technology, but it does give a small hint of its potential capabilities, with the number of lasers and potentially a screen dictating the power requirements.

Considering the flat spot and the top of the handle on the FCC drawings, it looks like there may be a screen, possibly like the 3DeVOK MT Gen2. More importantly, the 60W rating with no hints of a battery on the label may mean this scanner will require a PC to operate. This is often a pain point, as you would either need a powerful laptop to bring while scanning, or use a really long USB cable to your PC. As for the price, the 3DeVOK MT Gen2 is officially priced at $8,299, which is a very high price point, further making it unlikely that they may share a platform if Bambu Lab wants to keep consumer-friendly pricing.

Following the release of TypeSafe's Jev, many AI players have launched competitors, and many similar open-source projects from the likes of Microsoft, OpenAI, and many more have since emerged. Yet Nandakishor Mukkunnoth, of ConvAI Innovations, said that he'd come up with the base notions for Jev's architecture over a year before. So who copied who?

As a quick recap, Jev and its clones are APIs driven by decision models, for use in your own code. You feed them input data like a customer's online shopping transactions, alongside questions. For example: "is the user looking for a return?" for a yes/no answer, and "Which item are they referring to?" with a multiple-choice answer. A Jev-like AI model will answer each of the questions or choices with a probability that can then be used in your own "if" statements. While the concept by itself isn't strictly new, this practical application is indeed novel.

The release made a good portion of the internet abuzz, as the seemingly simple concept is extremely useful and neatly sidesteps the usual problems with trying to coax an LLM into giving a direct answer. There's no token-by-token text generation, no conversations, no re-feeding of conversation history, no feeding it gobs of information for context, and no conversational hallucination — just direct data in the form of probabilities. It's really fast too, answering questions in parallel, and exceedingly cheap compared to standard LLMs.

Along with Jev, TypeSafe also released a brief description of its System One architecture. Only days later, Nandakishor Mukkunnoth, founder of ConvAI Innovations, explained in a blog post that he'd actually "designed the Jev architecture one year back." He referred to his arXiv paper on SalesRLAgent, describing how he created a model for probability estimation, published on March 30, 2025. Along with the paper, he published his model weights and dataset. He later followed up with a September paper that more closely aligns with how Jev operates.

In his write-up, Mukkunnoth expressed his frustration, describing how he got overlooked "because [his idea] was built for a vertical use case," meaning SalesRLAgent was made to fix one specific problem, while TypeSafe made Jev a general-purpose decision engine. Notably, the company released Jev as a complete, hosted product, with its own servers, API, documentation, developer kits, and naturally, pricing.

Nevertheless, he said he opted to not remain bitter about the development, and ultimately released the open-source Laya roughly the same day. Laya is essentially a Jev-style model and interface that you can run on your own hardware, complete with multi-language support. Likely adding to the confusion, both TypeSafe and Mukkunnoth called their models "System 1/One" types, likely as a reference to Daniel Kahneman's book, Thinking, Fast and Slow, which describes System 1 as a faster, emotional mode of thought, whereas System 2 refers to slower, more logical thought.

Regardless, there was no stopping the hype generated by this new use case for AI, so players in this space did what they do best: copied the concept and rolled out their own services. In the space of only a few weeks after Jev was released, the world saw Microsoft Decision, OpenAI Decisions API, and Fastino Glide. Both Cloudflare Clef and Perplexity Decider arrived with open weights, meaning you can run them on your own gear, assuming it's up to the task. Over on the open-source aisle, there's Amazon's Strands Decider 2B, Kev, Von, Jeff, jevlike, SemIf, OpenJev, NanoJev, Ollaya, and many others.

Why so many? Well, because most of these projects, including the commercial ones, share the same root: taking an existing lightweight model, usually always a variant of Alibaba's open-source Qwen, and adding the extra layers that shape the input, output, and decision-making procedure. Mukkunnoth's Laya is based on encoder-only models from the Bert family, rather than an LLM like Qwen. And yet it's not too hard to imagine that many folks might have cribbed at least some notes from his work, given how quickly the alternatives materialized.

Over recent weeks, we've seen the release of DLSS 5 Neural Rendering in NBA 2K27, followed by its porting to older GPU generations, and the unlocking of DLSS Multi Frame Generation (MFG) for older graphics cards. But how did all of that happen, and who are the people in the modding community unlocking features that Nvidia itself has locked off from users of anything but its latest Blackwell-based GPUs? We sit down with modders Dashdogy and Uncle Burrito to understand how, and why, the modding community has been breaking down Nvidia's software-based locks.

In 2025, during the release of the RTX 5000 series graphics cards, one Australian student was watching a Digital Foundry interview with Nvidia engineers, where the team was showing off Multi Frame Generation (MFG), a feature locked to Blackwell GPUs. During the podcast, the idea of MFG running on older RTX 4000 series hardware was floated, but the feature was never released for Ada Lovelace hardware. “Every few months, I would do a Google search to see if it ever happened or not,” said Dashdogy, a Physics Major studying Mathematics and Space Science.

“A few weeks ago now, the perfect storm arrived. Mid-semester break had just started, and I did the same Google search as I always do. But thought, maybe I’ll look into it. How hard could it be?”

One AWS instance, and a week of late nights later, he unlocked “true” MFG on Ada Lovelace hardware, a feat previously believed to be impossible due to incompatible instructions and a black screen that blocked the progress of modders before them. We’ve tested the mod extensively, and the results stand out. Multi Frame Generation has unofficially arrived for non-Blackwell hardware.

Dashdogy isn’t the only modder that’s been hard at work unlocking features for older-gen GPUs. Several weeks ago, when DLSS5’s Neural Rendering DLL first found its way onto the internet, RTX Remix modder Uncle Burrito set their sights directly on it. “I had no idea of telling [if running DLSS 5 on Ada] was even possible,” they said. Given the previous performance claims of requiring multiple RTX 5090s to run on its initial reveal, Uncle Burrito knew DLSS 5 would be computationally expensive, but that didn’t stop him from trying to get into the DLL itself.

“Once I reverse-engineered it, with the help of Claude, it became obvious that this was possible on Ada. Not only was most of the code compatible, but to me, it looks like Ada support was simply left behind as a work in progress, not as a hard limit.”

And so, less than a day after the DLL had been released in an early access version of NBA 2K27, Uncle Burrito had successfully ported the technology to Ada hardware. In the weeks since the release of Uncle Burrito’s initial unlock for DLSS 5 NR on Ada GPUs, Nvidia has clarified that Neural Rendering would indeed be supported by RTX 4000 series GPUs, lending credence to the idea that implementation on Ada GPUs was merely unfinished in the initial shipping versions of the DLSS 5 DLL.

These two foundational mods by Dashdogy and Uncle Burrito now serve as the baseline for endless numbers of forks and integrations of both Neural Rendering and MFG for older hardware, which have now allowed for ports all the way back to 2018’s Turing architecture, and in DLSS 5 NR’s case, ports to AMD hardware. It’s now as simple as using one of many tools to click-and-install both into hundreds of games.

Unlocking MFG (Dashdogy)

Dashdogy’s experience in modding spans years, having created Stellaris mods while still in High School, making compatibility scripts to patch multiple mods together. But porting DLSS MFG to Ada devices was a different beast entirely. Blackwell and Ada use entirely different ISAs, despite their software similarities. “When this [running Blackwell instructions on Ada] happens, the frames will generate, but the GPU graphs an error and returns a black screen,” he explains.

Underpinning Nvidia’s implementations of DLSS in shipping titles are two pieces of software: a package named Streamline, which usually includes a suite of DLSS software, and is a universal translator that allows games to run various upscaling technologies like DLSS. Used in tandem with Streamline is a Neural Graphics Framework (NGX), Nvidia’s proprietary software that underpins its AI-powered efforts like Super Resolution and Frame Generation. As a game calls for tools, NGX cooks the computation, and Streamline serves them to a given game’s engine.

As Dashdogy explored how to make MFG compatible with Ada, the modder targeted Streamline and NGX directly. “I specifically spoof the Streamline and NGX calls in memory that define how many frames the GPU is allowed to generate.” This approach allowed an Ada-based GPU to think it was allowed to generate more frames than it ordinarily would. “It’s a pretty simple interception, and on 40-series turns 1 into a 5. Now the GPU knows ‘I am a 4080 and I’m allowed to generate five frames,'" which successfully swerved the black frame issue that other earlier modders encountered, thereby unlocking higher frame generation multipliers.

Dashdogy quickly packaged things up as a Cyberpunk 2077 mod, and shipped it off to Nexus Mods. This was the canary in the coal mine for a more mature integration, but things weren’t quite perfect yet. Dashdogy and other modders reported a problem — when using anything more than 2X MFG in Cyberpunk 2077 on Ada, things felt sluggish. Latency wasn’t great, and with the help of another modder, they believed that this was the work of the fabled “Hardware Flip Metering,” which smooths out MFG's outputs, and is a primary reason Nvidia offers as the reason the feature doesn’t work on older graphics cards.

Armed with a cloud instance that uses an RTX 6000 Pro Blackwell GPU, Dashdogy quickly went to work improving the MFG mod. “I conducted a kernel dump whilst the GPU was running MFG.” Dashdogy was also equipped with OpenAI’s Daybreak Blue AI model, a modified version of GPT 5.6-Sol with safeguards adjusted to allow for defensive cybersecurity tasks and vulnerability discovery. Using the model and his know-how, he analyzed the RTX 6000 Pro’s kernel dump to check where things might be going wrong for his MFG mod, directly comparing it to his native RTX 4000 Series integration.

“For 6X frame generation, the GPU will render two real frames, then generate five frames and place them between those two real frames,” he told Tom’s Hardware Premium. Without copying this integration, frame pacing in his existing solution felt odd and disjointed.

“The 40-series-generated frames were all compacted around the middle of the two-frame interval. As you can see [in the image above], what we would expect, and what I measured from the [RTX Pro 6000 Blackwell], was five frames, neatly positioned at separate intervals. However, the 40-series GPU was forcing all of these around the same interval as 2X frame gen would put its one single frame.”

This caused the frame pacing of the MFG frames in the initial mod to feel sluggish, weird, and have poor responsiveness, as frame pacing is crucial in making a title feel smooth, especially when any frame generation tool is involved. “I discovered that the 40-series kernel responsible for motion processing was hardcoded to output a midpoint scaling for 2x only,” Dashdogy described. “With multiple generated frames, that compressed their represented motion toward the middle. With the fix, they spread out much more like the Blackwell reference.”

“The mod can work anywhere normal frame generation is implemented in any game,” Dashdogy told us, with additional telemetry for users to see exactly what’s changing. “The kernel is the same for both 40-series and 50-series; [it’s] just architecture-specific functionality [which blocks MFG on Ada]. 50-series has a number of Blackwell-specific optimizations that I’ve backported as well, and they contribute to better latency overall.”

The modder explains that the frame pacing fix was the most difficult part of the now-universal MFG port to Ada. But after its release, it now sits as a loadable ASI in a game’s directory and controls up to 6X frame generation in supported titles. The project has since been forked by other authors, which plugs the logic Dashdogy wrote into ReShade, a popular graphics mod tool.

Unlocking DLSS 5 NR (Uncle Burrito)

“I’ve been working with 3D art and graphics for many years now,” explains Uncle Burrito, a graphics enthusiast who implemented Path Tracing into Need For Speed Underground 2 using RTX Remix several years ago. “Over the years, I’ve stayed in the RTX Remix community to learn a lot more about real-time rendering and the techniques used for it.”

After hanging out in Nvidia’s RTX Remix Discord channel, news of the emergence of DLSS 5’s nvngX_dlssnr.dll spread like wildfire. According to Uncle Burrito, mods quickly clamped down on discussion of the DLL, and modders flocked to private channels and alternative servers, such as the RenoDX Discord server, to discuss development and integration. The DLL itself was written specifically for Blackwell, but the Ada architecture shares the ability to read FP8 instructions, which is what the DLL uses to load DLSS 5 Neural Rendering’s model weights.

Using that as a starting point, Uncle Burrito quickly went to work. “The model itself is just weights. These weights need code to be executed. The code was only written for Blackwell. CUDA binaries, right?” he explained. But despite this, and the aforementioned difference in ISAs between Blackwell and Ada, certain instructions could not be read by the humbler RTX 4000 series GPUs.

“Four of the 15 CUDA binaries [contained within nvngx_dlssnr.dll] would not run on Ada.” But this wasn’t an impossible task, as Uncle Burrito previously explained. The integration for Ada appeared unfinished and therefore, not entirely impossible. “I simply needed to patch the replacement compiled binaries”, meaning that it only took patching four affected CUDA binaries to get things up and running for RTX 4000 series graphics cards, Uncle Burrito told Tom’s Hardware Premium.

Uncle Burrito, alongside Ghidra, a reverse engineering tool, and an instance of Claude Code, set out to recompile the incompatible binaries to design a patch, but fell into a roadblock made by Claude itself. “I’m not too familiar with reverse engineering myself [...] Claude made the decision to use the incorrect version of the CUDA SDK to compile the replacement [binaries].” And so, the patched DLL ran, but instead output a black screen. “I could see the NR debug banner, and it did affect my framerate, but the output was completely black.”

“This is one of the many pitfalls of vibe coding,” Uncle Burrito said. “You can’t make anything good if you don’t understand what you’re working on. Usually, I don’t give the model any room to gaslight or make a wrong decision. If you don’t know what you’re doing, then don’t expect miracles.”

After realizing the mistake and recompiling with the correct CUDA SDK, the results were quickly posted to the RenoDX Discord server. “Ada performance is about as good as it can get. It has native FP8 support, so the hardware is doing its best. The rest can be attributed to simply not [having] enough horsepower in the chips.”

The simplicity of the patch might appear to be surprising, but the DLL leans on the same information that’s standardized between games and platforms, similar to how Streamline works in most game engines. “Motion vectors and depth buffer are [two] of the few things in graphics programming that we’ve standardized. Almost every modern game produces motion vectors, and rasterization isn’t possible without a depth/z buffer,” Uncle Burrito told us. Therefore, the DLL becomes a drop-in replacement for the officially distributed one, which unlocks the functionality on Ada.

Uncle Burrito’s methodologies were since picked up by RenoDX’s ShortFuse, who then worked on porting the DLSS 5 NR DLL to Ampere and Turing generation graphics cards. That porting work is more involved, since it also includes the translation of the model to be read by FP16 instructions. Following the release of Uncle Burrito’s work, a new DLL has emerged, with universal compatibility between Turing, Ampere, and Ada generations.

Unblocking the software lockouts

Between the MFG unlocker from Dashdogy and the patched Neural Rendering DLL created by Uncle Burrito, the community-made mods both unlock functionality that would not have come to older-generation cards or would have otherwise been added at a later date. According to Dashdogy, “40-series has no excuse” when it comes to support for Multi Frame Generation. “It’s a very small change that allows [the mod] to work,” noting that additional work is being done to recompile things for Turing and Ampere, with the caveat that latency and overheads get higher the further you go back.

“It always comes down to performance,” Uncle Burrito said. “It’s fair for [Nvidia] to not include Ada until they can get the optimization part sorted.” The modder further adds that the situation can be read in both ways, as a method for Nvidia to sell more RTX 5000 series graphics cards, and to have more time to optimize Neural Rendering for older RTX 4000 series GPUs.

Everyone wants to make the most out of their available hardware, especially at a time when consumer graphics pricing has firmly rocketed past the moon, with RTX 5090 GPUs now approaching north of $9,000. “I personally think [the MFG mod] is really important in the current market,” Dashdogy adds. “... many are just getting priced out of the new generation entirely, so giving people the ability to hang on to their GPUs for a little bit longer is going to help a lot of people stay invigorated and connected to the hobby.”

If a single Australian student can unlock DLSS MFG for older GPUs, Nvidia’s claims of hardware exclusivity appear less like a technical limitation and more like artificial lockout. For those unafraid to modify a few simple files within a game, those features are all readily available, albeit unofficially. There’s an irony in how both MFG and Neural Rendering were ported to older GPUs — the development of both mods relied on cutting-edge AI models — powered by the same ecosystem that’s driving Nvidia’s earnings. Now, the very same AI revolution Nvidia champions is being used to tear down its own walled garden.

