fidzu : computers

Digg is relaunching again, this time as an AI-focused news aggregator rather than the Reddit-style community site it recently abandoned. TechCrunch reports: On Friday evening, the founder previewed a link to the newly redesigned Digg, which now looks nothing like a Reddit clone and more like the news aggregator it once was. This time around, the site is focused on ranking news -- specifically, AI news to start. In an email to beta testers, the company said the site's goal is to "track the most influential voices in a space" and to surface the news that's actually worth "paying attention to." AI is the area it's testing this idea with, but if successful, Digg will expand to include other topics. The email warned that the site was still raw and "buggy," and was designed more to give users a first look than to serve as its public debut. On the current homepage, Digg showcases four main stories at the top: the most viewed story, a story seeing rising discussion, the fastest-climbing story, and one "In case you missed it" headline. Below that is a ranked list of top stories for the day, complete with engagement metrics like views, comments, likes, and saves. But the twist is that these metrics aren't the ones generated on Digg itself. Instead, Digg is ingesting content from X in real-time to determine what's being discussed, while also performing sentiment analysis, clustering, and signal detection to determine what matters most. [...] The site also ranks the top 1,000 people involved in AI, as well as the top companies and the top politicians focused on AI issues.

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11 May 2026 11:00pm GMT

Production-version patches are coming online and should be installed pronto.

11 May 2026 10:28pm GMT

Audi made sure to consult American tastes for its first full-size SUV.

11 May 2026 10:01pm GMT

Nvidia's real AI moat isn't "a piece of hardware," writes Wired's Sheon Han. It's CUDA: a mature, deeply optimized software ecosystem that keeps machine-learning workloads tied to Nvidia GPUs. An anonymous reader quotes a report from Wired: What sounds like a chemical compound banned by the FDA may be the one true moat in AI. CUDA technically stands for Compute Unified Device Architecture, but much like laser or scuba, no one bothers to expand the acronym; we just say "KOO-duh." So what is this all-important treasure good for? If forced to give a one-word answer: parallelization. Here's a simple example. Let's say we task a machine with filling out a 9x9 multiplication table. Using a computer with a single core, all 81 operations are executed dutifully one by one. But a GPU with nine cores can assign tasks so that each core takes a different column -- one from 1x1 to 1x9, another from 2x1 to 2x9, and so on -- for a ninefold speed gain. Modern GPUs can be even cleverer. For example, if programmed to recognize commutativity -- 7x9 = 9x7 -- they can avoid duplicate work, reducing 81 operations to 45, nearly halving the workload. When a single training run costs a hundred million dollars, every optimization counts. Nvidia's GPUs were originally built to render graphics for video games. In the early 2000s, a Stanford PhD student named Ian Buck, who first got into GPUs as a gamer, realized their architecture could be repurposed for general high-performance computing. He created a programming language called Brook, was hired by Nvidia, and, with John Nickolls, led the development of CUDA. If AI ushers in the age of a permanent white-collar underclass and autonomous weapons, just know that it would all be because someone somewhere playing Doom thought a demon's scrotum should jiggle at 60 frames per second. CUDA is not a programming language in itself but a "platform." I use that weasel word because, not unlike how The New York Times is a newspaper that's also a gaming company, CUDA has, over the years, become a nested bundle of software libraries for AI. Each function shaves nanoseconds off single mathematical operations -- added up, they make GPUs, in industry parlance, go brrr. A modern graphics card is not just a circuit board crammed with chips and memory and fans. It's an elaborate confection of cache hierarchies and specialized units called "tensor cores" and "streaming multiprocessors." In that sense, what chip companies sell is like a professional kitchen, and more cores are akin to more grilling stations. But even a kitchen with 30 grilling stations won't run any faster without a capable head chef deftly assigning tasks -- as CUDA does for GPU cores. To extend the metaphor, hand-tuned CUDA libraries optimized for one matrix operation are the equivalent of kitchen tools designed for a single job and nothing more -- a cherry pitter, a shrimp deveiner -- which are indulgences for home cooks but not if you have 10,000 shrimp guts to yank out. Which brings us back to DeepSeek. Its engineers went below this already deep layer of abstraction to work directly in PTX, a kind of assembly language for Nvidia GPUs. Let's say the task is peeling garlic. An unoptimized GPU would go: "Peel the skin with your fingernails." CUDA can instruct: "Smash the clove with the flat of a knife." PTX lets you dictate every sub-instruction: "Lift the blade 2.35 inches above the cutting board, make it parallel to the clove's equator, and strike downward with your palm at a force of 36.2 newtons." "You can begin to see why CUDA is so valuable to Nvidia -- and so hard for anyone else to touch," writes Han. "Tuning GPU performance is a gnarly problem. You can't just conscript some tender-footed undergrad on Market Street, hand them a Claude Max plan, and expect them to hack GPU kernels. Writing at this level is a grindsome enterprise -- unless you're a cracker-jack programmer at DeepSeek..." Han goes on to argue that rivals like AMD and Intel offer competitive specs on paper, but their software stacks have struggled with bugs, compatibility issues, and weak adoption. As a result, Nvidia has built an Apple-like moat around AI computing, leaving the industry dependent on its expensive hardware.

