If you're tired of interacting with a bot that spews Nazi propaganda or refers to itself as MechaHitler, you could sign off of Elon Musk's xAI. Or, just to be sure, use an LLM whose training data ends in 1930, three years before the Nazis took power in Germany and nine years before World War II started.

A trio of AI researchers has released a 13-billion-parameter "vintage" language model they call Talkie, which has been trained solely on digital scans of English-language books, newspapers, periodicals, scientific journals, patents, and case law that were published before the end of 1930. Pre-1931 works were chosen because 1930 is the current public domain year in the United States.

In other words, if you're looking for information on World War II, the election of Franklin D. Roosevelt, Amelia Earhart's solo Atlantic flight, or how a microwave oven works, you're out of luck. Ask it about Betty Boop, flappers, the state of the US economy as the Great Depression began, or the sociological effects of the introduction of car radios, and you've come to the right place.

This isn't the first vintage AI model to appear, mind you, with others trained on Victorian literature and pre-1900 scientific texts already out in the world. It is, according to its creators, the largest they are aware of.

These days, the hype is all about AI and robots, but almost a decade ago, the tech du jour was self-driving. You couldn’t swing a lanyard at CES for the latter half of the last decade without hitting a robotaxi; post-COVID, the number of startups has shrunk, but the technology has definitely matured. Go to the right cities—San Francisco and Austin, Texas, spring to mind—and you might see dozens of sensor-festooned vehicles among the downtown traffic.

The pod-like robotaxis belonging to Zoox stand out. Other robotaxi developers are retrofitting existing vehicles like Hyundai Ioniq 5s with sensors and the computing power necessary for self-driving. Zoox, which was bought by Amazon in 2020, did that with its test fleet, but as it starts to offer ride-hailing services—currently in Las Vegas and San Francisco—it’s doing so with a purpose-built design that looks like it just drove off the set of a big-budget sci-fi production.

“A robotaxi is not a car; it’s not a human-driven vehicle, and the requirements are wildly different, although it has to live in that world,” explained Chris Stoffel, director of robot industrial design and studio engineering at Zoox.

It all starts with the sensors, each perched on a little ledge projecting from the top four corners of the robotaxi’s body. From up there, each has an unobstructed, high-level view, giving the Zoox robotaxi good situational awareness, particularly straight ahead. “Because we don’t have a traditional hood, we’ve optimized our frontal coverage in a way that would be nearly impossible on a retrofitted vehicle,” said Zoox director of sensor engineering Ryan McMichaels.

I've yet to see one of these in the wild, so I'm guessing they're geofencing to downtown and UT. Waymos, on the other hand ... I see multiple ones a day, and I don't get out all that much.

Japan’s famously conscientious but overburdened baggage handlers will soon be joined by extra staff at Tokyo’s Haneda airport – although their new colleagues will need to take regular recharging breaks.

Japan Airlines will introduce humanoid robots on a trial basis from the beginning of May, with a view to deploying them permanently as a solution to the country’s chronic labour shortage.

The Chinese-made humanoids will move travellers’ luggage and cargo on the tarmac at Haneda, which handles more than 60 million passengers a year.

JAL and its partner in the initiative, Japan Airlines GMO Internet Group, hope the experiment – which ends in 2028 – will lessen the burden on human employees amid a surge in inbound tourism and forecasts of more severe labour shortages.

In a demonstration for the media this week, a 130cm-tall robot manufactured by Hangzhou-based Unitree was seen tentatively “pushing” cargo on to a conveyer belt next to a JAL passenger plane and waving to an unseen colleague.

A GGUF port of DFlash speculative decoding. Standalone C++/CUDA stack on top of ggml, runs on a single 24 GB RTX 3090, hosts the new Qwen3.6-27B.

~1.98x mean over autoregressive on Qwen3.6 across HumanEval / GSM8K / Math500, with zero retraining.