Brazilian developer RafaelNGP has created his own Homebrew called PSBox Cloud Gaming on his jailbroken PS5 and released it for download on GitHub. The mod, created in part using Claude, allows Xbox Cloud Gaming to run natively on a PS5, with up to 4 DualSense controllers mapped to Xbox for compatibility.

The lines between consoles and PC have been blurring lately, and even more so for the PS5, with jailbreak mods allowing for many new capabilities it was never intended for. We recently covered a story about the original Xbox being emulated on a jailbroken PS5, but a more modern and usable mod is this natively running Xbox Cloud Gaming mod. Gone are the days of switching to your Xbox or PC to play xCloud; just run it on your PS5 — that's what RafaelNGP thought to himself before making PSBox Cloud Gaming.

Rafael explains how easy it is to get it running, with just a .zip file download from their GitHub, extraction to a specific folder, waiting for a Homebrew loader to mount the “game,” then launch and sign in as usual. Users are able to sign in using their phone through a code on the TV. It currently supports a 1080p60 stream, but can be upscaled to 4K using the PS5’s GPU with AMD FSR 1 or Anime4K upscalers. The application is still not perfect, with testers reporting video issues such as macroblocking, pink artifacts, and vibration issues on the DualSense controllers, while others are thrilled and having a good experience.

As if emulating the original Xbox and playing xCloud on a PS5 weren’t enough, a comment under the Reddit post asked whether they could use local Xbox Remote Play on it, intending to stream games from an Xbox they already have to the PS5. Rafael said it didn’t work yet, but promptly created an update days later enabling Xbox Remote Play.

The PS5’s library of exclusives may be lackluster, but it seems that the PS5 has more to offer than its own games outside of what Sony intends for it, thanks to the jailbreaking community.

When GlobalFoundries abandoned development of leading-edge nodes in 2018, it also canceled the development of its 7nm-class FinFET fabrication technology that it co-developed with IBM. Almost exactly eight years later, GlobalFoundries is back with a 7nm-class manufacturing process, only this time the node relies on planar transistors and fully-depleted silicon-on-insulator (FD-SOI). It is aimed at automotive, edge AI, industrial, robotics, sensors, and other devices that prioritize low power consumption, high integration, and cost efficiency over maximum performance.

"We are delighted that GlobalFoundries has announced its next-generation 'single-digit FD-SOI; node, building on technology that CEA-Leti has been advancing for decades," said Sébastien Dauvé, chief executive of CEA Leti. "Through the FAMES pilot line, CEA-Leti continues to shape the future European roadmap for FD-SOI and works every day to promote its adoption in a wide range of applications."

FDX Fusion enters the scene

The new fabrication technology from GlobalFoundries is called FDX Fusion, and it promises 7nm-class 'digital performance' (an ambiguous claim; we will try to interpret it later) and more than twice the transistor density of its original 22FDX process introduced circa 2015. To achieve its target goals, the first generation of FDX Fusion will combine innovations in SOI substrates, transistor structures, and back-end interconnects, though keep in mind that GF has not disclosed transistor dimensions, contacted gate pitch, minimum metal pitch, or actual transistor density. GF plans to launch production of chips on FDX Fusion at its Dresden, Germany, facility in 2028, which will mark its return to the development of substantially more advanced FD-SOI fabrication processes after years of efforts to enhance its existing 22nm-class platform.

In addition to improved 'digital performance,' FDX Fusion will support RF transistors with fT/fmax of up to 0.5 THz, analog and mixed-signal circuitry, embedded nonvolatile memory, and in-memory computing capabilities. The combination is intended to enable highly integrated chips that can process information from sensors, execute AI inference workloads, control external devices, and communicate wirelessly without the need for numerous separate ICs. GF also intends to provide processor IP based on MIPS, ARC, and RISC-V architectures to accelerate the development of such products.

That being said, the main selling point of FDX Fusion is not necessarily its 7nm-class 'digital performance' and high-performance processor IP, but rather its ability to combine relatively powerful digital logic with RF, analog and mixed-signal circuitry, embedded nonvolatile memory, and in-memory computing capabilities on a single chip. This combination — which is why GloFo calls the process technology FDX Fusion — could enable highly integrated SoCs that would otherwise require multiple chips manufactured on different process technologies, which means additional tapeout costs as well as power consumption.

GlobalFoundries said it plans to deliver initial demo silicon for customer evaluation in early 2027, followed by the first process design kit (PDK) in mid-2027. The company is already collaborating with several customers on the technology, although it has not identified specific products or committed production volumes. Specifically, GF mentioned in its press release that BMW, Bosch, Infineon, NXP, Siemens, and Tesla have expressed interest in FDX Fusion, though only Infineon specifically confirmed collaboration on future 7nm-class technologies for radar and wireless communications.

Significant development

The GlobalFoundries announcement represents a significant development for GF's FD-SOI roadmap. The company introduced 22FDX in 2015 and announced its 12FDX successor in 2016, which promised performance comparable to 10nm FinFET, full-node density improvements, and up to 50% lower power consumption. Initial 12FDX customer tape-outs were expected in 2019, but the technology has never been adopted for commercial products. Instead, GF focused on enhancements to 22FDX and eventually the introduction of 22FDX+ (around the time when Samsung unveiled its 18FDS+), with additional capabilities for RF, embedded memory, and low-power applications. Interestingly, 12FDX was still a part of GF's investor roadmap in 2022.

FDX Fusion could therefore represent the realization of GF's original ambitions to scale FD-SOI beyond 22nm-class, although the company has not explained whether the new technology incorporates developments from its earlier 12FDX program. Meanwhile, CEA-Leti, which has conducted research into advanced FD-SOI technologies for years, describes FDX Fusion as a single-digit FD-SOI node. Nonetheless, GF's claim of 7nm-class 'digital performance' does not necessarily imply comparable transistor dimensions or integration density.

From an industry perspective, FDX Fusion could provide an alternative to advanced FinFET and perhaps even gate-all-around processes for applications that require reasonably powerful digital logic alongside RF, analog, and embedded memory. Such integration could reduce system complexity and power consumption, particularly in edge AI devices where energy efficiency and real-time responsiveness are critical.

Perhaps more importantly, the technology could give European semiconductor developers access to a more advanced locally manufactured process without dependence on leading-edge foundries in Asia or the U.S.

Questions remain

However, the commercial success of FDX Fusion will depend on its actual performance, density, production costs, and the availability of a competitive design ecosystem, the latter arguably being the hardest part given the lack of any comments from leading electronic design automation (EDA) and IP developers.

When GlobalFoundries claims 2X 'digital performance' comparable to that of 7nm-class technologies, it doesn't reveal whether it means transistor switching speed, standard cell performance, achievable operating frequency, or something else. In addition, the company promises more than twice the logic density of its first-generation FDX technology, although the firm does not reveal any actual numbers. Consequently, it is unclear how FDX Fusion will compare with established 7nm-class FinFET technologies, which offer mature defect density and yields, plenty of supply, an established design ecosystem, and predictable pricing among other things, in terms of transistor density, performance, power consumption, and production costs. While CEA-Leti's comment seems promising, actual numbers are always better.

The very fact that GF's FDX Fusion planned 2028 introduction will come roughly nine years after the originally anticipated first 12FDX tape-outs illustrates significant technological and/or financial difficulties associated with the development of FD-SOI beyond the 22nm generation. So, while GlobalFoundries' FDX Fusion initiative certainly looks promising, it remains to be seen how that is going to play out for the contract chipmaker and its clients.

For now, the lineup of supporters from the automotive and industrial sectors — BMW, Bosch, Infineon, NXP, Siemens, and Tesla — certainly looks promising. But what about other applications? While established semiconductor companies such as Infineon and NXP already possess extensive processor IP portfolios, smaller fabless developers could benefit from GF’s MIPS and ARC processor cores, RISC-V expertise, and custom chip design capabilities, which could substantially reduce the cost and complexity of developing specialized SoCs. Still, to attract a broader range of chip developers, GlobalFoundries will need a mature ecosystem of EDA tools, standard-cell libraries, memory compilers, interface IP, and other silicon-proven building blocks. These are the things that GlobalFoundries has not touched upon in its press release.

Just five years after bringing its Software Guard Extensions (SGX) technology to its mainstream server platform, Intel on Friday announced plans to discontinue its support after its upcoming Xeon 'Diamond Rapids' CPUs and concentrate its confidential computing efforts on Trust Domain Extensions (TDX). The company will continue to support existing SGX-enabled platforms into the early 2030s, but at the same time will expand TDX capabilities to address emerging requirements of cloud computing, enterprise workloads, and agentic AI applications.

Without a doubt, data sovereignty requirements are an increasingly important factor as organizations seek to protect sensitive information from unauthorized access even when they process it on infrastructure operated by third parties. Although both Intel SGX and TDX are designed to protect sensitive information while it is being processed, they use substantially different approaches.

SGX provides hardware-protected enclaves within applications to isolate selected code and data from other software, including the operating system and hypervisor. By contrast, TDX isolates entire virtual machines from the underlying host environment, including the hypervisor and other VMs. While SGX requires developers to design or modify applications to use protected enclaves, TDX can protect existing workloads inside confidential VMs without extensive changes to individual applications, something that makes TDX particularly attractive to cloud service providers that operate large numbers of virtual machines.

While both SGX and TDX have faced numerous security vulnerabilities over the years, including side-channel attacks, privilege-escalation flaws, and attacks against their attestation mechanisms, Intel does not cite security concerns as a reason for its decision to discontinue SGX.

Intel's decision to phase out SGX reflects the industry's preference for VM-level isolation over application-specific enclaves. According to Intel, TDX provides scalability, ease of deployment, and the operational model required for widespread adoption of confidential computing. Although SGX enabled confidential computing in the data center and continues to serve security-conscious customers, Intel believes future demand will favor TDX. Diamond Rapids will therefore be the final Xeon generation to support SGX, which gives customers several years to validate alternative solutions based on TDX and migrate existing applications. Intel will continue to provide security updates and support for SGX-enabled platforms into the early 2030s, so its customers will have plenty of time to adopt TDX for new deployments.

Meanwhile, Intel plans to expand TDX capabilities with additional security technologies. These include Intel TDX Connect, which is designed to enable trusted I/O, as well as post-quantum cryptography and enhanced attestation mechanisms. Trusted I/O is particularly important for workloads that communicate with external devices, as protection of computations inside a virtual machine does not necessarily extend to data transferred between the VM and accelerators or other peripherals (read, CXL expanders, though Intel has not stated this for sure). Improved attestation will help organizations verify the integrity of protected environments, while post-quantum cryptography will help address future security threats. Meanwhile, Intel has not disclosed specific availability dates for these enhancements.

One important driver behind Intel's confidential computing strategy seems to be accelerated adoption of agentic AI. Unlike conventional applications, autonomous agents may access sensitive enterprise information, execute operations across multiple systems, and interact with other agents. Intel expects many such workloads to run on CPUs, and here TDX may offer practical advantages for agentic AI applications. Unlike SGX, TDX can protect entire agent execution environments without extensive software modifications and enable multiple agents to operate in separate, hardware-isolated VMs on shared infrastructure. For GPU-accelerated AI workloads, Intel works with Nvidia to coordinate confidential computing technologies across CPUs and GPUs to extend protection to sensitive data and AI models throughout the processing pipeline (which is obviously broader than Intel's development of custom Xeon CPUs for Nvidia).

Intel TDX is already available through major cloud providers, including Alibaba Cloud, Google Cloud, IBM Cloud, Microsoft Azure, and Volcano Cloud. Meanwhile, Red Hat, Canonical, and VMware are adding TDX support to their software platforms to enable adoption in private clouds and enterprise environments.

Frore Systems has introduced its bespoke LiquidJet Diamond liquid-cooling coldplate series that uses a diamond surface combined with a multi-stage 3D short-loop jet-channel microstructure to address precise hotspots on next-generation AI accelerators, such as AMD's Instinct MI400 and MI500-series, Nvidia's Rubin, and beyond. The company claims its new coldplates can handle hotspots with power densities reaching 770 W/cm², reduce GPU temperatures by up to 22C compared with conventional coldplates, and improve AI token throughput per watt by as much as 35%.

LiquidJet Diamond combines the expertise it used for its original LiquidJet coldplate product and the LiquidJet Nexus bespoke coldplate for Nvidia Blackwell and Nvidia Rubin-based servers. Unlike Nexus, which integrates multiple coldplates into a large cooling assembly for several processors, LiquidJet Diamond is an individual GPU coldplate, albeit a bespoke one.

From an internal technology perspective, Frore’s coldplates employ a three-dimensional, ultra-short-loop, multi-stage architecture with coolant channels customized for the power distribution of a specific processor. Meanwhile, the key innovation in LiquidJet Diamond is an additional heat spreader integrated into the bottom of the coldplate. This spreader incorporates diamond wafers positioned directly above the GPU’s hotspots to distribute heat more efficiently before it reaches the liquid-cooling structure. Diamond (carbon) has exceptionally high thermal conductivity, which can exceed 20 W/cm·K, compared with approximately 4 W/cm·K for copper. According to Frore, the addition of diamond heat spreaders allows LiquidJet Diamond to handle hotspots with power densities of up to 770 W/cm², compared with approximately 600 W/cm² for the original LiquidJet. However, the company has not disclosed how the diamond wafers are manufactured or integrated into the coldplate.

According to Frore, its original LiquidJet coldplate reduces GPU temperatures by approximately 12C compared with conventional skived coldplates (based on its simulation model), which translates into a 25% improvement in AI tokens per watt, according to the company’s estimates. Meanwhile, a custom Liquid Diamond heatspreader promises to further reduce hotspot temperatures by up to 10°C, while the complete LiquidJet Diamond solution provides a 16C – 22C reduction in GPU temperatures and improves token efficiency by 30%–35%, Frore claims. The company also expects 75% higher heat-transfer efficiency and over 150% higher maximum hotspot power density than conventional cold plates based on its models.

Frore plans to demonstrate LiquidJet Diamond at the OCP Global Summit on October 12 – 16, where it will showcase cooling for Nvidia's 2,300W Rubin accelerator and hotspots reaching 770 W/cm². However, the company has not disclosed whether the demonstration involves production GPUs or some type of thermal test vehicle.

OLED or LCD? This is a question many monitor shoppers ask themselves. When you consider the pros and cons of each, there isn’t a clear winner. OLED has better image quality thanks to its extreme contrast. But LCDs are brighter and less expensive. So, what if you could move the needle further towards one of the best OLED gaming monitors?

Gigabyte has done this with the GO27Q24G. This 27-inch QHD 240 Hz OLED delivers brightness over 1,300 nits for a shockingly low price of just $350 as I write this. Cutting corners? That’s a hard nope. You get 240 Hz, FHD gaming modes, wide gamut color, Adaptive-Sync, gaming aids, HDR10 and premium build quality. Let’s take a look.

Gigabyte GO27Q24G Specs

The GO27Q24G saves some cost by omitting USB ports, internal speakers, and LED lighting. But there is nothing else critical missing from this impressive display to meet the low price point. The refresh rate is 240 Hz with Adaptive-Sync and certified G-Sync and FreeSync operation. There’s an anti-flicker option to prevent image pumping during rapid frame rate transitions. And you can turn on black frame insertion to keep motion blur at bay when frame rates drop. Video processing gives nothing away to more expensive monitors.

There’s plenty of color and contrast from the WOLED panel. WOLED, or white OLED, achieves color with filters rather than RGB stripes or Quantum Dots. There’s a definite cost saving and you won’t quite get the huge color gamuts found in higher-priced displays. But you do get 96% of DCI-P3 by my measurements, and that’s a colorful image. Accuracy is there as well, with solid results in my tests that you can read about on pages four and five.

The panel’s high brightness comes from a Micro Lens Array, which is essentially a textured layer over the pixels that amplifies light. Each pixel has around 5,000 of these lenses over it, and given the numbers I saw in testing, it clearly works. This approach also reduces power consumption and improves viewing angles.

The GO27Q24G’s screen is glossy but includes an optical coating that deepens black levels and cuts reflections. There’s a lot of metal used here, both behind the panel and in the stand, which is one of the nicest bits I’ve seen in a while. You would never imagine the price tag being so low.

