Of all the apps you can misclick in, hitting the wrong button during an online meeting is one of the worst. You can accidentally show your webcam, hang up on the call, stick your hand in the air, and even leave the call altogether, just from a simple aiming problem. And when they do happen, you don't forget about it for weeks after.

One of the biggest benefits of using Linux is that it's a very much an operating system that gets out of your way. As such, when something on Linux doesn't respect people's choices and keeps bothering them, the developers are sure to know about it. And as much as I love KDE Plasma, there is one thing that irks me when managing the clipboard: the constant asking if I want to clear starred items.

Google's AI Overviews are running into an interesting problem right now. Earlier on Friday, if you searched for the term "disregard," the AI Overview section would include a response like what you'd see from a more traditional AI chatbot instead of the typical AI summary, as spotted on X. As you can see in the image at the top of this story, I got an AI Overview response that said, "Got it. If you need anything else or have a new question later, just let me know!"As of Friday afternoon, however, Google isn't showing an AI Overview for the term "disregard" at all - instead, it shows a list of news stories about the issue first. Google hasn' …Read the full story at The Verge.

The local models that get talked about most tend to sit in the 7B to 12B range, which is also where most setups land if you've got decent hardware. Anything smaller usually gets written off as a toy before it gets a fair try. But not everyone has 16GB+ of VRAM to work with, and the really tiny models, the under-2B crowd, are getting more capable than their size suggests, and I wanted to see if they're worth poking at despite being able to run the mid-size ones.

Just a stuffed deer having the time of his life. | Image: Gemini / The Verge Last year I deepfaked my kid's stuffed animal to make it look like his plush deer was on vacation.It was an experiment to see if I could re-create the events depicted in a Gemini ad Google was running, and I never showed the videos of Buddy the deer on his adventures to my four-year-old. But it was a revealing exercise that made me think a lot about the difference between some harmless fun with generative AI and full-on slop. Maybe that Venn diagram is a perfect circle! Maybe not. But what I know for sure is that the tools to make realistic videos are surprisingly good, requiring surprisingly little effort and know-how. And that trend is c …Read the full story at The Verge.

If you’ve worked on DIY computing projects in the late 2010s, you’ve definitely heard of the Raspberry Pi, if not own a few single-board computers belonging to this family. After all, their tiny form-factor, affordable price tags, and solid compatibility with popular Linux distros (and packages) made them the perfect tinkering companions. But that’s all in the past now.

If I remember correctly, I've had USB ports on my monitors since 2017, but I never thought of actually using them. The ports on the motherboard and case always proved to be enough, leaving no reason for me to consider the onboard USB ports on the monitor. When I switched to wireless peripherals, however, my monitor's USB hub became a lifesaver. It solved the annoying problem of wireless interference between all the dongles by allowing me to create enough distance between them. Even if you don't have wired peripherals, using the monitor's USB hub provides a more convenient and clutter-free way to connect them. Your monitor's USB ports are meant for convenience instead of peak performance, so stop ignoring them.

The AMS has always been one of Bambu Lab’s best ideas, but also one of its messiest workflows. It can swap materials, keep spools ready, and turn a single printer into a much more flexible machine. Yet the software side has never quite felt as polished as the hardware promised. For a system built around loading multiple spools at once, keeping track of those spools has often been weirdly manual.

For the longest time, the conversation around local AI models revolved around quality. They were either too slow, too dumb, too small, or too incapable to match what the titans over at OpenAI, Anthropic, and Google are doing with ChatGPT, Claude, and Gemini, respectively. That gap, however, is shrinking a lot faster than most people realize, even though it does exist in some areas. For the most part, though, modern local models have become genuinely impressive, and are capable of writing, summarizing, coding, and reasoning on capable hardware, of course.

Most of the small reasoning models that have shipped in the past year are variations on a theme. A familiar transformer backbone, a Mixture-of-Experts wrapper, grouped-query attention or something like Gated DeltaNet in Qwen's case for a smaller KV cache, and a heavy reinforcement learning stage at the end. Performance improves year on year, but the architecture of what's actually running is similar to the shape it was when DeepSeek R1 arrived.

In an ideal world, you'd be able to use any controller on any device. Different controller designers bring different things to the table, and having the option to pick your favorite and use it on any console or PC you own would be a huge benefit. At the very least, it would stop me needing to re-learn where the A and B buttons are when I go between an Xbox and a Switch controller.

Anthropic has now built persistent memory into Claude Code. It works in two ways. First, there's Auto Memory, where Claude automatically saves useful project context, patterns, and preferences. Second, there's the CLAUDE.md file, which stores project instructions and context that get loaded into future sessions.