If you have CUDA 12+ and an NVIDIA GPU like RTX 3090 / 4090 / 5090, then all you need to do is

clone the repo

cd lucebox-hub/dflash
cmake -B build -S . -DCMAKE_BUILD_TYPE=Release
cmake --build build --target test_dflash -j

hf download unsloth/Qwen3.6-27B-GGUF Qwen3.6-27B-Q4_K_M.gguf --local-dir models/

hf download z-lab/Qwen3.6-27B-DFlash --local-dir models/draft/

DFLASH_TARGET=models/Qwen3.6-27B-Q4_K_M.gguf python3 scripts/run.py --prompt "def fibonacci(n):"

Luce DFlash will:

1. Load Qwen3.6-27B Q4_K_M target weights (~16 GB) plus the matched DFlash bf16 draft (~3.46 GB) and run DDTree tree-verify speculative decoding (block size 16, default budget 22, greedy verify).
2. Compress the KV cache to TQ3_0 (3.5 bpv, ~9.7x vs F16) and roll a 4096-slot target_feat ring so 256K context fits in 24 GB. Q4_0 is the legacy path and tops out near 128K.
3. Auto-bump the prefill ubatch from 16 to 192 for prompts past 2048 tokens (~913 tok/s prefill on 13K prompts).
4. Apply sliding-window flash attention at decode (default 2048-token window, 100% speculative acceptance retained) so 60K context still decodes at 89.7 tok/s instead of 25.8 tok/s.
5. Serve over an OpenAI-compatible HTTP endpoint or a local chat REPL.

Running on RTX 3090, Qwen3.6-27B UD-Q4_K_XL (unsloth Dynamic 2.0) target, 10 prompts/dataset, n_gen=256:

Bench AR tok/s DFlash tok/s AL Speedup

HumanEval 34.90 78.16 5.94 2.24x

Math500 35.13 69.77 5.15 1.99x

GSM8K 34.89 59.65 4.43 1.71x

Mean 34.97 69.19 5.17 1.98x

I didn’t know about “mukbangs”—a portmanteau of the Korean words “meongneun” (eating) and “bangsong” (broadcast)—until Enid Frances appeared on my TikTok account’s explore page. Enid, wearing a pink tank top and bright lipstick, taps on the plastic packaging of a chocolate cake. She’s silent, making intense eye contact with us. She lifts the lid. She gulps milk. Her fork enters. The chewing is exaggerated and loud. Two minutes pass, and a quarter of the cake is consumed. Enid flashes a thumbs up.

Videos like Enid’s, seemingly innocuous by nature, have managed to incite international controversy. In 2024, sensationalistic reports surfaced about 24-year-old Pan Xiaoting, who supposedly ate herself to death on air. She promised followers she would consume 10kg of food in one sitting, and was said to have eaten until her stomach tore. Though there was skepticism about the veracity of Xiaoting’s story, additional influencers have since allegedly perished.

China now bans the filming and streaming of mukbangs. The Philippines proposed a similar ban. Meanwhile, in South Korea, a crackdown on public health guidelines to address mukbangs are raising questions about government infringement on freedom of choice. For American viewers, the mukbang is an unregulated and relatively new form of entertainment.

How is this a thing? I rarely enjoy watching people eat across the table.

AI companies are beginning to entertain the possibility that they could cease to exist. This notion was, until recently, more theoretical: A couple of years ago, an ex-OpenAI employee named Leopold Aschenbrenner wrote a lengthy memo speculating that the U.S. government might soon take control of the industry. By 2026 or 2027, Aschenbrenner wrote, an “obvious question” will be circling through the Pentagon and Congress: Do we need a government-led program for artificial general intelligence—an AGI Manhattan Project? He predicted that Washington would decide to go all in on such an effort.