In addition to pro-level video processing, there are gaming aids like reticles, timers and a frame counter. OLED care options are plentiful, with pixel orbiting, logo and perimeter protection, and screen refresh. Variable brightness is available too, which helps bump up the impact of small highlights to as much as 1,300 nits.

If you’ve been fancying an OLED but didn’t want to spend $600 or more on a 27-inch monitor, the GO27Q24G is a compelling option.

Assembly and Accessories

The GO27Q24G comes packed in crumbly foam in three parts. I was impressed by the stand, which is all-metal and super solid. Everything assembles tool-free. The accessory bundle includes an external power supply and a DisplayPort cable. If you want to use an arm, there’s a 100mm VESA mount, but you’ll need to source your own fasteners.\

Product 360

The GO27Q24G’s styling and build is minimalist in all the right ways. From the front, you only see the image surrounded by a very narrow flush bezel of 8-11 millimeters. There is no plastic trim anywhere in sight and no logos either. Even the power LED is tucked well underneath where you won’t be distracted.

The base is a stamped steel plate with a gray satin finish. Its footprint is small, but with rubber feet and an ideal shape, it’s very stable. The upright is all-metal with very smooth movements and the same gray satin finish. The GO27Q24G includes full ergonomics with 5/21 degrees of tilt, 15 degrees swivel, a 90-degree portrait mode, and a 5.1-inch height range. A small cable clip is included to keep your wires tidy.

The only plastic used is in the back, where a small component bulge is trimmed with generous ventilation and a small Gigabyte logo. There’s a joystick flanked by two buttons and the input panel. It features two HDMI 2.1 ports, one DisplayPort 1.4 with DSC, and a USB-C input which has 15 watts of power. There are no additional USB ports or internal speakers, but you do get a 3.5mm headphone jack.

OSD Features

A single joystick controls the GO27Q24G’s OSD. Two flanking buttons toggle power and switch between aspect ratio modes.

The OSD screen is well appointed with information. Resolution and refresh numbers are at the top while other parameters are at the bottom. You can quickly check the active input, SDR/HDR status, picture mode, brightness level, gamma setting, and color temp mode.

The GO27Q24G’s Gaming menu has Ultra Clear, which is Gigabyte’s term for black frame insertion. It effectively eliminates motion blur below 120 Hz. It also cuts brightness by around 40%, but it’s a great solution for slower PCs and consoles that operate at low frame rates.

The Picture menu offers 10 picture modes, each with its own set of calibration options. Standard works well and leaves all controls available. There are gamma presets and color temps along with gamut selections. For sRGB, use the sRGB picture mode. The GO27Q24G has variable brightness, which you’d think would be here, but it isn’t. Read on to find it.

The GO27Q24G includes PIP and PBP options with full control of the PIP window’s size and location. You can also program the four joystick directions for quick access to commonly used settings.

To find OLED Care, press the joystick and click left. There are many bits here, like pixel shift, cleaning routines that you can schedule, logo and corner dimming, and APL Stabilize. What is that, you ask? It’s the variable brightness option, which should be in the Picture menu. It has three levels which are termed counterintuitively. You’d think Low means the least stable, as in the most aggressive dimming. Nope, it’s effectively the off button. If you want constant brightness, choose that. High is great for HDR and watching SDR video. With it, you get very bright highlights and deep blacks for an impactful image.

Press the joystick and click right for the Game Assist menu. It has crosshairs and the Tactical Switch. This is fancy-speak for the resolution modes. You can switch on the fly to FHD either full screen or in a 24-inch window. I recommend the latter because it pixel-maps 1:1, thereby avoiding the softness that comes with displaying FHD graphics on a QHD screen. You get black borders, but you can position the picture at the top, bottom, or center of the screen. The switch itself is the button on the right side of the joystick. Don’t press the left one unless you want to turn off the GO27Q24G.

Gigabyte GO27Q24G Calibration Settings

In Standard mode, the GO27Q24G measures OK out of the box but leaves room for improvement. Grayscale is a tad warm, and gamma is too dark, which makes the picture less lively. With a few tweaks to the RGB sliders and a change of gamma preset from 2.2 to 2.0, the picture is greatly improved. Color gamut coverage is nearly 100% of DCI-P3, so you can see a vivid picture in SDR or HDR mode. If you want sRGB, choose that mode from the 10 presets. It has only a brightness control available. My recommended settings are below.

For HDR signals, there are five specific modes. To get the brightest possible picture, choose Peak 1300. It has a lot of impact, but for the most accurate luminance tracking, HDR is the way to go. You can read more about this on page five.

Gaming and Hands-on

You’ll see in the upcoming tests that the GO27Q24G delivers more brightness than any other OLED in its class. But does that translate to gaming goodness? I’m going to say yes. Because it’s one of the most precise monitors I’ve ever played on. Qualifier: you’ll need to keep the frame rate above 200fps. But that’s true of any OLED, regardless of resolution. I had no problem with that thanks to a GeForce RTX 4090. And when I say precision, I mean that I could pretty much not miss. The firing accuracy I enjoyed made me a bit overconfident, to the point where I was wading into hordes of enemies rather than taking my time picking them off one by one. I can’t promise that the GO27Q24G will make you a better player, but it is an absolute weapon. Pro competitors will surely want to give it an audition.

Picture quality was superb thanks to its high brightness. I tried both HDR and Peak 1300 modes for Doom Eternal and picked the latter as my favorite. You can see the technical differences between them in my test on page five. Quick spoiler: Peak 1300 is much brighter, almost double, in fact. And it has tremendous impact. The GO27Q24G has a bit less color volume than Quantum Dot or Tandem OLED monitors, but its extra light output makes up for that.

I noted from the get-go that the GO27Q24G has premium build quality. Though many OLEDs share this trait, I was particularly impressed with the all-metal stand. It’s sleek and slender, but supremely solid. The panel’s fulcrum is equally tight, which creates a monolithic package. And with nothing facing the viewer besides the screen, there are no distracting elements; no lights, no logos, no plastic trim, no nothing. I was amazed when I learned that the price is only $350.

If you want to make the GO27Q24G an everyday screen, it is more than up to the task. I recommend calibration, but it’s a simple matter. Just plug in my numbers above to see the same image I did. It has variable brightness, which you’ll find in the OLED Care menu. Choose Low for constant brightness and High for maximum contrast and impact. For those who need sRGB, that option is in the picture mode list. With 109ppi, there is enough pixel density to show a finely detailed and smooth image for things like Photoshop or YouTube.

Takeaway: The GO27Q24G is one of the best values I’ve seen in the OLED category. It offers all the performance of more expensive monitors while outpacing them in brightness. It also has the smoothness and response of the best gaming panels I’ve experienced. There are a few peripheral bits missing, like USB ports, LEDs, and internal speakers. But for the money, there isn’t a better 27-inch QHD OLED.

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The speediest OLEDs are found in the 27-inch QHD category, so I’ve included these in the GO27Q24G’s comparison group. They are Sony’s INZONE M10S II, ViewSonic’s VX2738-2K, Gigabyte’s MO27Q28G, Alienware’s AW2726DM, and Asus’ XG27AQWMG.

Pixel Response and Input Lag

Click here to read up on our pixel response and input lag testing procedures.

The Asus is omitted from the response results because it wasn’t tested with the Nvidia LDAT sensor. The remaining screens are all within a whisker of the GO27Q24G, with black-to-white transition times ranging from 0.16 to 0.24ms. That’s a difference you can’t see with the naked eye. I have yet to see an OLED look any more or less smooth than any other at a given frame rate. And clearly, higher refresh speeds don’t translate to faster response. Note that the 540 Hz Sony is 0.04ms slower than the 280 Hz MO27Q28G. The GO27Q24G is on par with most of the 240 Hz OLEDs I’ve tested.

In the lag test, the GO27Q24G takes the top spot by 0.5ms. Again, this is well below the range of human perception, but I can say unequivocally that it is one of the fastest QHD OLEDs I have reviewed. In practice, I never experienced anything but instant response to control inputs.

Test Takeaway: The GO27Q24G is one of the quickest and smoothest 240 Hz QHD OLEDs you can buy. It edges out monitors with higher refresh rates and higher prices. At rates greater than 200fps, there is no motion blur. For lower speeds, below 120fps, the Ultra Clear option works well. The price/performance ratio here is unmatched.

Viewing Angles

One wouldn’t think OLEDs needed help in the viewing angle department, but recent variants of the technology have shown some of the effects of polarization. The Micro Lens Array used in the GO27Q24G eliminates any artifacts caused by things like stacked layers or Quantum Dots. The side photo shows no change in color, brightness, or gamma. This is as good as a flat panel can get. The top view remains neutral in color but has a tad lower brightness and gamma.

Screen Uniformity

To learn how we measure screen uniformity, click here.

The chart looks a bit dramatic because the top four screens are below 3% in my uniformity test, but the GO27Q24G is still below the visible threshold of 10% with a 7.22% score. There are no hot spots to be seen in any neutral or colored field pattern.

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To read about our monitor tests in-depth, please check out Display Testing Explained: How We Test PC Monitors. We cover brightness and contrast testing on page two.

Uncalibrated – Maximum Backlight Level

Brightness is where the GO27Q24G’s rubber meets the road. It is brighter than just about any OLED I’ve reviewed, regardless of size, price, resolution, or technology. That 722 nits is from a 25% window pattern with APL Stabilize set to High. If you set it to Low, a window or full field measures 263 nits, still plenty of light if you want constant brightness. Black levels and contrast could not be measured.

After Calibration to 200 nits

Calibration changes nothing except the peak output level, which I set to 200 nits. I noted that if you want to switch between constant and variable brightness, the brightness slider’s value stays the same, meaning you must change it each time you switch. In both static and intra-image tests, black levels and contrast could not be measured.

Test Takeaway: The GO27Q24G has similar contrast to other OLEDs but much more brightness than almost every example I’ve reviewed. Its Micro Lens Array technology is a true game changer because it provides a lot of light for no extra cost and no downsides in performance. And you get better viewing angles too, win-win!

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The GO27Q24G looks OK out of the box but has room for improvement in its default Standard picture mode.

Grayscale and Gamma Tracking

Our grayscale and gamma tests use Calman calibration software from Portrait Displays. We describe our grayscale and gamma tests in detail here.

Default grayscale is a bit warm in tone, which is a forgivable error. Too much red won’t harm image quality as much as too much green or blue. Gamma is too dark as well, which makes the picture a bit flat.

To calibrate, I adjusted the RGB sliders and changed the gamma preset from 2.2 to 2.0. This made a significant improvement. The image is much more vivid and textural with these changes.

To use the sRGB gamut, choose that mode from the 10 presets. There is a gamut selector in the picture menu, but it only offers Adobe and DCI. That one should be left on Native. In sRGB, you get a brightness control, but other options are grayed out. This one has a warm grayscale and dark gamma as well.

Comparisons

4.03dE doesn’t seem like an impressive out-of-box result for the GO27Q24G, but it is only eclipsed by the Asus in this test. All the screens need some love to look their best. Fortunately, it is just a few clicks of the OSD joystick away to an excellent 0.81dE result and an on-par finish. None of the monitors have visible grayscale errors.

In the gamma comparison, the GO27Q24G sits well with a tight 0.09 range of values and a 1.36% deviation from the 2.2 reference. The gamma presets are a bit off the mark, but if you select 2.0, you get 2.17, not bad at all. This is solid performance.

Color Gamut Accuracy

Our color gamut and volume testing use Portrait Displays’ Calman software. For details on our color gamut testing and volume calculations, click here.

In the gamut test, the GO27Q24G is visually perfect out of the box. The chart shows a slight red oversaturation but no hue errors. Calibration tightens up the chart with all points on or close to their targets. This is excellent performance.

In the sRGB test, you can see the same red oversaturation, but no point is out of contact with its target box. This is solid performance.

Comparisons

With calibration, the GO27Q24G posts the best color result of the group. There are no visible errors from any of the screens, but a 1.04dE result is among the very best. Its only relative weakness is in color volume, which is lower than the others. They all use either Quantum Dots or Tandem RGB Stripe tech to expand the gamut. The GO27Q24G comes close to 100% of DCI-P3, so it is colorful, just not as much. Its 105% coverage of sRGB is from a little bonus red.

Test Takeaway: The GO27Q24G is a colorful and accurate monitor once calibrated. It has a little less color volume than its competition, but it is brighter and less expensive. And it covers almost 100% of DCI-P3. It comes out of the box looking a little dark, but a few tweaks are all that’s needed for a nice gain in performance and quality.

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Our HDR benchmarking uses Portrait Displays’ Calman software. To learn about our HDR testing, see our breakdown of how we test PC monitors.

The GO27Q24G supports HDR10 signals with an automatic switch where you’ll find five new picture modes. You also get some choices for brightness and other parameters.

HDR Brightness and Contrast

I’ve noted in past OLED monitor reviews that modes like “Peak 1000” are no brighter than modes called "Game” or “Cinema.” The GO27Q24G bucks this trend. The default mode is called HDR, and it will hit around 465 nits when measuring a 25% window. This earns it the HDR400 certification. But if you want to see the full potential, pick the Peak 1300 mode. That measured over 728 nits in my 25% window test. Gigabyte claims 1,300 nits for a 1.5% window, and there is no reason to doubt that. The GO27Q24G is BRIGHT. But there’s a catch; read on.

Grayscale, EOTF and Color

If you want the most accurate luminance tracking from the GO27Q24G’s HDR mode, choose the HDR preset. It’s a touch dark until the 40% step, then it tracks the reference almost perfectly. Grayscale is a tad warm but not to the point where it reduces image quality. This is excellent performance. The second chart shows the Peak 1300 mode. It has the same grayscale tracking, but the EOTF trace is a bit wonky. It keeps the same dark tone levels but pumps up midtones for more impact. It looks good to my eyes, but it isn’t strictly accurate. It is, however, the way to get the brightest HDR from the GO27Q24G.

In the color test, I observed the same result from the two modes, so I’m showing HDR here. There is general oversaturation in DCI-P3 and BT.2020 that is comparable to the other HDR OLEDs I’ve reviewed. Hue points are on target, so there are no visible errors. In the BT.2020 chart, color runs out at 75% red, 70% green, and 95% blue.

Test Takeaway: The GO27Q24G has the brightest HDR I’ve seen from an OLED display. In its Peak 1300 mode, it truly delivers 1,300 nits from the smallest highlights. This gives the picture real pop and dimension. Color is a bit short of the competition, but that difference is minor. Since hues are on target, there is no cause for complaint. The GO27Q24G is a superb HDR monitor.

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Desktop OLED gaming monitors have been with us for a few years now, and in that time, their prices have trickled down slowly at best. It’s a premium technology for sure, and for many users, the cost is just out of reach, until now. The Gigabyte GO27Q24G is $350 as I write this, and for that sum, you get a 27-inch OLED panel with 240 Hz, QHD resolution, HDR, Adaptive-Sync, and wide gamut color. What more do you need to know?

A few things have been sacrificed on the altar of value, like internal speakers, USB ports, and LED lighting. But the image and gaming experience are every bit the equal of monitors costing twice as much. The GO27Q24G’s Micro Lens Array delivers tremendous brightness, as much as 1,300 nits in HDR mode. It also has nearly perfect viewing angles. Color volume isn’t quite as large as panels with Quantum Dots or Tandem RGB Stripes, but you do get over 96% coverage of DCI-P3. I noted warm grayscale and dark gamma out of the box, but these issues were easily resolved with calibration.

When it comes to game performance, there is no complaint, only praise. A 240 Hz refresh rate delivers smooth motion and instant control response. The GO27Q24G has a tad less input lag than its nearest competitors. In practice, it’s a gaming weapon. And if you pair it with a console, there’s black frame insertion at 120 Hz to keep the action clear.

A quick search reveals similar monitors priced from $ 400 to $ 600. The GO27Q24G is a serious value. If OLED’s cost and lower brightness have put you off, Gigabyte has answered those concerns. Budget-conscious gamers should definitely check it out.

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AMD is bringing a new reference rack-scale design to the data center ecosystem with Helion. It’s a standardized, 21-inch rack reference design that will complement the Helios rack AMD revealed at OCP Global Summit last year. This year, we have Helion, which AMD says can house up to 32,768 Zen 6 cores in a CPU-only deployment using the dense 256-core design available with the EPYC ‘Venice’ 9996.

