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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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.

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MEXICO-STAD (ANP/AFP) - Mexico ziet af van het plan om het schooljaar eerder te beëindigen in verband met het WK voetbal deze zomer. Vorige week maakte het ministerie van Onderwijs bekend dat het overwoog de schoolvakantie veertig dagen eerder te laten beginnen.

Reden voor het plan voor de vervroegde vakantie was zowel het voetbaltoernooi als hittegolven in meerdere staten. Het voorstel stuitte op verzet van verschillende staatsoverheden. Ook het bedrijfsleven en veel ouders waren erop tegen, vanwege hun zorgen over de beschikbaarheid van kinderopvang en de kosten daarvan.

Mexico organiseert het wereldkampioenschap voetbal samen met de Verenigde Staten en Canada. Het WK begint op 11 juni in Mexico-Stad met de wedstrijd Mexico tegen Zuid-Afrika.

WASSENBERG (ANP/DPA) - Bij een schietpartij in de Duitse plaats Wassenberg, vlak bij de Nederlandse grens ter hoogte van Roermond, is maandagavond een man om het leven gekomen. De politie is een klopjacht begonnen op de dader en heeft onder meer een helikopter ingezet, meldt een woordvoerder van de Duitse politie.

De schietpartij vond plaats rond 20.00 uur, melden politiebronnen aan persbureau DPA. Een man zou uit zijn auto zijn gestapt en het slachtoffer hebben doodgeschoten buiten een huis in de plaats. De Duitse krant Bild meldt dat een Duitse militair eerste hulp heeft verleend. Er werd een traumahelikopter ingezet, maar de hulp voor het slachtoffer kwam te laat.

De verdachte zou er vandoor zijn gegaan in een auto, mogelijk met hulp van een handlanger, aldus de politie. Er is volgens de woordvoerder geen gevaar voor de samenleving.

MONTERREY (ANP/BLOOMBERG) - De Mexicaanse politie heeft de leider gearresteerd van een groep die nauwe banden heeft met het beruchte drugskartel Cartel del Noreste. Tijdens de arrestatie werden naast wapens, drugs, auto's en motoren ook zeven tijgers in beslag genomen.

Volgens het Mexicaanse ministerie van Veiligheid, dat een foto van de tijgers deelde, volgde de arrestatie op de inbeslagname van een schip in Tamaulipas. De zaak draait om onder meer benzinesmokkel door criminelen die banden hebben met Cartel del Noreste. Het kartel werd vorig jaar door de Amerikaanse president Donald Trump op de lijst met terroristische organisaties gezet.

Exotische dieren worden in de Mexicaanse kartelwereld gebruikt als statussymbool en afschrikmiddel. In een Amerikaanse aanklacht tegen de zoons van de beruchte kartelbaas El Chapo uit 2023 werden zij ervan beschuldigd enkele van hun slachtoffers "dood of levend" aan hun tijgers te hebben gevoerd.

Greg Adams Photography posted a photo:

Remnants of the 1976 Bicentennial paint job on an old SEPTA trolley rusting in the woods in Central PA.

Red Hat Enterprise Linux 10.1 has powered up on board a datacenter orbiting 250 miles or about 400 km above the earth. That RHEL-powered satellite is Voyager’s LEOcloud Space Edge “micro” datacenter, which launched aboard a SpaceX Falcon 9 rocket and hitched a ride on the International Space Station (ISS) back in September. The system is designed to demonstrate the advantages of processing data gathered directly in orbit, rather than sending info back to a terrestrial conventional datacenter. Voyager boasts the reduction in latency makes the system as much as 30x faster than sending all the data back to Earth. Originally developed by LEOcloud prior to its acquisition by Voyager last year, Space Edge is, as its name suggests, a low-power edge compute platform for orbital data processing. Voyager and Red Hat contend that “as commercial and government organizations increase their reliance on space-based data, the ability to process data in orbit is increasingly critical.” And they certainly wouldn’t be the first to suggest that. Faced with power constraints, SpaceX, Amazon, Google, Nvidia and others have all announced plans to put large clusters of AI datacenters in orbit, with some designs aiming to cram 100kW worth of compute onboard a single satellite. The company hasn’t disclosed the hardware used in Voyager’s Space Edge, stating only that it’s a “space-hardened managed cloud infrastructure.” Hardening is certainly a concern for complex electronics operating outside Earth’s atmosphere, where charged particles and radiation can corrupt data or do permanent damage over time. HPE’s Spacebourne compute platform demonstrated many of these challenges during its first mission aboard the ISS in 2017. Over the course of its mission the system, which was composed of mostly off-the-shelf components, suffered several upsets including a power failure and SSDs that failed at an “alarming rate,” HPE's Mark Fernandez said at the time. We’ve reached out to Voyager for comment on the system and what kind of data its “micro” datacenter will process during its mission. We’ll let you know if we hear anything back. It’s safe to assume Space Edge’s compute capacity is limited compared as promotional images show its systems are little larger than a shoebox - and therefore offer less room for components than servers used on earth. What we do know is that RHEL 10.1, along with Red Hat’s Universal Base Image (UBI), are up and running on the ISS. Specifically, Space Edge is running RHEL in image mode, an immutable build of the OS where changes to the most directories will reset to a known good state upon reboot. This means that any issues related to what they call "configuration drift" can be addressed by turning the machine off and back on again, a feature we’ll sure will be popular among many in the IT crowd. Alongside the base OS, Space Edge is also running Red Hat’s UBI container image under Podman, a container runtime interface (CRI) similar to Docker that is rootless and daemonless by default. RHEL 10.1’s arrival in orbit comes amid renewed interest in space driven by the yearning of every great hyperscaler to boldly go and generate tokens where no one has before. Actually, they have, but not at scale. But that’s exactly what SpaceX, Amazon and others have proposed. In pursuit of unlimited power, the two companies have independently filed to put large constellations of AI satellite compute platforms in sun-synchronous orbit. In February, SpaceX filed an application with the Federal Communications Commission to lob a million space-based datacenters into orbit. Meanwhile, Amazon has proposed a slightly smaller constellation with 51,600 data processing satellites. Of course, these plans do have one small problem left to solve. How will they get those sats into orbit for less than the cost of simply building more terrestrial infrastructure? According to one space datacenter startup, the economics of orbital datacenters won’t be viable until the cost to orbit falls to around $10 per kilogram. As of writing, a rideshare aboard a Falcon 9 runs about $7,000 a kilogram. ®

Since Russian invasion, about 20,500 children have been unlawfully deported or forcibly transferred to Russia or Russian-held territories in Ukraine. What we know on day 1,539

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Elke zaterdag verzamelen kinderen met een fysieke of verstandelijke beperking zich bij een revalidatiecentrum in Utrecht om samen te sporten.

Uit straatboekenkastjes in en buiten Nederland haalt Arjen Fortuin steeds een boek, bespreekt het, en geeft het door. Deze week een liefdesroman uit een expatmagneet aan de Main.

Horizontaal: 1. Ode (aan groenten) 5. ‘Close but no __’ 9. Geestdrift 11. In de buurt 12. Past voor pool of lijn 15. Gezondere monteurs? 16. __ Wennemars 17.

Plaats de cijfers 1 tot en met 9 zo in het diagram dat elk cijfer precies één keer voorkomt in elke rij, kolom, de negen vetomrande 3x3 vakken, én de vier grijze 3x3 vakken.