Aschenbrenner may have been prescient. Earlier this year, at the height of the Pentagon’s ugly contract dispute with Anthropic, Secretary of Defense Pete Hegseth warned that he could invoke the Defense Production Act (DPA), a Cold War–era law that he reportedly suggested would allow him to force the AI company to hand over its technology on whatever terms the Pentagon desired. The act is one of numerous levers the Trump administration can pull to direct, or even commandeer, AI companies. And the companies have been giving the administration plenty of reason to consider doing so.

Future bots could help design and carry out biological, nuclear, and chemical warfare. They could be weaponized to take down power grids, monitor congressional emails, and black out major media outlets. These aren’t purely hypothetical concerns: Earlier this month, Anthropic announced it had developed a new AI model, Claude Mythos Preview, capable of orchestrating cyberattacks on the level of elite, state-sponsored hacking cells, potentially putting a private company’s cyber offense on par with that of the CIA and NSA. In an example of Mythos’s power, Anthropic researchers described how the model used a “moderately sophisticated multi-step exploit” to work around restrictions and gain broad internet access, then emailed a researcher—much to his surprise—while he was eating a sandwich in the park.

Washington is getting antsy about the power imbalance. Over the past year, multiple senators have proposed legislation that would order federal agencies to explore “potential nationalization” of AI. Murmurs of possible tactics abound—including more talk within the administration of the DPA after Anthropic’s Mythos announcement, one person with knowledge of such discussions told us. Meanwhile, Silicon Valley is watching carefully. In recent weeks, Elon Musk, OpenAI’s CEO Sam Altman, and Palantir’s CEO Alex Karp have publicly spoken about the possibility of nationalization. Lawyers who represent Silicon Valley’s biggest AI firms are paying attention.

Worth noting, later in the story it's pointed out why full nationalization is vanishingly unlikely, but more federal oversight is likely.

cross-posted from: lemmy.ml/post/46379162

The Kubuntu team is thrilled to announce the release of Kubuntu 26.04 LTS, codenamed “Resolute Raccoon”! As a community-driven flavour of Ubuntu, Kubuntu continues its mission to deliver the cutting-edge KDE software ecosystem on top of Ubuntu’s rock-solid foundation. This Long-Term Support release, aligned with Ubuntu’s two-year LTS cycle, brings together the freshest stable KDE software with the reliability and security users depend on for years to come.

Building on the Ubuntu 26.04 LTS base released today by Canonical, Kubuntu 26.04 introduces Plasma 6.6 as the flagship desktop environment, alongside Qt 6.10.2, KDE Frameworks 6.24.0, and the latest KDE Gear 25.12.3 application suite. We’ve also upgraded to Linux kernel 7.0 for enhanced hardware support and performance. Whether you’re a developer, creator, or everyday user, this release emphasises Wayland maturity, modern security, and seamless integration with the open source world.

Kubuntu 26.04 LTS will receive security updates and critical fixes through April 2029, making it an excellent choice for home users, schools, businesses, and anyone who values a dependable, beautiful desktop.

Kubuntu remains completely free to download, use, and share—empowering our global community to innovate without barriers.

Four Exciting New Features for Kubuntu Users

Here are four standout enhancements that Kubuntu 26.04 LTS brings to your desktop:

• Text Recognition in Spectacle: Capture Text, Not Just Images Spectacle, KDE’s built-in screenshot tool, gains one of its most practical new capabilities in Plasma 6.6: built-in OCR text recognition. Capture any screenshot containing text—a document, a web page, an error dialog, a presentation slide—and Spectacle can analyse the image and convert the visible text into selectable, copyable content, right from within the app. No third-party tools required. Multi-language support means it works for users around the world, and the extracted text copies directly to your clipboard for immediate use. It’s the kind of small feature that quickly becomes indispensable.
• A New On-Screen Keyboard for Touch, Accessibility, and Beyond: Plasma 6.6 introduces a fully integrated on-screen keyboard, making Kubuntu a much stronger choice for touchscreen devices, tablets, and users with accessibility needs. The keyboard supports multiple languages and layouts, adjusts its position intelligently to avoid covering input fields, and is easily accessible via the system tray or accessibility settings. It includes standard keys, function keys, and emoji support, and appears automatically when you tap a text input field on touch-enabled hardware. This addition reflects KDE’s ongoing commitment to making the desktop inclusive and usable for everyone.
• Plasma Wayland - The Default, Fully Supported Session: The Plasma Wayland session is the default and fully supported session in Kubuntu 26.04 LTS, delivering improved security, smoother rendering, and better HiDPI display support. For users who need it for legacy hardware or specific workflows, the plasma-session-x11 package remains available in the Ubuntu archive— but it is not installed by default and is not supported by the Kubuntu team.
• Extensive Theming and Configuration Improvements: Plasma 6.6 brings significant advances to theming and desktop configuration, giving users more expressive control over the look and feel of their environment than ever before. Custom global themes have been expanded, colour scheme handling has been refined throughout the shell and applications, and widget customisation options have been deepened across panels and the desktop. Whether you prefer a polished out-of-the-box experience or enjoy crafting every detail of your workspace, Resolute Raccoon gives you the tools to make Kubuntu truly your own.

What’s New Under the Hood

Beyond these highlights, Kubuntu 26.04 LTS inherits Ubuntu’s robust platform upgrades:

• Linux Kernel 7.0: Updated from 6.8, the kernel now enables crash dumps by default on desktop installations, brings the new sched_ext scheduling system for hot-swappable eBPF-based schedulers, and retires the linux-lowlatency package in favour of a leaner lowlatency-kernel tuning approach on top of linux-generic.
• KDE Applications 25.12.3: All KDE Gear applications have been updated to 25.12.3, a stable release, including Dolphin, Konsole, Okular, Kdenlive, and more.
• Qt 6 Ecosystem: Qt 6.10.2 and KDE Frameworks 6.24.0 power the desktop. Qt5 (5.15.1cool1.gif and KDE Frameworks 5 (5.116.0) legacy packages remain in the archive for applications that have not yet completed their Qt6 port.
• Firefox 150 and LibreOffice 26.2: Both core applications are updated, with Firefox delivered as a Snap from the Snap Store and LibreOffice included in the full installation.
• sudo-rs by default: Ubuntu 26.04 LTS ships sudo-rs, a memory-safe Rust reimplementation of sudo, as the default sudo provider — improving security without changing everyday usage.
• Rust-powered core utilities: The core OS utilities are now provided by rust-coreutils, bringing performance improvements and memory safety to fundamental command-line tools.
• VA-API hardware video acceleration: AMD and Intel users now get hardware-accelerated video encoding and decoding by default via the Video Acceleration API — great for media playback and video work.
• Updated developer toolchain: GCC 15.2, Python 3.14, Rust 1.93, Golang 1.26, LLVM 21, OpenJDK 25, and .NET 10 are all included and ready to use.
• APT 3.2: The package manager gains a new dependency solver, OpenSSL-backed TLS, an automatic pager for commands like apt show and apt list and history and rollback commands like apt history-list or apt history-rollback, which were previously found only in separate apt-rollback tool.

This release marks another milestone in Kubuntu’s long journey as one of Ubuntu’s most beloved flavours. A huge thank you to our volunteer contributors, testers, bug reporters, and the upstream KDE and Ubuntu teams for making Resolute Raccoon a reality.

People still use large handcarts in so-called “developing countries”. However, they can be just as useful again in the large cities of the industrialized world, as I can testify after using one for a couple of months. Last autumn, I received an internship application from Kozimo, who studies at the Design Academy Eindhoven. In his application, Kozimo sent a video of a large handcart he made, which he was driving on the streets of Rotterdam, the Netherlands.

I have always dreamt of a handcart. I have never owned a car, and the only times I miss one are when I have to move stuff, something which has become increasingly common lately. Consequently, I proposed to Kozimo to build a handcart for me.