The rack design is standardized, based on the Open Compute Project’s ORv4 specification, which is slightly wider and taller than a standard IT rack. Helion is designed to support 44 OpenU trays, which are 21 inches wide and 48mm tall, slightly larger than a standard EA1-310 tray. AMD says the reference design supports both air-cooled and direct liquid-cooled deployments.

The design is also compliant with OCP’s DC-MHS (Data Center Modular Hardware System) standard. MHS is designed to bring “interoperability between key elements of data center, edge, and enterprise infrastructure,” according to OCP.

Although AMD has renders of the design you can see in the presentation below, it won’t actually sell racks. This is a reference design that AMD is contributing to OCP, and OEMs and ODMs will actually bring that design to market. AMD didn’t share partners supporting Helion during a pre-briefing with the press. The company says CEO Lisa Su will announce partners during the lead keynote at the OCP Global Summit later today.

AMD also didn’t share deployment partners, though it suggested that Helios customers will also deploy Helion racks.

Unlike Helios, which is built for AI training and inference, Helion is a more flexible rack solution primarily focused on CPUs. In a CPU-only deployment, the design can hold up to 128 EPYC 9996 CPUs, bringing that impressive 32,768 core count per rack. This configuration would likely look something like an agentic AI sandbox system, which is then connected to an inference system.

This model for personal AI agents is in use today, both in Meta’s Muse and OpenAI Dots. Each user has a sandbox with a slice of compute from the host system, with the backbone of an inference server. Some workloads are handled on those CPU-only servers, such as building software, but the heavy-duty AI inference happens elsewhere.

Presumably, this is the model AMD is aiming at with Helion as hyperscalers build out CPU capacity on the back of agentic AI. However, the design is flexible, supporting up to 16 MI350P GPUs and 102 Tbps of networking, though at the cost of CPU capacity. This hybrid configuration is targeted at enterprises, says AMD, giving them an all-in-one rack for data management, networking, and AI usage.

AMD says the Helion rack will be available starting in the first half of 2027, likely riding the wave of Zen 6 deployments that are expected to start ramping up later this year.

Full AMD OCP 2026 presentation

In its latest industry report, TrendForce has projected that global notebook shipments could witness a decline of a low single-digit percentage in 2027. Laptop manufacturers are also expected to reconsider their production strategies as rising costs make manufacturing outside China less attractive. The share of global notebook production outside China is projected to fall from 24% in 2025 to 21% in 2026 and potentially below 20% in 2027.

The biggest concern is expected to be the shift from component availability to weakening consumer demand, as manufacturers continue to tackle high CPU, DRAM, and SSD prices. The firm also added that if component prices continue to remain on the higher side, brands might pass more of these costs on to consumers.

Notebook shipments are expected to benefit from improved CPU availability and manufacturers stocking up on components in 2026. However, TrendForce warns that it does not directly translate into healthy demand. In anticipation of higher prices, certain customers have upgraded their devices earlier than planned. Essentially, fewer people will be looking forward to buying new laptops in 2027.

Additionally, once inventories purchased at lower prices gradually run out, manufacturers will face greater pressure to absorb higher component costs or pass them on to consumers. Increasing the retail price could further weaken demand, while absorbing the additional costs would squeeze profit margins. Manufacturers could also make changes to specifications, including memory capacity, to control production costs, potentially making their products less competitive.

It is estimated that the CPU, DRAM, and SSD account for approximately 68% of the bill of materials (BOM) cost for mainstream notebooks with a $900 manufacturer’s suggested retail price in the third quarter of 2026. TrendForce said manufacturers are unlikely to maintain pricing, specifications, and profitability simultaneously in 2027.

Rising component costs will continue to put pressure on manufacturers. While DRAM supply is likely to remain tight due to AI demand, NAND flash availability could improve in the second half of 2027. TrendForce says the key challenge will be whether consumers can absorb higher laptop prices. If manufacturers manage to limit price increases by adjusting specifications and absorbing some costs, shipments could decline by a small percentage in 2027. However, if higher costs are passed on to consumers, the decline could reach the high-single-digit range.

A vibecoder and modder has revealed they successfully launched Minecraft inside a modded iPhone port of GTA V, immediately showing the Minecraft HUD and loading in Steve. This was done using Claude Opus 5.5, doing everything from writing the code to testing the game; 0xProbability claims that they have not touched the phone while Claude successfully flies the Ender Dragon around Los Santos.

Minecraft in GTA V isn’t surprising, considering the vast amount of wacky mods you can put into the game. However, running it on an iPhone, now that’s just absurd. 0xProbability wasn’t the one to port GTA V onto the iPhone; they credit that to C22, a student of EPFL, a prestigious school in Switzerland. C22’s port is impressive; it’s running GTA V natively on the iPhone, based on a version of GTA V that was adapted to run in a web browser, and making that run as a native iOS application instead — even supporting multiplayer. The README states that it runs on iOS 15 or later and even macOS 14 or later on Apple silicon, ideally with 8GB of RAM or more. The port runs at an impressive 50-60 FPS on an iPhone 17 and only uses 1.1GB of RAM, as shown in C22’s video on X, showcasing their work.

As if GTA V on an iPhone isn’t impressive enough, vibecoder 0xProbability modded this version of GTA V with Minecraft. Before putting it on the iPhone, the developer experimented with possibly the same browser version of GTA V with Minecraft, complete with block-building mechanics, not just Minecraft mobs and characters. On one of their posts, they stated: “It’s crazy what you can run in a browser nowadays,” emphasizing how web browsers used to be for simple .io games, while in 2026, you can now play heavy 3D games on them.

While it would be impressive if the developer manually modded the iPhone port of GTA V himself, it’s also interesting to see how much Anthropic’s Claude Opus 5.5 is able to write code and test it all on its own.

A GitHub programmer has created an Nvidia bug tracker page that compiles each driver update’s release notes and feedback threads on the forums, logging progress on 462 different driver bugs. They first shared their creation, called NvidiaWatch, in late September and then released an update on the r/Nvidia subreddit earlier this week.

The programmer said that each bug gets its own page, meaning anyone affected by it could easily track if the latest driver update has already solved the issue. Each driver update also gets a dedicated page that includes the release notes, fixed bugs, and open issues that Nvidia couldn’t address yet. The creator also added a chart that tracks the number of known issues that were fixed during that release, fixed in a later release, remained open, and those that were carried over from an earlier driver release.

This website is quite useful for anyone running into issues with their Nvidia hardware, as they’d be able to track whether their problem has already been recognized by the company and whether it has done something about it. It’s also a good idea for anyone wanting to update the driver on their GPU to consult NvidiaWatch first; that way, they could avoid some nasty surprises like the fan control bug that came with the GeForce 595.59 driver.

Hopefully, someone could create a similar update but for Windows updates. A website like WindowsWatch would absolutely be useful, especially as the Microsoft operating system has a lot more users than Nvidia GPUs. This would help savvy users determine if an update is problematic, allowing them to roll back or pause updates before they encounter an issue, while also making Microsoft’s notes easier to understand for the layperson. Having a trend graph could also pressure Microsoft to fix issues much more quickly, as users could now see the number of problems piling up between fixes. This would be a bit complicated, though, especially as there are many different Windows versions, with some updates only affecting a few versions.

An ongoing cyberattack has reportedly struck major supermarket chains across Europe, disrupting refrigeration control systems. The attack — which has reportedly seen units set to continuously defrost at 50 degrees Celsius — is also apparently affecting deliveries and in-store pricing powered by electronic shelf labels, La Dépêche reports.

According to the report, "several" major retailers have been targeted by a cyberattack, which has hit Danfoss-made refrigeration controls used by French supermarkets Intermarché, Leclerc, and Coopérative U. Indeed, the latter's president, Dominique Schelcher, has confirmed as of Monday morning that "A cyberattack has been affecting the refrigeration production facilities of several stores in our network since last night." Schelcher said teams had been mobilized to fix the issue and promised an investigation into the incident, which he described as "extremely serious."

The report states the units have had their automatic defrosting systems activate, but that hackers have also configured the function — which normally runs for just two hours a day — into a continuous, forced defrosting cycle with the temperature set to a toasty 50 degrees Celsius. Sources reportedly described "a wave of heat" escaping from fridges and freezers

Early reports indicate losses are already approaching 300,000 euros, but could run into several million euros nationwide. Separately, NOS in the Netherlands reports that several supermarket chains have been hit with a malfunction due to a cybersecurity incident on Sunday afternoon. Albert Heijn, Etos, and Gall & Gall have had their websites taken down, impacting deliveries. Electronic shelf labels have also been compromised, disrupting in-store pricing. "We have immediately taken measures to protect our IT environment. Part of this involves the preventive temporary shutdown of a number of systems," Albert Heijn said in a statement.

It is unclear at this stage whether the two attacks are related or how widespread either of them is. Belgium's Delhaize chain, which belongs to Albert Heijn, has also reported disruption. Images online show stores in Amsterdam warning customers about price problems, and the suspension of loyalty programs that have also been impacted by the incident.

A GPU repair specialist has uncovered another GPU scam involving a counterfeit RTX 4090, with a fake GPU die and memory chips designed to resemble genuine components. The graphics card was purchased for 30,000 Rubles, or approximately $350, as a potential repair project. However, upon close inspection, it was revealed that the board was fitted with dummy components.

According to VIK-off (h/t VideoCardz), the Russian repair specialist received the GPU from a customer who purchased the card as a bare printed circuit board (PCB). Since the original cooling system was missing, it was difficult to verify whether it actually worked before the purchase was made. Now we’ve seen similar scams in the past, but this particular case stands out due to the sheer effort that was put into making the counterfeit components.

According to Vik-Off, the counterfeiters managed to replicate intricate details including the labeling, GPU package, chip markings, as well as the compound surrounding the processor. The fake GPU die was even soldered onto the PCB using a ball grid array (BGA), making it appear as though it had been installed during the original manufacturing process.

However, certain inconsistencies gave it away, like the color of the substrate, surface reflections, and certain lettering. After removing the fake GPU package, the repair specialist found that its contact area did not resemble that of a functional processor, while the solder mask started to deteriorate during cleaning.

Even though the memory chips looked genuine at first, removing one of the packages revealed what appeared to be GDDR6 memory rather than the GDDR6X chips used on the RTX 4090. The markings on these chips closely resembled genuine Micron memory packages, making the counterfeits even more difficult to identify. Vik-Off suspects the PCB design could be based on an RTX 3090 Ti, although there is no conclusive proof.

This isn’t the first time a counterfeit RTX 4090 has made its way into the hands of customers. Back in June, Chinese hardware shop owner Brother Zhang came across a broken RTX 4090 that had been purchased for around $222. A closer inspection revealed that the card was essentially a replica with a plastic imitation of Nvidia’s AD102 GPU die instead of the actual silicon. Additionally, the "TW 3043E2" marking indicated that the card was somehow manufactured in 2030.

One should always be cautious when purchasing used high-end graphics cards, especially those marked as repairable or untested. The onboard components and chip markings might look convincing, but that does not guarantee that the hardware inside is genuine. Always ask the seller for proof that the card works and, whenever possible, drop it in a system and test it before handing over your money.

Developer Maurice Heumann details in his blog how AI agents were able to decompile Call of Duty: Modern Warfare 2 (2009), which the post calls only “a popular first-person shooter,” in an effort to rebuild its source code in C++, taking three months and over 500 billion tokens. The agents originally attempted to cheat a byte-for-byte check added after the first month of code ran, but it was “semantically wrong,” and now 99% of the game’s functions are present, with 83% matching the original.

Heumann’s goal since the beginning has been to produce an “accurate, stable and feature-complete recreation,” and he wrote on X less than two weeks ago that the game was fully playable. By his estimate, the project consumed 600–700 billion tokens. In another X post, he said he doesn’t pay for his own tokens but put the cost at about €1,200 with subscriptions or $200,000–$250,000 with API tokens.

The difficulty turned out to be not in producing the code but verifying it was correct, forcing the developer to create a check and to make sure the agents couldn’t game it. The other challenge, as he put it, was that “corporate America was here to ruin our fun.” Two earlier blog posts on the project have since been removed, and the video in his Sept. 30 X post was disabled after a report by the copyright owner. No comment from Activision is currently on record.

The method includes pointing a fleet of agents, using Anthropic’s Claude and OpenAI’s Codex, at the original 2009 PC game. Heumann started with a Claude Max (20x) plan, then added Codex Pro and used both simultaneously. These are flat-rate plans and do not use per-token API billing. “Most of the time,” the developer relied on Sonnet 5, although Opus 5.5 and OpenAI’s Luna, Sol, and Terra were “also used a lot.” For harnesses, he relied mostly on the Claude Code and Codex CLIs.

The agents read the code through IDA using Hex-Rays’ ida-mcp server. The work started with four agents, three workers and a reviewer; by Sept. 30, he wrote on X, it had “17 agents working in parallel.” Keeping all of this straight meant having one GitHub issue per translation unit, and having all agents and humans share a single Discord channel with GitHub webhook CI posts. The developer also tuned the auto-compaction threshold, from the default 90% of the context window maximum to 42% to help clear finished functions out of memory. Agents also had a tendency to drift, so an hourly cron job had them reread instructions.

The agents’ first month of code was extremely readable but “semantically wrong” for multiple reasons: wrong function signatures, types and struct layout issues, and logic that was invented or removed. The agents also made unneeded architectural changes, such as turning a config-variable lookup into one that was “orders of magnitude more expensive.”

The reviewer agent failed to stop this as there were no objective acceptance criteria, and the workers’ comments justifying their changes “effectively acted as unintentional prompt injection,” Heumann says. The team eventually stripped all comments from the source, which “helped a lot,” he wrote on X. An attempt to salvage the first four weeks of code took more time than starting from scratch would have.

The answer was an automated check, so the team switched to the same compiler used to build the original game. A script compares each rebuilt function against the game’s executable at the byte level. Calls and data references are at different addresses and are skipped, with target symbols and offsets checked instead, but data and types get the same check. Then it’s a simple matter of pass/fail for each function, and every match is recorded so CI can recheck it and alert on regressions. While this type of matching is slow and sometimes challenging, a match guarantees identical behavior down to reproducing original bugs.

Even with this positive change, the agents immediately tried to cheat by writing “inline assembly” and “repeatedly tried to modify this script to exclude their function from comparison,” Heumann wrote. Inline assembly and similar shortcuts were then banned in the agents’ instructions, and CI now hashes the verification script and checks it against a hash stored as a GitHub Actions secret. Agents cheating is an expected outcome at this point with many such reports, such as when OpenAI’s models went after ExploitGym answers instead of solving the capture-the-flag challenges directly. As Heumann discovered, having a reviewer agent alone may be insufficient.

Before the check was originally implemented, the cheaper, less capable Haiku and Luna models “produced extremely bad results,” the post says. With the check in place, there was sufficient feedback to make the models work, which cut costs and let the project scale up. After almost two more months, 99% of the functions were present, with 83% meeting the byte-exact requirements. Heumann believes the 16% lacking a byte match are still semantically correct, but diminishing returns were getting real. The blog claims the game “runs flawlessly” as it stands.

For “obvious reasons,” the project’s code is remaining private and will be used “for my own needs only,” Heumann says. As he put it on X, the “decompiled code is obviously also copyrighted.” However, the developer has started extending Sogen, his userspace emulator, into lightweight sandboxing for agents, a response to his project’s agents wiping VMs. It will not be production-ready for a while.

As for the decompilation project, Heumann says that it is a special case, as not every project can do a byte-for-byte reference, but thinks every project can get close “with enough creativity.” One takeaway lesson is that you should be willing to move past failures as “Generating code is cheap now. Throw it away if it’s bad” and focus on correctness over productivity.

If you're in the market for a budget gaming laptop, then $1,149 for a 15-inch RTX 5060 HyperX OMEN is about as good as it gets right now. Walmart has slashed $750 off the price of this Intel Core Ultra 7 machine with 16GB of RAM and 1TB SSD, now just $1,149.

● Check out this deal at Walmart

In a world where PC prices are skyrocketing, gaming laptops and desktops are getting more expensive on a near-weekly basis. This is a generous spec and price in the market given current conditions, and worth considering for anyone who wants to take their first step into mobile gaming or to upgrade from an older device.