Read more of this story at Slashdot.

11 May 2026 10:00pm GMT

cURL creator Daniel Stenberg says Anthropic's hyped Mythos bug-hunting model found only one confirmed low-severity vulnerability in cURL, plus a few non-security bugs, after he expected a much longer list. He argues Mythos may be useful, but not meaningfully beyond other modern AI code-analysis tools. "My personal conclusion can however not end up with anything else than that the big hype around this model so far was primarily marketing," Stenberg said a blog post. "I see no evidence that this setup finds issues to any particular higher or more advanced degree than the other tools have done before Mythos." He went on to call Mythos "an amazingly successful marketing stunt for sure." The Register reports: Stenberg explained in a Monday blog post that he was promised access to Anthropic's Mythos model - sort of - through the AI biz's Project Glasswing program. Part of Glasswing involves giving high-profile open source projects access via the Linux Foundation, but while Stenberg signed up to try Mythos, he said he never actually received direct access to the model. Instead, someone else with access ran Mythos against curl's codebase and later sent him a report. "It's not that I would have a lot of time to explore lots of different prompts and doing deep dive adventures anyway," Stenberg explained. "Getting the tool to generate a first proper scan and analysis would be great, whoever did it." That scan, which analyzed curl's git repository at a recent master-branch commit, was sent back to him earlier this month, and it found just five things that it claimed were "confirmed security vulnerabilities" in cURL. Saying he had expected an extensive list of vulnerabilities, Stenberg wrote that the report "felt like nothing," and that feeling was further validated by a review of Mythos' findings. "Once my curl security team fellows and I had poked on this short list for a number of hours and dug into the details, we had trimmed the list down and were left with one confirmed vulnerability," Stenberg said, bringing us back to the aforementioned number. As for the other four, three turned out to be false positives that pointed out cURL shortcomings already noted in API documentation, while the team deemed the fourth to be just a simple bug. "The single confirmed vulnerability is going to end up a severity low CVE planned to get published in sync with our pending next curl release 8.21.0 in late June," the cURL meister noted. "The flaw is not going to make anyone grasp for breath."

Read more of this story at Slashdot.

11 May 2026 9:00pm GMT

FCC extends waiver allowing routers and drones to get patches for two more years.

11 May 2026 8:48pm GMT

Big news from the Debian release team: Debian is going for reproducible package builds. Aided by the efforts of the Reproducible Builds project, we've decided it's time to say that Debian must ship reproducible packages. Since yesterday, we have enabled our migration software to block migration of new packages that can't be reproduced or existing packages (in testing) that regress in reproducibility. ↫ Paul Gevers Reproducible means, in short, that you can verify that the source code used to build a package is indeed that source code. This provides a layer of defense against people tampering with code or otherwise trying to fiddle with the process between source code and final package on your system. This effort constitutes a tremendous amount of work, but it's massively important.

11 May 2026 9:08am GMT

ymawky is a small, static http web server written entirely in aarch64 assembly for macos. it uses raw darwin syscalls with no libc wrappers, serves static files, supports GET, HEAD, PUT, OPTIONS, DELETE, byte ranges, directory listing, custom error pages, and tries to be as hardened as possible. why? why not? the dream of the 80s is alive in ymawky. everybody has nginx. having apache makes you a square. so why not strip every single convenience layer that computer science has given us since 1957? i wanted to understand how a web server actually works, something i know little about coming from a low-level/systems background. the risks that come up, the problems that need to be solved, the things you don't think about when you're writing python or c. this (probably) won't replace nginx, but it is doing something in the most difficult way possible. ↫ Tony "imtomt" I love this.

11 May 2026 8:55am GMT

Ada is incredibly well designed. One way this shows is that it takes the big, monolithic features of other languages and breaks them down into their constituent parts, so we can choose which portions of those features we want. The example I often reach for to explain this is object-oriented programming. ↫ Christoffer Stjernlöf Exactly what it says on the tin.

11 May 2026 8:50am GMT

Just trying to answer one simple question: What if the terminal was 3D?

11 May 2026 12:00am GMT

Break the pattern today or the loop will repeat tomorrow.

18 Apr 2026 12:00am GMT

My thoughts on AI-assisted programming.

11 Apr 2026 12:00am GMT