Now, I can no longer imagine living without it. I have used the vehicle to move houses and offices, pick up materials and objects I bought online, new or second-hand, and transport workshop and event materials (bike generators, solar panels, solar ovens, books, sound systems). I have done the same for friends. During these trips, I often took home materials, furniture, or objects that I found for free on the streets of Barcelona.

Unlike a van or a car, my handcart doesn’t need gasoline, electricity, or batteries, making it entirely independent from energy infrastructures. Neither do I need to pay taxes and insurance. The handcart is a very democratic vehicle. It allows anyone to carry a load wherever they want, while older, less affordable cars and vans are no longer allowed to enter city centers due to the installation of Low Emission Zones.

It would make a lot of sense to offer vehicles like this at community centers, where they are available for all neighbors to use when needed. Few people would need a handcart each day, and communal use would solve the parking problem. Although our handcart can also be parked vertically, it won’t fit in most apartments.

If charging speed is one of the major stumbling blocks preventing people from considering an electric vehicle, then ChargePoint’s new Express Solo DC fast charger is a step in the right direction. It has been designed to be compact and work with DC power, making it easy to install in tight spaces. Oh, and it maxes out at a hefty 600 kW.

As we saw with yesterday’s news from CATL, EV batteries are getting more and more capable by the day. Increasing power can reduce charge times, as long as the battery can take it—BYD’s new Blade battery can charge at up to 1.5 MW, and megawatt chargers are already common across China.

Once again, you can see how badly the US is lagging in EVs. Most Tesla Superchargers max out at 250 kW, Electrify America stops at 350 kW, and even the new IONNA stations top out at 400 kW per plug. So the Express Solo’s 600 kW—as powerful as a Formula E pit stop—sets a new benchmark, particularly for a standalone charger that could live in an urban gas station or convenience store parking lot.

New gas projects linked to just 11 data center campuses around the US have the potential to create more greenhouse gases than the country of Morocco emitted in 2024. Emissions estimates from air permit documents examined by WIRED show that these natural gas projects—which are being built to power data centers to serve some of the US’s most powerful AI companies, including OpenAI, Meta, Microsoft, and xAI—have the potential to emit more than 129 million tons of greenhouse gases per year.

As tech companies race to secure massive power deals to build out hundreds of data centers across the country, these projects represent just the tip of the iceberg when it comes to the potential climate cost of the AI boom.

The infrastructure on this list of large natural gas projects reviewed by WIRED is being developed to largely bypass the grid and provide power solely for data centers, a trend known as behind-the-meter power. As data center developers face long waits for connections to traditional utilities, and amid mounting public resistance to the possibility of higher energy bills, making their own power is becoming an increasingly popular option. These projects have either been announced or are under construction, with companies already submitting air permit application materials with state agencies.

Earlier this year, we committed to publishing a reader-facing explanation of how Ars Technica uses, and doesn’t use, generative AI. Translating our internal policy into a reader-facing document that meets our standards for clarity and precision took longer than I’d have liked, but I wanted to get it right rather than get it out fast. That document is now live, and you can find it below (and also linked in the footer of most pages on the site).

Our approach comes from two convictions: that AI cannot replace human insight, creativity, and ingenuity, and that these tools, used well, can help professionals do better work. From those starting points, it was always clear what we wouldn’t allow. AI would not become the author, the illustrator, or the videographer. These tools are best used by professionals in the service of their profession, not as a clever end run around it, and certainly not as a path to eventually replacing it.

The short version: Ars Technica is written by humans. Our reporting, analysis, and commentary are human-authored. Where we use AI tools in our workflow, we use them with standards and oversight, and humans make every editorial decision. Our policy covers how we handle text, research, source attribution, images, audio, and video.

These standards aren’t new. They’ve governed our editorial work since AI tooling became available. What’s new is making them visible to you. You deserve to see the rules we hold ourselves to, not just trust that they exist.

As promised after the Benj Edwards fiasco. Nice to see them following through.