At the heart of this gaming rig is the Intel Core Ultra 7 255H. This 16-core, Arrow Lake-H CPU has six performance cores and eight efficient cores, making it ideal for both gaming on the go and productivity workloads, all while preserving battery life. The RTX 5060 won't run Cyberpunk 2077 at 4K 60 fps, but it doesn't need to, and will provide more than ample performance at this laptop's native resolution of 1920 x 1200. With up to a 165Hz refresh rate, gaming on this display will be smooth, with added support for Nvidia's DLSS 4.5 technology.

To complement the CPU and GPU, you get 16GB of RAM, which is a decent amount for multitasking at this current price bracket. You'll also get a 1TB SSD for storing games and files. As well as a copy of Windows 11.

Connectivity includes USB Type-A, Ethernet, and a 3.5mm audio jack, as well as Wi-Fi 7 under the hood.

As we noted in our recent review of the Omen 15 lineup, this is a competitive laptop range when it comes to gaming, with some obvious cost-cutting measures. At this budget, the chassis will feel less premium than more expensive offerings.

Snag an awesome after-the-sales bargain on a new OLED monitor upgrade with a delicious 36% off deal on a new 27-inch Asus Republic of Gamers (XG27AQDMGR) WOLED gaming monitor for just $384. Now's the perfect time to upgrade your gaming setup to an OLED panel whilst it's on sale. You can find this superb deal on Amazon, where the original list price of this screen was $599, so you're making a saving of $215. That's nothing to be sniffed at in the current climate for PC gaming prices.

● Check out this deal at Amazon

The Asus ROG XG27AQDMGR is a flat-panel gaming monitor with a 1440p QHD resolution along with a super-fast refresh rate of 240Hz. As with the majority of OLED monitors, the technology allows for a rapid response time of just 0.03ms; this provides an incredibly smooth gaming experience and eliminates ghosting from fast-motion gameplay.

The WOLED panel sports VESA DisplayHDR 400 True Black compliance, 99% DCI-P3 color gamut, true 10-bit color, and a Delta E <2 color difference for astonishing HDR performance from your games. This screen also features Asus' Neo proximity sensor that can precisely detect when you're away from your screen and can switch to a black screen to reduce any chance of static screen burn-in. Along with OLED care functions, the screen should stay bright and burn-in-free.

Asus' superb WOLED monitor also comes with plenty of connectivity options for connecting to your PC and other computing hardware. You can hook up your game consoles like the Xbox Series X, Switch 2, and PlayStation 5, or maybe even your laptop for work or school, or anything else with a compatible video port. There are 2 x HDMI 2.1 ports, 2 x DisplayPort 1.4, and 2 x USB ports.

Redditor u/cal93 had the used PC they bought for $650 from an unnamed seller suddenly blocked from working by a remote trigger. According to their post, they bought the computer a few months ago on OfferUp, but downloading a Windows update last month led to the situation. Fragile, which is NZXT’s partner that runs the Flex subscription program, commented on the thread, saying that the PC they bought was a rental and that the seller had no right to sell it. We spoke with the Redditor, and documents reviewed by Tom's Hardware confirm that they were sent an entirely new PC by Fragile, free of charge, to replace the stolen PC they originally purchased, with the requirement that the stolen PC be turned in to the police.

“We’re sorry you’ve been put in this situation. The PC you purchased was being rented through NZXT Flex, and the person who sold it to you did not own it or have the right to sell it. We understand you paid for what you believed was a legitimate purchase, and we want to help,” the company said. “Please email us or call/text with a link to this thread so we can connect with you directly. You can also DM us here on reddit. In situations like this, we typically work with the buyer and local law enforcement to help pursue the seller. Please keep any messages, the original listing, and proof of payment.”

This response was great news for u/cal93, who said that they were using the computer for school. They added to the thread that they were happy with the proposal and would provide more details once the company gave them the green light. u/cal93_’s latest Reddit update gave us more details about the transaction. They said that the seller sold the PC to them, which appears to be an NZXT Flex One unit worth around $1,500, for $650. When Fragile saw the post and reached out, the company asked for proof — receipts, chats, and seller information — after which it agreed to replace the “bricked” PC. The Redditor is just waiting for the shipping label and instructions to drop off the device at FedEx and then hopefully get their replacement soon after.

NZXT’s PC rental program started back in 2024 and is one solution for a person who needs a computer right now but can’t afford the upfront spend requirement of buying one. However, the program faced issues a little over a year in, resulting in a RICO lawsuit in California. This ended with the company paying a settlement earlier this year, totaling $3.45 million, to affected customers. Because of this, some commenters call this move a “rare” win for the user, while also earning NZXT and Fragile some positive feedback.

Whatever the case, the Redditor said that they got the best possible scenario, as they will get a new PC to replace the one they were scammed on. Fragile also said that it will pursue the person who sold the rental NZXT PC, so they’re not getting away scot-free either.

A Reddit post by user markpronkin (“OP”), titled “54gb vram for 35$,” says the user purchased an old crypto mining rig, originally discovered in a garage, for a negotiated 3,000 rubles, or about $35. The rig was rusty, and the buyer “had zero idea if it works, so did the seller,” with a pre-purchase test request refused. However, on the first try, all nine Nvidia P106-100 GPUs, with 54GB of VRAM between them, worked. The initial test: a successful local run with the 35-billion-parameter model Qwen3.6-35B-A3B in Ollama, which operated at over 30 tokens per second.

The rig was discovered in a “damp garage” the seller had purchased years earlier, then listed on Avito, a Russian classifieds site. The OP had concerns about whether or not the rig would work and offered to test it and pay more if it functioned, but the seller refused, and the price was negotiated down without a test. The cost was low enough to take the risk, the buyer said. Even in the case the rig worked, performance was imbalanced, as the main system has a weak Celeron CPU with very little system memory.

The setup was originally intended for crypto mining with specialized Nvidia P106-100 GPUs, Pascal-generation cards with 6GB of GDDR5 each that OP calls “basically gtx 1060 6gb.” Gigabyte’s P106-100, for reference, has 8,008 MHz memory with a 192-bit bus width for about 192 GB/s per card. The hardware was originally introduced around the middle of 2017. The cards are no longer entirely supported as CUDA 13.0 removed offline compilation for GPUs below compute capability 7.5, which includes Pascal GPUs, and driver branch 580 is “the final [one] that supports GPUs before CC 7.5,” Nvidia says on its developer blog. Security updates are supported through October 2028, however.

The first test was a mixture-of-experts model using Alibaba’s Qwen with “35B [parameters] in total and 3B activated,” per Qwen’s model card on Hugging Face; it’s roughly a 24GB download. The initial test had it at “30+ tokens a second” in Ollama but it can probably operate faster “with mtp and some optimizations,” OP says, referring to multi-token prediction.

Another user stated that such performance was possible on a CPU alone, to which OP replied, “On a 35$ device without any optimizations?” A dense, non-MoE model such as Qwen3.8-27B is unlikely to run as well, but “It should run any MoE model that fits entirely into VRAM decently well.” Performance is also expected to be limited by the PCIe 2.0 x1 motherboard slots.

The system is capable but would have some limitations due to the sizes of some popular models. Qwen3.6-35B-A3B at 8-bit should fit at 36.9GB, as should Llama 3.3 70B at 4-bit, at 42.5GB; at 5-bit, just below 50GB, it would leave little room for context. Larger models are probably not workable, and even the 70B 4-bit Llama would hit a ceiling around 4.5 tokens per second before hitting other bottlenecks, since each token reads all 42.5GB, card by card, at about 192 GB/s. The performance the buyer achieved is in spite of the rig, and the MoE model was the best choice for that type of result.

The buyer still got a good deal, as the price comes out to about 65 cents per GB of VRAM. For comparison, an RTX 5090 with 32GB of VRAM and 1,792 GB/s of memory bandwidth launched at $1,999 in early 2025. The rig has 1.7 times the VRAM for less than 2% of that price, but each of its cards has about a ninth of the bandwidth. According to OP, the mostly compute-only P106 cards sell for about 50% of their GTX counterparts.

One important caveat here is electricity costs, with the GPUs having a combined 1,080W TDP as estimated by one commenter, but OP says their power is free and generally inexpensive in Russia as a whole.

With the rig securely in hand, the OP’s next move is to transfer the hardware to a better case that supports up to an i7-7700K CPU and 32GB of RAM. The new case allows for 12 GPUs, so buying three more of the same adds up to 72GB of VRAM total. The solution is attractive because of “unlimited usage and actual privacy,” the buyer said to WiredEntrepreneur. Repurposing used hardware for a self-hosted AI solution with appropriately sized MoE models is a viable, useful project for enthusiasts who want freedom. From the OP’s perspective, more VRAM means more freedom.

Video game console sales in the U.S. have cratered, with both the PS5 and Xbox seeing a massive drop in YTD sales through the end of August compared with last year. Mat Piscatella, the video game industry advisor at research firm Circana, shared the numbers on his Bluesky account — PlayStation 5 sales have dropped by 25%, putting it at its lowest point since 2013, when gamers held off buying PlayStation consoles in anticipation of the arrival of the PS4, while Xbox’s retail figures have cratered by 33% YTD, putting its sales numbers at an all-time low since its launch almost 25 years ago.

From Circana's US Retail Tracking Service:For 2026 YTD ending August, Xbox hardware unit sales are down 33% versus a year ago in the US, while PlayStation hardware units are 25% lower.Xbox YTD US hardware unit sales are at an all-time low, while PlayStation is at lowest point since 2013.

— @matpiscatella.bsky.social (@matpiscatella.bsky.social.bsky.social) 2026-10-11T15:51:03.015Z

Piscatella said price sensitivity is becoming a real problem among gamers, especially as the chip shortage has pushed console manufacturers to raise prices. Microsoft has raised the price of the Xbox three times in the past two years, with the 512GB versions jumping by $100 and 1TB models becoming $150 more expensive. Worse, the company has killed off the 2TB model. This brought the Xbox Series S to $499.99 (512GB) and $599.99 (1TB), while the Xbox Series X now costs $749.99 for the Digital Edition, and the disc version costs $50 more at $799.99.

PlayStation fans haven’t escaped these price hikes, as Sony raised prices for that console by $100 to $150. The base Digital Edition PS5 now costs $599.99, while the version with an optical drive is priced at $649.99. If you want the PS5 Pro, you’ll have to shell out $899.99, while those who want to stream games from their console via the PlayStation Portal must now pay $249.99 — $50 higher than its $199.99 launch price. Even used consoles didn't escape inflation, with Sony bumping the price of refurbished PS5 Slim consoles by $100, bringing them to $399.

Despite the higher prices, the PS5 Pro remains in short supply, which is why used prices have now reached the stratosphere. Refurbished PS5 Pros now cost $1,399 at GameStop, almost $500 more than the MSRP of a new one (if you can find one in stock at that price). While this price might feel egregious, it’s about $100 less than the prices of new units we found at Best Buy and Walmart, and sealed units on online marketplaces sell for about $100 less than this.

AI chip shortage-driven price hikes, along with rising living costs, have made console purchases less of a priority for many families, driving this massive downturn in retail sales. The arrival of the much-anticipated GTA VI in November, along with the upcoming holiday season, will hopefully help consoles bounce back. Still, Piscatella says the U.S. hardware market has never been more precarious since the early 1980s.

Cyberleek, the infamous group that's been drip-feeding the gaming community with improperly tone-mapped leaks of GTA 6 from what appears to be a real final build of the game, has just put down an ultimatum for Take-Two Interactive and Rockstar Games: do a physical release for GTA 6 and apologize, or the group will release a full build of the game with the complete story mode. It's not clear exactly what Cyberleek wants an apology for, but that's the demand.

As we reported previously, Cyberleek is leveraging its stolen build of Grand Theft Auto VI to try and pump its memecoin, $CYBERLEEK on Solana. That has seemingly always been the plan; the leakers cashed out some $250,000 just hours before Rockstar's Extended Look show went live on Netflix. We thought that would probably be the last we heard of Cyberleek, but the outlaw has returned this week with more leaks, including footage of both main characters as undressed as they get and numerous major story spoilers.

This time, Cyberleek's goals are grander, and also more transparently self-serving. While the leakers previously spoke of high-minded ideals, like preserving gamer ownership of games, this latest message, titled "The Offer," simply demands that the Cyberleek memecoin hits "30 million marketcap" before they will release the build. That's right: even if Take-Two completely ignores Cyberleek, apparently nothing will happen unless the memecoin hits $30 million.

That's not happening soon, because the market cap of the memecoin is only $5 million and is actually trending sharply downward from a peak of $7.6 million at 5:00 AM Central US time. Have the people lost faith in Cyberleek? Or is it simply that people are realizing what a scam this whole operation is and doing the mature, intelligent thing by electing to wait for the official release of the game?

Well, it could be something to do with the image above, where Cyberleek demanded a $6 million market cap for the Cyberleek memecoin to provide "4K closeups, fully naked" of the main character, Lucia. Those promised prurient photos have not appeared on the site yet, but speaking as a gamer myself, this shameful scenario really isn't doing anything to help the reputation of gamers everywhere.

GTA VI launches on November 19, 2026, barely more than a month away. Neither Rockstar nor Take-Two have addressed the leaks directly; Rockstar said that the situation is "heartbreaking" for the development team, which is understandable. If you're excited for GTA VI, do yourself a favor and stay away from these poor-quality leaks. Whoever has the development build doesn't play the game very well and doesn't understand HDR tonemapping, so all the clips are badly washed out and some of the most boring gameplay you have ever seen in your life. Take my word for it and go listen to "Love is a Long Road" one more time.

A YouTuber has received an unexpected visit from the police over an automatic license plate recognition (ALPR) camera he built to specifically track police cars, using the same technology law enforcement has infamously used to track ordinary citizens. In a video posted to his channel on October 7, Anthony Sistilli says two police officers showed up at his doorstep on September 20th to ask questions about the device, asking what his intentions were with the project.

Sistilli, a Canadian software engineer and YouTuber, pointed out the irony of the officers' concerns, explaining that they mirror the privacy concerns of ordinary citizens who are growing increasingly weary of the recent spike in blanket surveillance brought about by a mass installation of ALPR cameras. Flock Safety, a U.S. public safety technology company, recently scaled its centralized national surveillance network to over 120,000 cameras operating across 49 states, according to the company, capturing billions of vehicle scans every month.

The development sparked widespread public backlash, with critics arguing that Flock has quietly built a massive government surveillance dragnet without a public vote or federal oversight, since any police department on the network can search across state lines. Security researchers later discovered the network included 335,701 Flock cameras and created a “Flock Surveillance Map,” exposing their locations.

Similar ALPR camera surveillance networks exist in Canada, where Sistilli resides, prompting him to build his own device, but this time, encoded to exclusively track police cars. He detailed the build in several TikTok videos, describing it as “a personal Flock surveillance camera to Flock the Flockers.” He then posted a video of himself using the device in real life. The video brought Peel Regional Police, the local law enforcement serving Sistilli’s city, Brampton, Ontario, to his doorstep two weeks later.

“One of them [the officers] took the time to specifically mention how scary it would be for them, because people would be able to find out where they lived, when they got on their shift and what they were doing throughout the day, and that that type of powerful information could put them personally at risk for any bad apples that might want to track them down,” Sistilli narrated. He went on to point out that these were the exact concerns ordinary citizens had about constant surveillance, suggesting there should be more policies and systems around such networks. The officers reportedly responded that there was probably no effective way to implement this without giving away details of active investigations to criminals.

After several investigative reports exposed incidents where officers misused Flock’s database, with instances of stalking of exes and their acquaintances, public backlash snowballed into physical resistance that has seen residents covering or destroying the cameras. Several municipalities, including major hubs like Los Angeles and Fullerton, have now suspended or outright canceled their Flock contracts due to constituent privacy concerns.

Flock and its proponents insist the network has helped lower crime, a claim critics say misreads the data. Sistilli’s video also details aggressive, arguably deceptive marketing tactics Flock uses to convince municipalities to accept cameras. Another issue is centered around the collection and handling of the data. The company says its cameras are protected by on-device encryption and only briefly store images before they are forwarded to its servers. However, hackers reportedly extracted over 27,000 clips and 1.6 million images, captured in a span of 21 days, from a stolen Flock camera.

