Matmos are an incredibly accomplished duo between their own solo records like the masterpiece A Chance to Cut Is a Chance to Cure and production classic Bjork records like Vespertine. But Drew Daniel, one half of Matmos, is fiendishly prolific. When he's not literally dreaming up new viral music genres, he's also putting out records under the banner of The Soft Pink Truth. Where Matmos usually focuses on a specific musical experiment - using only samples of medical procedures or building instruments out of PVC tubing - Soft Pink Truth goes wherever Daniel's whims take him. That might be a house record. It might be a bunch of black metal co …Read the full story at The Verge.

Lorde performing at the 2026 Governors Ball. | Photo: Siegfried Anthony/Billboard via Getty Images Lorde was performing at the Real Cool Festival in Madrid on Thursday and took some time during her set to speak out against AI glasses. While she didn't specify any brands in particular, it's likely she was taking a shot at festival sponsor Ray-Ban, which has collaborated with Meta on a pair of AI smartglasses. The comments were captured in videos shared to social media. After thanking the crowd for being there and taking part in "something real," she said that it was increasingly hard to know is and isn't real, before saying "You don't know if someone is wearing sunglasses or if they're wearing those fucked up fucking… Can I just say, for …Read the full story at The Verge.

My home lab servers basically never break, and my laptop used to all the time. That's bugged me for years because my servers are always on, run more varied software, and serve more users (okay, one user, but he's very demanding). They also get far less attention day to day, but that was the very reason they survived. The difference wasn't the hardware or the distro. It was that my Proxmox boxes were maintained on a schedule, and my laptop got updated whenever the notification icon annoyed me enough to click it.

Started with just two stacks less than a year ago, and they had already grown over 20, and I was adding a few every week. The majority of them were permanent ones I used regularly, and some were experimental. And for most of them, I didn’t even remember the configuration I had done by hand in the first place because once deployed, I rarely visited them until they asked for my attention. Compose files could tell me how Docker was running it, but those files couldn’t tell me why I made those decisions in the first place.

The sinking feeling of waking up to an unresponsive computer is one I cannot describe. I hit the power button, and instead of my desktop loading, I was greeted by an inaccessible boot device prompt. My massive high-capacity primary SSD died without warning, instantly vaporizing 4TB worth of files, including critical documents, years of local project data, setup archives, and workspace history.

There was a time when building a PC was the most economical way to play games, because given enough time, it would nearly always offer a tangible return on your investment. Even if consoles offered better upfront value, a carefully curated list of parts would deliver more performance for the money while creating a pathway for future upgrades.

The prevailing market conditions have priced out a big chunk of PC gamers from upgrading their builds. Even if you don't need more memory or storage right now, buying a current-gen GPU that doesn't suck will cost you a pretty penny, due in no small part to price hikes hitting graphics cards as well. That said, if you always wanted to put together a second PC as a dedicated budget gaming rig with an older GPU or a retro gaming box with an inexpensive GPU, you can still do that. If you have around $150 to spend on a pre-owned graphics card, eBay is still a great place to hunt for deals. I've deliberately kept GPUs belonging to the RTX 30, RX 6000, and newer series out of this list, since I don't consider them "old" right now. From the RTX 2080 Super and GTX 1080 Ti for excellent budget gaming in 2026 titles to the RX 580 for retro gaming, this list has something for every budget.

Ever since I upgraded to an RTX 4090, I've been trying to game at native 4K whenever possible. After all, I've always wanted to experience AAA titles at the highest quality possible. As long as I was getting over 60FPS, I didn't feel the need to use DLSS upscaling or frame generation. To me, native 4K at over 60FPS always felt like the gold standard for PC gaming, or at least it was supposed to. In fact, I was willing to compromise on ray tracing in supported games if it meant I didn't have to rely on DLSS.

Browser security warnings used to feel like part of the home lab experience. I’d type in an IP address, get the usual scary interstitial, click through it, and then act like that was perfectly normal because the server was mine. It was only on my network, after all, so I told myself it wasn’t a big deal. After enough times, though, that warning stopped feeling useful and started feeling like one more thing I’d trained myself to ignore.

I've spent years telling myself a big OLED was the endgame for movie watching, and then a laser projector landed on my coffee table and ruined the plan. My XGIMI Titan Noir Max review covers the specific unit doing the ruining, but this piece is about the bigger argument: for movies, specifically movies, a modern laser projector beats a QLED or OLED TV. I know how that sounds coming from someone who also knows projector brightness claims get inflated, so believe me, I went into this ready to be disappointed. I wasn't.

Apple's self-driving car program never really got off the ground, but it may have been what made the company's chips the powerful AI performers they are. Early in the development of the self-driving platform, Apple realized that it would need powerful on-device AI processing. While the car processor was never finished, as Mark Gurman details in his latest Power On newsletter, it did lead to the development of the Neural Engine, the backbone of Apple's on-device AI processing. The Neural Engine made its debut with the iPhone X and the A11 Bionic. In those early days, it was primarily used for computer vision, powering FaceID, Animoji, and a …Read the full story at The Verge.

Choosing the right locally-deployed large language model can be a bit of a hassle. Bulky LLMs, for example, can deliver accurate results, but you’ll need decent hardware to get them up and running. I use Mixture-of-Experts models for most of my LLM-heavy tasks, but even with their optimized nature, I can’t use MoE offloading to run 35B clankers on iGPU-laden systems with less than 8GB of memory.