It might be reasonable to assume that desktop PCs are built in a certain way due to decades of evolution and optimization. However, we're getting used to TrashBench challenging convention, and we're pleased to say the video below represents one of this enthusiast's best cooling innovations yet. In this latest video, completely ignoring the accepted norms of GPU placement delivered up to a 19°C hotspot temperature reduction but adversely impacted CPU temperatures. However, some more tweaking resulted in a 14°C reduction in hotspot temperatures and a 3.3°C cooler CPU.

TrashBench's plan was to prepare his RTX 3080 desktop PC and "test it normally, then start moving s*** around." This process began with an entirely conventional setup with the CPU cooled by a 360mm AIO, and the triple-fan RTX 3080 slotted directly into the usual PCIe expansion slot.

With the traditional build complete, TrashBench tested this baseline with a constant thermal load from looping 3DMark Time Spy and 7-Zip’s built-in benchmark. The fans in the system had their RPMs locked for consistency. Now he could start "trying to figure out if we’ve been putting the parts in the wrong place."

Beginning the first 'alternative' PC build, we heard the modder muse, "cable management isn’t important here... Is it ever?" Then we saw the GPU tested at the bottom of the case, and vertically to the side, facing one way or another, and either side of the triple case fans on the side. Meanwhile, the CPU AiO cooler was tested with the radiator fans pushing air out or bringing air in.

In summary, some configurations mostly benefitted the GPU or the CPU. But, as we noted in the intro, the sweet spot - where a worthwhile benefit was recorded in cooling both the GPU and CPU was still very worthwhile.

Taking the lessons learned from the best GPU and CPU cooling ideas, and striking a balance, TrashBench finalized his reinvented PC cooling design. That was with the CPU mounted vertically, directly against the side intake fans, and the CPU AiO cooler radiator in a traditional exhaust config. See the screenshot for the observed benefits. We’d headline this sweet spot configuration as delivering a 3.3°C cooler CPU and chilling the GPU hotspot by 14°C.

If you want to try this kind of GPU repositioning testing, a PCIe riser cable is essential. We saw TrashBench use them in a number of lengths.

Russian bot traffic has dropped dramatically in the past few days after Ukraine knocked out Yandex’s biggest data centers, with a third attack happening last night. Cloudflare reports that bot traffic from the Yandex network has dropped to just 0.4% of the maximum number of HTTP requests recorded in the past two weeks. It initially dropped to around 57% on Oct. 8, which happened when Ukraine hit a Yandex data center housing two supercomputers in Sasovo, Russia, located around 195 miles to the southeast of the Kremlin. A second, bigger Yandex campus in Kaluga, about 220 miles to the west of Sasovo, was knocked offline yesterday.

These attacks are apparently Ukraine’s response to Moscow’s strikes on its own data centers, some of which resulted in the outage of some of the most popular piracy websites.

Yandex is Russia’s equivalent to Google, and its Yandex Cloud service status reports that at least 84 services are currently offline. Global internet monitoring firm NetBlocks said that Yandex’s network traffic has dropped to just 30% for Yandex Cloud and 63% for Yandex LLC, most likely resulting in slower internet services or complete disruption for the average Russian. Unfortunately, the ordinary Russian wouldn’t be able to use high-speed satellite internet as a backup, as Starlink does not work in Russia, while the competing Rassvet constellation has had a good number of its existing satellites fall back to the surface after launch.

These incidents are a result of the ongoing conflict in Ukraine, which escalated dramatically in 2022 after Russia’s failed attempt to capture Kyiv. However, many observers say that the war actually started in 2014 when Russian forces seized Crimea and occupied parts of eastern Ukraine after the fall of the pro-Russian government that year.

The hostilities, which have dragged on for years, saw the introduction of new technologies and strategies, specifically in drone warfare. It began with the wide deployment of commercially available drones on the front lines, typically for reconnaissance, dropping explosives, and kamikaze-style attacks. However, it has since evolved into long-range warfare, with specially built drones able to reach distances of over 1,500 miles and destroy Tu-95 strategic bombers situated well behind the front lines.

The drone strikes on data centers are relatively new developments. While data centers on bases are often considered valid targets, Russia’s justification for the attacks on civilian data centers was that Ukrainian military intelligence used them. This isn’t the first time that civilian data centers have also been hit by drones and missiles. AWS sites in Bahrain and the UAE have been hit multiple times since Washington started its bombing campaign against Iran, with the company telling its clients to move their data to sites outside the region, as it doesn’t have a recovery timeline.

Sandisk is back with another welcome SSD, the NAS 800. As the name implies, this drive is designed for NAS appliances, but could also be a good choice for high-end desktop and enthusiast workstations. We recently reviewed the Optimus GX Pro 850P, a consumer drive for the PS5, so SanDisk is on a roll. The company has made it clear it wants to support the broader consumer market, as it’s even bringing back SATA SSDs in the form of the 320 and 520 series. The NAS 800 is closer in theme to the WD Red series of drives, like the WD Red SN700, which are optimized for home and small-business servers.

At its heart, the NAS 800 is a specialized, optimized Sandisk Optimus GX Pro 8100 (formerly the WD Black SN8100). That progenitor is one of the best drives on the market. It has a stellar controller and excellent all-around flash with good power efficiency and low latency. This makes a great base for a NAS drive, although some changes are necessary. The bones are good, though, and this drive could be used in any system. The only real issue is that you’re paying a premium for the NAS optimizations, and that’s where our focus is.

Sandisk NAS 800 Specifications

The Sandisk NAS 800 has some strange capacities, at least compared to consumer offerings, because the drives reserve more spare flash as overprovisioning, which improves endurance. The drive comes in 960GB, 1.92TB, 3.84TB, and 7.68TB flavors. The final one is the most welcome, as it’s been difficult to find larger drives outside of enterprise. Performance is excellent, at up to 14,900 / 13,200 MB/s for sequential reads and writes and up to 2,300K / 2,100K random read and write IOPS. Peak overall performance should be achieved at 3.84TB.

Write endurance is where this drive really stands out. It’s rated for up to 14PBW at its maximum capacity. Proportional to size, this puts it at almost three times the normal for consumer drives. The drive also supports TCG Opal self-encryption for data at rest, as would be expected for a drive in this class. Things are capped off with a standard five-year warranty.

You pay for this performance and endurance. At the time of writing,SanDisk’ss store lists the four capacities at $387.99, $699.99, $1,374.99, and $2,749.99. That’s roughly 45% to 65% more than the WD Black SN8100’s current street prices. Against the same drive under its new Optimus GX Pro 8100 name, the premium is between 27% and 29% at the time of review. The extra cost comes partly from the drive’s optimization but mostly from its TBW rating. You’re getting about one drive write per day over the five-year warranty, which is all but required for a drive of this type, and worthy of the price tag if you’re focused on endurance.

Sandisk NAS 800 Software and Accessories

If you own a Sandisk drive, or a WD drive for that matter, then you should be no stranger to the NAS 800’s software offerings. Sandisk has its own dashboard, aptly named Sandisk Dashboard, which follows the popular WD Dashboard. This SSD toolbox has all the information you need for your drive, including important SMART and health information. It also lets you enable optional features, find firmware updates, and more. Sandisk also provides a download for its OEM version of Acronis True Image, useful for backing up your files or cloning your drive.

Sandisk NAS 800: A Closer Look

The 1,920GB, or 1.92TB, version of the NAS 800 is single-sided. That also applies to the 960GB and 3.84TB versions. Only the 7.68TB version is double-sided, although that shouldn’t generally preclude you from using it in devices that would benefit from the drive. It could make a difference for certain cooling arrangements. The drive’s rating of 3.3V / 2.7A puts it at around 9W, which is between the drive’s maximum power state of 9.50W and its 6.5W / 6.4W average draw for this capacity. The reported active draw of 7.52W is higher than this average, but given that this drive is NAS-optimized with a small pseudo-SLC (pSLC) cache, it will likely be lower in practice. The drive should run cooler as a result.

The drive layout includes the SSD controller, a DRAM package, and two NAND flash packages. The 7.68TB version will need more packages on the rear, for a total of four flash packages. The controller is labeled in a way similar to SanDisk’s proprietary parts, but the “250800” spells out that this is a Silicon Motion, or SMI, SM2508. This is an eight-channel, high-end PCIe 5.0 SSD controller with generally excellent performance and power efficiency.

The DRAM package is LPDDR4 and is therefore a more power-efficient choice. It’s also 2GB, which follows the normal 1:1,000 ratio of DRAM to NAND. Our recent Optimus GX Pro 850P review had a 2TB drive from Sandisk with only 1GB of RAM. That’s perfectly suitable for gaming use. For this NAS drive, 2GB is very much preferred. The controller and DRAM are paired with SanDisk’s 218-layer BiCS8 TLC flash. This is some of the best flash on the market, with good all-around performance, very good latency, and very good power efficiency. This is world-class hardware, and the price reflects that.

MORE: Best SSDs

MORE: Best External SSDs

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Comparison Products

The Sandisk NAS 800 technically has little competition in this market. We do have the Gen 4 Addlink NAS D60 with power-loss protection, but it’s otherwise pretty thin, particularly for Gen 5. The closest non-NAS retail drive in Gen 4 is the WD Black SN850X. For Gen 5, we have the WD Black SN8100, which has the same hardware as the NAS 800, and the same goes for the Kingston Fury Renegade G5. The Crucial T710 and Lexar NM1090 Pro use the same controller but two different generations of Micron flash rather than Kioxia or Sandisk flash. Phison is represented by the Corsair MP700 Pro XT, while the main proprietary option here is Samsung’s 9100 Pro.

Trace Testing — 3DMark Storage Benchmark

Built for gamers, 3DMark’s Storage Benchmark focuses on real-world gaming performance. Each round in this benchmark stresses storage based on gaming activities including loading games, saving progress, installing game files, and recording gameplay video streams. Future gaming benchmarks will be DirectStorage-inclusive and an evaluation for future-proofing is included where applicable.

We wouldn’t normally recommend a NAS drive for gaming, but if you happen to use this drive, you would be good to go. The NAS 800’s flash is known for being low-latency, and while it doesn’t perform up to the Black SN8100’s level, it’s in the same ballpark as the T710 and 9100 Pro. The drive does not seem optimized for it, though, as it does lose quite a bit of performance against the Black SN8100, which has the same hardware. This is still more than fast enough for games. You would be plenty happy with just the Black SN850X.

Trace Testing — PCMark 10 Storage Benchmark

PCMark 10 is an industry standard trace-based benchmark that uses a wide-ranging set of real-world traces from popular applications and everyday tasks to measure the performance of storage devices. The results are particularly useful when analyzing drives for their use as primary/boot storage devices and in work environments.

Performance is a bit weaker in PCMark 10 than in 3DMark. The NAS 800 finishes closer to the Lexar NM1090 Pro, which is not a bad drive but also not fully within the same class. We would expect it to be closer to the T710 and 9100 Pro. The Black SN8100 doesn’t shine quite as much here, either, but the NAS 800 trails it by 26%, a wider gap than the 21% in 3DMark.

This points to firmware tuning and other optimizations on the NAS 800, rather than a limitation of the shared hardware. The Phison-based MP700 Pro XT leads the pack and seems better optimized for PCMark. The NAS 800’s performance is still excellent in the grand scheme of things, though, well above Gen 4 drives. It’s just not our first choice for applications.

Console Testing — PlayStation 5 Transfers

The PlayStation 5 is capable of taking one additional PCIe 4.0 or faster SSD for extra game storage. While any 4.0 drive will technically work, Sony recommends drives that can deliver at least 5,500 MB/s of sequential read bandwidth for optimal performance. Based on our extensive testing, PCIe 5.0 SSDs don’t bring much to the table and generally shouldn’t be used in the PS5, especially as they may require additional cooling. Check our Best PS5 SSDs article for more information.

Our testing utilizes the PS5’s internal storage test and manual read/write tests with over 192GB of data both from and to the internal storage. Throttling is prevented where possible to see how each drive operates under ideal conditions. While game load times should not deviate much from drive to drive, our results can indicate which drives may be more responsive in long-term use.

If the NAS 800 is overkill for PC gaming, it’s really overkill for PS5 gaming. Performance is pretty good, as expected, but you’re leaving a lot of its bandwidth potential on the table. The drive is also not optimized for this type of workload. However, it could work if you do a lot of writes on your PS5 and want something with extreme endurance.

Transfer Rates — DiskBench

We use the DiskBench storage benchmarking tool to test file transfer performance with a custom 50GB dataset. We write 31,227 files of various types, such as pictures, PDFs, and videos to the test drive, then make a copy of that data to a new folder, and follow up with a reading test of a newly written 6.5GB zip file. This is a real-world type workload that fits into the cache of most drives.

At a quick glance, the NAS 800 does well with reads but not so well with writes and copying in our DiskBench test. Obviously, having slower writes will impact copy performance. That’s the reason the drive lags here, as the test works against the NAS 800’s design. Its roughly 12GB pSLC cache can only absorb the first quarter of the 50GB write, with the rest going straight to TLC. For that reason, its write score lands about 20% below the other Gen 5 drives, with a drop of 36% for copying against the same-hardware SN8100.

Admittedly, a NAS drive should be able to tackle file copying like this. A better test to show its value would be an extremely large transfer, where its steady-state performance would win out. Also, for smaller transfers, particularly random writes, its small cache would perform well. Know your workload before picking your drive.

Synthetic Testing — ATTO / CrystalDiskMark

ATTO and CrystalDiskMark (CDM) are free and easy-to-use storage benchmarking tools that SSD vendors commonly use to assign performance specifications to their products. Both of these tools give us insight into how each device handles different file sizes and at different queue depths for both sequential and random workloads.

The NAS 800 does quite well in ATTO and CDM where it matters. Its performance in ATTO is as expected, tracking the curve of the similar Black SN8100, and quite good on the whole. Write performance in particular is consistent.

In CDM, the drive is top in random read latency and nearly the top in random write latency. These are great numbers, and the drive is exceptionally responsive with 4KB low-queue-depth operations. Sequential performance is rougher but not terrible. Once queue depth gets up there (QD8), sequential read performance is effectively identical to the very fastest drives available. Sequential write performance is weaker, although we expect that to some degree on a drive optimized more for sustained writes. For internal transfers between very fast drives, this can be a factor, but the extra write endurance is a solid trade-off.

Sustained Write Performance and Cache Recovery

Official write specifications are only part of the performance picture. Most SSDs implement a write cache, which is a fast area of pseudo-SLC (single-bit) programmed flash that absorbs incoming data. Sustained write speeds can suffer tremendously once the workload spills outside of the cache and into the "native" TLC (three-bit) or QLC (four-bit) flash. Performance can suffer even more if the drive is forced to fold, the process of migrating data out of the cache in order to free up space for further incoming data.

We use Iometer to hammer the SSD with sequential writes for 15 minutes to measure both the size of the write cache and performance after the cache is saturated. We also monitor cache recovery via multiple idle rounds. This process shows the performance of the drive in various states including the steady state write performance.

The NAS 800 writes a bit differently than most other drives we’ve tested. It’s only pushing 12 GB/s for about a second in the pSLC mode, and then it drops to just below 4 GB/s for the direct-to-TLC mode. This indicates that the cache is likely static, that is, always available and in a usually high-endurance region. We’ve tested consumer drives with this setup in the past, like the original WD Black and the WD Black SN750. These drives were actually great for NAS. However, over time, it became clear that consumer workloads are bursty and prefer large, dynamic caches. Sandisk and Samsung use hybrid caches these days for the best of both worlds.

While small, a static cache can be useful for higher endurance, and it still handles many random writes just fine. As the cache comes from the base flash, its size is limited. The NAS 800 already has extra overprovisioning to increase its endurance, just as many enterprise drives have, which potentially limits the size of this cache even more. Typically, you would have about 24GB of static cache for 2TB and about 12GB for 1TB, give or take, so our guess is Sandisk is balancing all of this for endurance with the extra overprovisioning.

We find this to be a good trade-off, as 12GB is still quite a lot if you’re juggling smaller random writes. Those get handled by the pSLC cache, which likely has very high endurance, and then they are combined for low write amplification to the native TLC flash, or discarded if the writes aren’t kept. The static cache and native flash may have separate wear zones, which, in summary, means the cache arrangement can help support higher overall drive endurance.

Another big bonus of the small cache is that post-cache performance is high and consistent. At about 4 GB/s, it’s very fast for consumer-grade hardware, and this drive held that pace for a full hour in our testing. That’s a big selling point, and 4 GB/s is more than enough for 10GbE links. Internally, this can keep up with pretty much any Gen 4 drive in the long term. If arranged in an array, this level of performance is high enough for workstation and even some enterprise-level workloads. The T710 and MP700 Pro XT look faster on paper but are not as consistent.

Power Consumption and Temperature

We use the Quarch HD Programmable Power Module to gain a deeper understanding of power characteristics. Idle power consumption is an important aspect to consider, especially if you're looking for a laptop upgrade as even the best ultrabooks can have mediocre stock storage in terms of capacity and performance. Desktops are often more performance-oriented with less support for power-saving features so we show the worst-case for idle.

Some SSDs can consume watts of power at idle while better-suited ones sip just milliwatts. Average workload power consumption and max consumption are two other aspects of power consumption but performance-per-watt, or efficiency, is more important. A drive might consume more power during any given workload but accomplishing a task faster allows the drive to drop into an idle state more quickly, ultimately saving energy.

For temperature recording we currently poll the drive’s primary composite sensor during testing with a ~22°C ambient. Our testing is rigorous enough to heat the drive to a realistic ceiling temperature but real-world temperatures will vary due to the environment and workload factors.

The NAS 800 is not terribly efficient by Gen 5 standards, or even Gen 4, coming in under the Black SN850X. This is OK and explained by the fact that the drive has a very small pSLC cache. TLC flash is not as performant, so it does less work. Less power is used, but multi-bit programming is less efficient. When placed next to the D60, it becomes clear that the NAS 800’s results aren’t so bad, although the D60 has power-loss protection hardware, which can affect power consumption.

As we said, TLC can mean less power, so this lower level of efficiency does not translate to higher heat production. The drive hit a peak reading below 70 degrees Celsius in our testing, and as the drive is optimized for sustained writes, our type of testing is more relevant than usual. The drive has about 15 degrees of headroom if this reading correlates to the throttling temperature, which is acceptable to us, although certainly a heatsink is not unwelcome.

Test Bench and Testing Notes

We use an Alder Lake platform with most background applications such as indexing, Windows updates, and antivirus disabled in the OS to reduce run-to-run variability. Each SSD is prefilled to 50% capacity and tested as a secondary device. Unless noted, we use active cooling for all SSDs.

Sandisk NAS 800 Bottom Line

The Sandisk NAS 800 is not a drive for everyone. It’s priced too high for that, and its performance distinctly prefers certain workloads. Due to its optimization, it’s also not very power-efficient, so you might not want this in your laptop, either. This is all OK, though, because this drive is great at what it’s made for: NAS workloads.

Its sustained write performance, in particular, is high and consistent. It can also handle all of those writes with its exceptionally high TBW. The base hardware is fantastic in its own right, and there remain hints of that with the drive’s top-tier 4KB QD1 latencies, too. If you have a place for this drive and can afford it, it’s the best retail option out there for NAS.

There are some things the NAS 800 can’t do, though. It lacks power-loss protection hardware, like an array of capacitors. The D60 has these, and it’s one of the few retail options avialable with that feature. The NAS 800 is also not an ultra-low-latency option on par with a pSLC drive, or one with extreme endurance like the PNY LX3030, but that’s moot with no real products like that currently on the market.

We would instead look at two other possibilities: One, you go with a Gen 4 drive, or two, you grab an equivalent Gen 5 drive with a standard caching scheme. One downside for either is that you’re not getting the NAS 800’s high TBW. We also think the caching scheme works well for write-heavy workloads. Performance-wise, a Gen 4 drive could work as an alternative for many NAS applications, but we would highlight the NAS 800’s excellent latency as a counterpoint. If you need bandwidth, then there is not much of a substitute, either.

On the power-efficiency front, the NAS 800’s results are underwhelming, but expected. It would be wrong to take our numbers at face value for a drive that writes mostly in TLC mode. It’s plenty efficient for its intended workload, and the drive did not overheat in our testing.

As such, our biggest gripe is the price. We know what this hardware is, and we can account for the firmware optimization and the pSLC cache. That means you’re paying for the endurance rating. Frankly, we’re OK with that because this is one place you want that level of security. Standard drives often have comically high TBW for what users actually do with them, but this drive might actually see some serious writes over years of regular use. If that sounds like you, then you should definitely give the NAS 800 a serious look.

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A creative director just created a AAA version of the classic Minesweeper game that used to come with Windows. Mike Lacher shared his creation on LinkedIn, which he called a “big-budget, triple-A” reboot, with “loot boxes and brand integrations” set to arrive in the first quarter of next year. When you visit the Triple-A Minesweeper page, you’ll be greeted by the classic Minesweeper logo similar to what you’d expect to see on a Windows 95 desktop. But when you double-click on the icon, you’ll be greeted by the usual sweeping audio entrance that you find on big-budget games, alongside a series of logos from the usual suspects — Unreal Engine, Nvidia, Bink Video, and Wwise — before finally seeing the Minesweeper title splash appear across the page.

Once the loading screens finish, you’re immediately transported to the Minesweeper game. But instead of just loading the game window, you’re greeted by the screen as if you’re coming to after being knocked out in a first-person video game. This is where Nora, your apparent handler, calls you “Sweeper” and introduces what you need to do. It also says, “I’m patched into your neural hub,” just like what many sci-fi games do.

If you wait a while before pressing anything, you’re going to be greeted by a series of voice messages from the apparent antagonist, called “The Don,” plus a series of annoying side characters like your apparent best friend “Clyde,” and some scientist telling you to find things for a neural HUD upgrade called “Dr. K.” There’s also a “DJ Dan” calling you a “mysterious hero” on the radio, similar to the radio station that you’d expect in the coming GTA VI. In between the annoying voice messages, you also get this constant internal monologue saying, “Time’s wasting. Better sweep these mines,” and “It’s time to sweep these mines.”

As you play one round of Minesweeper, Nora practically gives away the game with a yellow mark telling you where to press so that you don’t die. But if you’re hard-headed and prefer to step on the mines instead, the game doesn’t end. Instead, you’re just given a red damage marker, just like in Call of Duty. Unfortunately, it’s just a single round, so once you complete the level, you’re presented with the rolling credits.

It’s unclear if Lacher used AI to build this version of Minesweeper, but the final version is apparently a jab at how modern video games hold the player’s hand to get them through the first few rounds, plus all the voices that fill in the dead air to keep the “conversation” going. While they’re designed to be helpful, not every game needs them, so it’s a good idea to have the option to shush them if you want to explore the map in peace. Now, even though Triple-A Minesweeper can get on your nerves if you don’t get through it as quickly as possible, there’s a twist in the ending suggesting a sequel. You'll have to visit the website if you want to find out what the surprise is.

The Nintendo 64 game Super Mario 64 has come to the Microsoft Zune HD, Hackaday reports, through a project that runs natively on the device’s hardware through the unofficial OpenZDK kit, per the repo’s README. A touchscreen controller overlay is drawn over the game’s video, and the game “plays (mostly) at full speed with sound, touch controls and saves,” from the rsheldiii repo, although no ROM is included and one dumped from your own cartridge is required. The Zune HD, a 2009-era media player that rivaled Apple’s iPod, has Nvidia Tegra hardware inside, and the project is built on sm64ex, a fork of the unofficial, decompiled Super Mario 64 PC port.

The Zune HD, part of our 2009 gift guide, was marketed as having a “3.3-inch glass screen” using OLED and touchscreen technology, from Microsoft’s media alert at the time, with Tegra providing the “multimedia muscle,” according to an Nvidia release. The unit was originally priced between $219.99 and $289.99, depending on capacity, and uses the Nvidia Tegra APX 2600 chip. The operating system is Windows CE-based, with third-party games going through Microsoft’s XNA. The Zune was short-lived, with Microsoft halting production in 2011, but an exploit led to OpenZDK coming out that allowed for homebrew.

The implementation depends on native ARM code on top of the Zune HD’s OS, using OpenZDK. The device’s firmware is not modified, but the port, according to the developer, should only be used “at your own risk,” a standard disclaimer. It leverages an OpenGL ES 2 renderer derived from Fast3D with prebuilt shader variants, using Nvidia’s cgc and shaderfix tools, because the Zune’s graphics driver can’t compile OpenGL Shading Language (GLSL) shaders. Blending is compiled into the fragment shaders as well, since the GPU lacks fixed-function blending hardware. These workarounds are what make the project interesting.

The game’s logic runs at 30 ticks a second, but some lag is present when the Zune is unable to keep up. There is also no official FPS number. The game renders at 480x272 in landscape, with the device rotated to match. The audio synthesis runs on its own thread at a higher priority than the game, so it is not impacted by a slower frame rate. The touch control overlay provides a facsimile analog stick as well as the A, B, Z, R, four C, and Start buttons, with customizability for button style and opacity.

The project itself relies on a Super Mario 64 decompilation effort completed by fans in 2019, with a C source that rebuilds a matching ROM. The decompilation doesn’t include all of the game’s assets, and extraction requires a copy of the game. The ROM is read on the PC during the build, and the finished game can later be moved over to the device through USB. The build runs on Docker in Linux, so no Windows PC is required. The repo has no releases, and the port, which applies 14 patches to a pinned version of sm64ex, has only been tested on firmware 4.5.

The full PC port arrived in May 2020, of which sm64ex is a fork with extra features, such as mouse look and a cheats menu. Nintendo’s legal representatives responded quickly, targeting “sites hosting the compiled version of the Mario 64 PC port” and at least one gameplay video, Video Games Chronicle reported. However, a number of ports have found their way out for the 3DS, Wii U, PS2, PlayStation and PS Vita, Dreamcast, Nintendo DS and DSi, the web, and now the Zune HD.

The project shows what could have been on the Zune HD had Microsoft been less restrictive with development. Ports are nothing new, but the number has been increasing lately, potentially due to the wider availability of powerful AI tools; the repo’s first commit ends “Co-Authored-By: Claude Opus 5.5,” so AI was used at least in part. An example of something different is a decent Doom port to an $8,000 Hasselblad X2D camera, born from firmware research, showing there are multiple pathways to the same goal.

When it comes to the gaming industry, the billions bandied about regarding AAA titles often lead many to think that if your game scores a hit, you're essentially set for life. Unfortunately, the sad reality is that indie developers often have to end up pinching pennies or outright in a deficit despite strong sales. Omer Develioğlu, the co-founder of Northend Games, offered a candid breakdown of how $560,000 in income over five years for sales of his games ended up as just $134,000 split two ways, with $73,000 in his and the co-founder's pockets. In the end, the co-creator got only $15,000 per year and continues to drive his 2012 Mazda, hardly the riches one would expect.

The $560,000 gross figure refers to sales for two titles: Northend Tower Defense and Deepstone Rift (Early Access), both sold on Steam, for a grand total of 135,000 units. In an accompanying video, Develioğlu mentions that an impressive 53.3% of sales come directly from China.

Unfortunately, he also says that the country's customers are very demanding, and that the refund rate there is disproportionately large. Thus, $134,000 goes right away towards said refunds, with a rate of 22%, "way above" the purported standard of 10-15%. For what it's worth, the Chinese refund rate is corroborated by both older and recent third-party figures. Current tally: $426,000.

Then there's Steam itself. The platform is widely beloved by gamers everywhere for its value-add features like the Workshop, but also for the basic notion of not making the other platforms' questionable business decisions. Having said that, Gabe Newell's enterprise has also been on the receiving end of criticism thanks to fees starting at 30%, which only go down for amounts over $10 million and beyond. As Develioğlu's games are nowhere near those figures, 30% it is: $127,000 for Steam, and $297,000 for the devs... or so you'd think.

Next up, there's the U.S. withholding taxes. The developer lived in Iraq and moved to Thailand, a country that has a tax agreement with the U.S. to prevent double taxation. Even still, Uncle Sam's slice is 5%, bringing the total down to $287,300.

Now, it's time for one of the more controversial aspects: the publisher's cut. According to Develioğlu, his Asian publisher took care of PR, distribution, and marketing in the China, Japan, and South Korea regions. The fact that the majority of the game's sales came from China could mean the publisher did a good job, but the cut was hefty: $115,000, seemingly in a sliding scale, leaving take-home at $172,000.... before local taxes.

Develioğlu doesn't clear up what the publisher's cut, perhaps due to an NDA. The most logical option is that the $115,000 fee refers to the sales in Asian countries. Given that 53.3% of sales are in China, and that the publisher also handled Japan and Korea, this would mean a percentage cut of around 35-40% of net income.

As an exercise, we ran the figures assuming no publisher, only 15% of sales in Asia, and a lower refund rate. Interestingly, the net amount was nearly the same.

Thailand's offices also want in on the action, and take 15% away from Northend Studios, a mercifully low rate as it's a digital product. Even still, it's $26,000 off the cash pile, now reduced to $146,000.

Finally, Develioğlu split this 50/50 with his co-founder at Northend Games, for a grand personal total of $73,000 for five years' work, or roughly $15,000 per year of work. As the developer notes, he lives in Thailand, and this comparatively small amount is still more than the country's average wage, letting him make games as a full-time occupation. (For reference, the average wage in Thailand is around $5,280 a year).

But as he says, despite making half a million dollars in sales, instead of buying a Lamborghini, he still drives a 2012 Mazda.

Over 3,400 “victim servers” were hit by cryptomining malware PoeLLM during a campaign named Canto Incognito, tracked since April 2026, Lumen’s cybersecurity research team Black Lotus Labs reports. The malware’s “command-and-control (C2) mechanism” used address encoding through four words in a two-stanza poem on GitHub, altered 11 times so far, to direct affected hosts to new C2 servers. Most of those hit look to be running “vulnerable versions of open-source AI/LLM services, such as LiteLLM and Ollama,” despite an April LiteLLM fix that probably patched the exploitation path.

The malware’s payload consists of XMRig and Iron miners, connected to Kryptex mining infrastructure, with infected servers becoming scanners and exploit servers. The “primary commonality amongst the first 900 victims” was contact with “an endpoint for the Russian crypto mining service,” Lumen says. This indicates that it may be financially motivated. “AI infrastructure is becoming an attractive target” because exposed AI services may contain valuable data and hardware access, especially GPUs. In the meantime, it has “blocked all traffic to and from the PoeLLM C2 servers.”

The primary targets are LiteLLM, a proxy server (AI Gateway) to call LLM APIs, a way companies can route their apps to many models through one endpoint, and Gotenberg, a Docker-based API for PDF conversion, which has a guide warning not to expose it to the internet. Also hit are Ollama, which allows you to run open-weight models on your own hardware, although it is not internet-exposed by default, and Gitea, a self-hosted Git platform. Ivanti Sentry, an enterprise gateway appliance, “may also have been targeted,” and one instance was how Lumen discovered the campaign.

Although the malware’s methodology involves leveraging poetry, this is only for pointing the infected servers to the C2 server. It is not a form of an AI jailbreak through harmful requests or prompt injection, or what is known as “adversarial poetry,” described in a paper last year.

The poem, “On the Nature of Connection,” was first committed in April, with each new version pointing to a new C2 server. The malware is able to decode the new address by pulling specific words and converting them into an IPv4 address. Lumen says that “the malware creator has not changed the pattern used in deciphering the poem” at the time of reporting. Using a poem likely aided in obfuscation as it is “a perfect vehicle for hiding an important message,” the researchers told The Register.

The malware is “deployed through vulnerability exploitation of publicly exposed services,” with broad scanning beginning in May. For LiteLLM, a crafted POST to the connection endpoint “was likely the exploitation path,” based on a flaw where two endpoints would run a supplied command on the host with no role check (CVE-2026-42271), which CISA added to its list of exploited vulnerabilities in June. Lumen didn’t detail the methods for Ollama, Gotenberg, and Gitea.

If you want to check your own systems, look at connection logs for the indicators of compromise listed on Lumen’s GitHub page. Be sure to audit external exposure when installing any open-source tool and close unnecessary ports. Patch any and all network devices. Follow the individual advisories for the vulnerable products — LiteLLM 1.83.7 or later and Ivanti Sentry R10.5.2, R10.6.2, or R10.7.1.

When Lumen published its report, three of the 12 C2 servers were still active and the campaign “continues to infect new victims.” The firm “will continue to monitor for new traffic.” More attacks like this seem likely: Lumen says enterprise attack surfaces are “expanding rapidly as AI infrastructure grows.”

California is taking another swing at banning 3D-printed “ghost guns,” and this time the target is one of the world’s largest manufacturers of 3D printing filament. Polymaker LLC, headquartered in Shanghai with U.S. operations based in Houston, was named in a civil lawsuit filed October 5, 2026, by San Diego County Counsel on behalf of the People of the State of California. The complaint alleges that Polymaker marketed its filament in such a way as to appeal to gun enthusiasts and thus transform harmless PLA into a regulated “firearm precursor part.”

Under California law, a firearm precursor part is “defined to include any article marketed or sold to the public to become or be used as the frame or receiver of a functional firearm once completed, assembled or converted,” according to the civil complaint filed in San Diego County Superior Court. The County seeks disgorgement of profits, civil penalties and injunctive relief.

The complaint acknowledges that 3D printing filament itself is not illegal. But prosecutors argue that Polymaker actively cultivated and monetized the “ghost gun” community by supporting and then hiring Sean Aranda, who goes by The 3D Print General on social media. Aranda, a 3D printing expert, book author, and gun enthusiast, was banned from YouTube in 2023 over firearm policy violations. His YouTube channel at the time had 123K subs. Polymaker, which had been sponsoring his channel with a special edition creator spool of khaki colored PLA Pro, came to his rescue with a job offer. He became the Head of Customer Experience, which entailed fostering Polymaker’s online community and attending community festivals with the company. He is now a Senior Technical Account Manager for Polymaker.

Aranda is mentioned 65 times in the 39-page People v. Polymaker complaint. The prosecution implies that Aranda was specifically hired for his connection to the 3D printing gun community and not that he was simply a qualified individual searching for a job away from content creation.

The prosecution attempts to link a common marketing tactic used within the online creator community to the illegal proliferation of ghost guns: affiliate links. Affiliate links are used by content creators to promote the products they use, be it spools of PLA, energy drinks, or dog food. When an audience member clicks a link and makes a purchase, the content creator is awarded a small percentage of the sale.

Polymaker supports all manner of 3D printing content creators, and the application for affiliate links is publicly posted on its website. The application asks for your name, location, and number of followers on assorted platforms. It does not ask what type of content you create or how big your audience might be. “Whether you run a YouTube channel, a TikTok account, or a niche 3D printing blog, you're welcome here. If you love Polymaker, you qualify.”

The lawsuit is presented by San Diego County’s new Consumer Fairness and Public Protection Division. If it prevails, the ramifications will extend far beyond 3D-printed firearms. If a manufacturer in Texas can be held civilly liable in California because a YouTuber used that product to do something that is not against the law in their home state, every raw material supplier, software developer, and desktop hardware manufacturer operating in the digital age could find itself in the crosshairs.

Brandon Thomas, developer of ArtCraft, a suite of open-source creative tools meant to replicate Adobe applications for free, has now announced apps to replace Microsoft Office tools such as Excel, PowerPoint, and Word, respectively, named GridCraft, DeckCraft, and WordCraft, that are created with Claude. Thomas has shared his new clones to ArtCraft GitHub, making them free for all to download.

After our previous story covering ArtCraft, we have since discovered that u/ai_art_is_art is Brandon Thomas, a highly talented software engineer with 15 years of experience under his belt. After his ArtCraft project became popular, many criticisms followed about vibecoded software and AI slop, to which Brandon responded on his X account, saying that he does know how to code.

One of the biggest pain points for these software programs is OS compatibility, while Adobe runs on MacOS and Windows, Linux requires additional compatibility layers and Windows emulation to work. One of ArtCraft’s biggest selling points is being able to run all the software across all three platforms while still giving an identical user experience regardless of OS — this is also part of the parity that ArtCraft wants to achieve. While Google provides these tools for free with Google Sheets, Docs, and Slides available on all platforms through a browser, the online-only model takes away the ownership aspect of the software, fearing that one day the tools would suddenly require a subscription and users would not have any say in it.

Microsoft sits among the most criticized companies for its business practices, similar to Adobe. What was once a one-time purchase now comes as a subscription package with various tools that many don’t need; many even have overlapping features and uses, essentially wasting some of the subscription value. It seems that Brandon Thomas is not only creating open-source alternatives, but is also creating a targeted protest against these practices.

ArtCraft’s Discord community is also growing very quickly, with constant recommendations of other software they would like to see, with CADcraft being commonly discussed among 3D printing and engineering enthusiasts who don’t like Autodesk, similar to Microsoft and Adobe. As many free alternatives as there were before the rampant vibecoding, it seems that this growing collection of tools is not only functional, but a message to the large companies as well. Most of these apps are still far from what they intend to replace, however, so we'll have to see how deep this message cuts.

Spain’s Museo de Historia de la Computación unveiled its 18-month-long project to commemorate the 50th anniversary of both the Cray-1’s first operational use in Los Alamos and Apple’s founding. The replica uses 30 Mac Minis, 25 dual-core i5 units, and five quad-core i7 units from 2012-2014, totaling 70 cores that produce a peak of 1.5 TeraFLOPS; a theoretical 9,375x jump from the original Cray-1's 160 MegaFLOPS. After one quad-core machine went offline, the current reported peak sits at 1.3 TeraFLOPS.

The original Cray-1 is considered to be the first commercially successful supercomputer, with 80 systems sold in its heyday. Science and engineering institutions sought it out to churn through gigantic datasets for uses ranging from intense weather prediction and aerodynamics to nuclear physics and structural analysis, among many others.

It was very efficient at these computations thanks to vector processing, a computing technique we take for granted nowadays. Vector computing made this supercomputer so powerful; while most computers still handled tasks one instruction at a time, the Cray-1 could process chunks of numbers in parallel, saving a huge amount of time.

The replica has 70 cores from the 30 Mac Minis, and of course, vector processing has since become the norm and a standard feature of modern CPUs; jumping from a single core to 70 “modern” cores and 50 years' worth of innovation is what Museo de Historia de la Computación wants to showcase in this project. It is not only a replica, but a representation of how far technology has come.

The original version was cooled by a network of refrigerant lines that led to 20-ton refrigeration compressors in a separate room, while the replica is cooled passively through a convection-tower design and is extremely quiet, with only the Ethernet switches making the most noise. The museum plans to use silent switches to make it even quieter.

For visitors to see it in action, the museum also created a retro-style control terminal, akin to what you’d see in old movies: a large metal desk with a keyboard in the middle and multiple screens embedded into a panel spanning the desk, with angled features flanking the screens, completing the 70s control terminal silhouette.

On the screen, you can see it churning away at large matrix multiplication problems, the sort of thing it’s good at. Surprisingly, the team behind it realized they could run the supercomputer on macOS Mojave, which supports MPI (Message Passing Interface), allowing the instructions to spread across several Mac Minis for parallel computing. That's not the end of it, though: the museum plans to start a crowdfunding campaign and buy 70-80 M4 Mac Minis to fill the remaining slots, aiming to enter the TOP500 supercomputers list.

Plan your trip if you want to see it; it’s on permanent display, and the museum is open to the public on Saturdays from 11:30 AM-2:00 PM, but it doesn’t allow tours without a guide, and it's closed during summer, Christmas, January, and February.

A U.S. military-backed company plans to deliver a payload to any point on Earth within 90 minutes by prepositioning assets in space and then calling down delivery vehicles as needed. Sierra Space, a subsidiary of the Sierra Nevada Corporation, has successfully completed two test drops of its Ghost reentry vehicle while carrying a bottle of whiskey and a software-defined radio. According to Aviation Week, the test was conducted using high-altitude balloons that dropped it from 35,000 feet and 68,500 feet.

While this test isn’t as exciting as SpaceX rockets landing on a platform at sea, it’s still an achievement for the team working on the project, as it’s the first test of the vehicle in two years. This demonstration is part of the U.S. Space Command’s Apollo Nexus training exercise, which aims to demonstrate the needed synchronization of multiple units in complex operations.

The test’s payload isn’t just two random items, either. They’ve been specifically selected to show that liquids and sensitive electronics could survive part of the trip back to the surface. “We were able to safely demonstrate that and prove that we could come through all of those environments and then be recoverable in a certain period of time by the team on the ground,” Sierra Space senior vice president Erik Daehler told the publication.

It should be noted that these cargo units aren’t designed to be launched by rockets from another side of the world to be delivered to frontline forces as needed. Instead, they’re designed to stay in orbit for up to five years and then be called down to troops as needed — similar to how Orbital Depots drop down from the sky when called by an SCV in StarCraft II. “Getting something into theater to the warfighter when they need it is critical,” Daehler added. “If you’re in a denied area where you couldn’t get a C-17 or a C-130 to be able to drop into the theater, space is a perfect logistics node.”

The company says that Ghost can deliver its payload to any point on Earth within 90 minutes of getting called down. However, since it is based in space, the military would have to anticipate what supplies are needed, launch them, and keep them in orbit for up to five years. This is similar to how the U.S. pre-positions supply and cargo ships in remote bases across the world like Guam and Diego Garcia, so it could easily deploy materiel where it’s needed. The Ghost is a seemingly small unit, though, with a capacity of just five to ten tons, so it won’t be able to deploy tanks or artillery pieces across the world. Still, it’s a useful device for dropping equipment, ammunition, and supplies, like this in-house assembled drone or microwave counter-drone system, to units that need them without having to risk assets and aircrew.

A dedicated charging solution is a great way to declutter your desk and keep your essential gadgets charged whenever you need them. If you are looking for one, don’t miss this deal on the Ugreen Nexode 100W GaN wall charger. Currently on sale at 27% off on Amazon, the charging adapter is $39.98, down from its original price of $54.99. Thanks to its high power output, it can charge multiple devices at once, making it suitable for your smartphone, tablet, and even your laptop.

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The Ugreen Nexode 100W is a Gallium Nitride (GaN) charger that replaces internal silicon components with a highly efficient semiconductor capable of handling higher voltages. At the same time, it runs cooler and shrinks the power adapter's overall size by up to half. With a foldable plug design, this charger is also compact, making it the perfect companion for your next vacation or business trip.

It features four charging ports, including three USB Type-C ports and one USB Type-A port. One USB Type-C port can deliver up to 100W of power, provided you use a compatible 100W, 5A charging cable. According to Ugreen, this is enough to charge a MacBook Air M3 from zero to 55% in under 30 minutes. The charger works with a wide range of devices, including Apple MacBook Pro and MacBook Air notebooks, iPhones, Samsung Galaxy smartphones, iPads, and handheld consoles like the Steam Deck.

Notably, the company notes that certain Dell and Lenovo laptops may not charge at their maximum supported speeds because of charging-protocol limitations. Always check compatibility with your device before buying. The charger also includes built-in safety measures, including dynamic temperature sensors that monitor heat and an intelligent PWM chip that adjusts power output to help protect connected devices.

At its current discounted price of $39.98 on Amazon, the Ugreen Nexode 100W GaN charger is a worthwhile option for anyone looking to power multiple devices with a single wall adapter.

Masayoshi Son, founder of SoftBank, is seeking up to $100 billion from Gulf investors to establish a fund that would acquire companies and improve their operations using artificial intelligence and robotics, according to the Financial Times. The initiative comes as SoftBank faces growing concerns over its $65 billion investment in OpenAI and its delayed initial public offering (IPO).

Unlike SoftBank's previous investment vehicles, which primarily financed technology companies, the proposed fund would purchase established businesses and introduce AI and other advanced technologies to improve their operations in a bid to improve their value, which is a relatively novel model to make money on AI. Son has reportedly approached influential investors in the Middle East, including senior figures in the United Arab Emirates, in recent weeks to get the money to acquire companies that have not yet adopted AI and/or robotics, but which could substantially improve their business positions by doing so.

Roze, SoftBank's robotics and physical AI division, would reportedly play a major role in these transformations, though exact details remain unclear. Son also intends to eventually take Roze public at a substantial valuation, though neither the fund's establishment nor its financing is guaranteed. In fact, at this point it is unclear whether the fund will only finance acquisitions, or will also finance development of Roze.

SoftBank has already committed approximately $65 billion to OpenAI, and the company remains the crown jewel of its investment strategy. The Japanese company has financed its investments using internal resources, external capital, and borrowing partly secured by its holdings in Arm. Meanwhile, SoftBank's well-being significantly depends on the valuation of OpenAI, which has yet to become a highly profitable company. Despite risks associated with OpenAI valuation, SoftBank continues to pursue aggressive AI expansion.

Son has previously attracted substantial financing from Middle Eastern sovereign wealth funds. Saudi Arabia's Public Investment Fund and Abu Dhabi's Mubadala participated in SoftBank's original $100 billion Vision Fund in 2017. Since its establishment, Vision Fund 1 has accumulated approximately $29 billion in investment gains, whereas Vision Fund 2, which holds the OpenAI investment and is primarily financed by SoftBank, has generated $20.5 billion as of June. Abu Dhabi has also expanded its AI investments through MGX and G42.

Last month, SoftBank raised more than $11 billion through the largest junk bond issuance on record, with yields reaching 9.75% (i.e., very expensive borrowing as risks are high). As of June, the company's net asset value stood at ¥72.3 trillion ($456.57 billion), while its loan-to-value ratio was 13%, considerably below its normal operating limit of 25%. However, a substantial portion of SoftBank's assets is tied to technology companies, including Arm and OpenAI, so a decline in their valuations could increase the company's LTV to uncomfortable levels even without further borrowings.

Son's investment history includes Alibaba's massive success and WeWork's 2023 bankruptcy, so it remains to be seen where the current strategy leads SoftBank.

Ting-Wei “Willy” Sun, a third-party broker and “fixer” who’s been charged alongside Super Micro co-founder Yih-Shyan “Wally” Liaw and sales manager Ruei-Tsang “Steven” Chang for conspiring to unlawfully divert Nvidia AI chips to China, has pleaded guilty to the allegations against him. According to Bloomberg, Sun’s plea comes as part of an agreement with prosecutors, although the details of any possible cooperation arrangement remain undisclosed. Sun is also expected to be sentenced on Sept. 8, 2027, after entering his plea.

The case against the individuals was revealed earlier this year after it was discovered that they diverted Super Micro servers containing Nvidia chips to China. The three were reported to have sent the servers to a Southeast Asian company, which then proceeded to fake the paperwork and create dummy servers for inspectors. Workers then used hair dryers to remove the serial numbers on the real servers to transfer them to the dummy server shells to complete the illusion, while the real servers made their way to China. Further investigation revealed that the three used a Thailand-based corporation to receive the servers, which were then delivered to Alibaba, even as the Chinese tech giant denied receiving the banned Nvidia hardware.

Super Micro has also denied any knowledge of the operation, even as it has netted $2.5 billion in sales since it started in 2024. Nevertheless, the company’s shareholders have sued it, accusing it of concealing its dependence on illicit sales to China. Liaw, on the other hand, has pleaded not guilty to the charges and was released on a $5 million bond. The Super Micro co-founder is set to go to trial this coming Nov. 2, even as the third co-conspirator, Chang, remains a fugitive.

Taiwanese authorities are also building their own case against the illegal shipment of AI chips to China, with the investigators raiding some Super Micro offices and the homes of six individuals. The company, on the other hand, denied that its premises were raided, insisting that it cooperated with the police and provided access to the workstations and gadgets of the employees that were being investigated. It also said that it has been collaborating with both U.S. and Taiwanese authorities over the smuggling investigation, and that it has even fired several employees after completing its own independent investigation. Soon after this, Taiwan indicted nine more people involved in the illegal smuggling of Nvidia B300 GPUs.

Sun’s guilty plea is the latest development in the U.S.’s clampdown on illegal AI chip exports, which happened soon after another tech CEO was arrested in California for smuggling $300 million in Nvidia AI servers to China. These cases show how serious the White House is about protecting its hardware advantage over Beijing in the AI race, even as AI development is facing its own challenges at home.