Naast de LIAP-residentie (waar ik zit) en veeeeeel kunstenaarsateliers, zijn er op het Spinnerei complex wel veertien (!) galeries en een Halle 14 / Centrum voor hedendaagse kunst met een bibliotheek gehuisvest. Ik ga op [Meer...]

Microsoft has released a public preview of Windows Subsystem for Linux (WSL) containers, adding a built-in command-line tool and API for running Linux containers directly inside Windows applications without third-party software. The update also introduces faster file access, improved networking and memory management, plus integration with Defender, Intune, and VS Code. The Register reports: WSL has always been a handy way to run Linux workloads from Windows, and is particularly convenient for Linux developers who must comply with corporate edicts to use a Windows device. The CLI for end-to-end container workflows furthers this. Microsoft stated, "WSL containers make it easier for developers and organizations to build, test, and run containerized workloads while benefiting from the security, manageability, and integration of the Windows platform."
Alternatively, you could run your preferred Linux distribution natively, but that might not be an option, particularly if an organization is keen on the "security, manageability, and integration of the Windows platform." And this is an important point. WSL's existing Microsoft Defender for Endpoint (MDE) has been updated (in private preview) to be aware of Linux container events, and there are settings in Intune for managing WSL containers. Support is also in a pre-release version of VS Code, where the Docker path in the dev container settings can be changed to wslc.

There is also a new default file system for WSL container that Microsoft claims makes Windows file access twice the speed. So, going from terribly slow to just slow? We'll wait until general availability is reached before passing judgment. There's a new default networking mode to improve compatibility and better memory reclaim techniques. However, none of these tweaks will be enabled by default in WSL. Microsoft wrote, "Since these changes touch mission critical paths like file system access and network, for now they are enabled just in WSL container."

Read more of this story at Slashdot.

Home Office assessment shows new limits on human rights route based on family ties could result in another 11,700 claims turned down

More than half of the people whose asylum and visa claims will be rejected under tightened human rights laws will continue to live in the UK, according to the Home Office’s own assessment.

Documents released on Tuesday show that plans to set new limits on article 8 of the European convention on human rights are expected to result in another 11,700 people having their claims rejected.

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The boy, identified as Klieber Moran, was the only reported survivor found on the sixth day of the ongoing search

A child has been rescued from the rubble in Venezuela, six days since the country was hit by devastating twin earthquakes.

The boy, identified by the Reuters news agency as Klieber Moran, was rescued early on Tuesday, the only reported survivor on the sixth day of rescue efforts, according to Venezuelan authorities.

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Patient reported to have been admitted to the Queen Elizabeth university hospital in the early hours of Tuesday

A patient is being tested for the suspected Ebola virus at a Glasgow hospital, the Press Association has reported.

It is understood the patient was admitted to the Queen Elizabeth university hospital in the early hours of Tuesday.

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⚽️ Kick-off time: 5pm local/10pm BST/7am AEST
⚽️ Player guide | Bracketology | Golden Boot | Mail Will

Wrap your eyeballs around Football Daily.

France (4-2-3-1): Maignan; Kounde, Upamecano, Saliba; Digne; Tchouameni, Rabiot; Dembele, Barcola, Olies; Mbappe

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Simple Minds

Kraftwerk

DEN HAAG (ANP) - Sportminister Mirjam Sterk denkt na over hoe geld in de toekomst eerlijker kan worden verdeeld over sportclubs. Dat zei ze tijdens een debat nadat Kamerleden haar vroegen naar de subsidieregeling voor amateursportverenigingen. Onlangs zorgde het grote aantal aanvragen van die zogenoemde BOSA-regeling voor een storing, waardoor niet meer viel te achterhalen welke aanvragen als eerste werden gedaan en tot onvrede van de verenigingen over de aanvragen werd geloot.

Juridisch gezien bood de loting volgens Sterk een oplossing, maar ze snapt dat het schuurde met het rechtvaardigheidsgevoel. Hoewel ze dus begrip heeft voor de sores van de aanvragers, benadrukte de minister dat door de loting uiteindelijk net iets meer verenigingen subsidie krijgen.

Een vereniging kan maximaal 2,5 miljoen euro krijgen. "Best hoog", vindt Sterk, die nadenkt of dat anders moet. Ook wil ze kijken of het eerlijker is om verenigingen een bredere tijdspanne te geven voor de subsidieaanvraag, omdat de een er mogelijk iets bedrevener in is dan de ander. Sterk wil ook kijken of het mogelijk is om het totale subsidiebedrag volgend jaar te verhogen, omdat het nu niet genoeg is. "Dat was andere jaren niet anders", zei ze er direct bij. Dit jaar is er in totaal 46,5 miljoen euro beschikbaar, dat is inclusief 3 miljoen euro die op initiatief van CDA erbij is gekomen.

Daarnaast wil ze in 2028 deels over op een revolverend fonds, om clubs structureler te kunnen financieren. Dat betekent dat de verenigingen leningen krijgen en via rente over die leningen weer geld beschikbaar komt in het fonds voor andere clubs.

DEN HAAG (ANP) - De politie heeft recent een minderjarige verdachte aangehouden voor het plannen van een terroristisch misdrijf vanuit zogenoemd nihilistisch gewelddadig extremisme. Een woordvoerster van de politie bevestigt berichtgeving van Nieuwsuur hierover. Waar en wanneer de verdachte is aangehouden, wil de politie niet zeggen, omdat volgens de woordvoerster het onderzoek nog loopt.

De Nationaal Coördinator Terrorismebestrijding en Veiligheid (NCTV) waarschuwde dinsdag in zijn halfjaarlijkse dreigingsbeeld voor een toenemende dreiging uit het nihilistisch extremisme. Volgens de terrorismebestrijder gaat het om extremisten uit "een zeer gewelddadige onlinesubcultuur" die geen duidelijke ideologie kent.

"Extremistische aanhangers delen een mensvijandig en destructief wereldbeeld en plegen op basis daarvan geweld. Binnen dit extremisme zijn geweld en chaos zowel doelen op zich als middelen om iets te bereiken", stelt de NCTV.

STADE (ANP/AFP) - De man die wordt verdacht van het doodschieten van zes mensen in het Duitse Stade lijkt eerder zijn jonge baby door elkaar geschud te hebben. Ook had hij artsen in het ziekenhuis waar de baby werd behandeld bedreigd, melden Duitse media.

Der Spiegel meldt op basis van anonieme bronnen dat de 45-jarige Fatih Khan G. zijn dochter dusdanig door elkaar schudde dat het gewond raakte. Een behandelend arts stelde verwondingen vast die daarop duidden.

Artsen maakten volgens Die Welt in april en mei melding van bedreigingen door G. Er werd een onderzoek ingesteld, maar het kwam niet tot een veroordeling. De moeder van het kind had G. volgens Der Spiegel verlaten en probeerde via de rechter voogdij te krijgen.

De aanklagers meldden eerder dat de verdachte maandag naar de opvanglocatie in Stade was gekomen om te bespreken wat er met het kind zou gebeuren. Vervolgens zou hij plots het vuur geopend hebben op medewerkers. De moeder en het drie maanden oude meisje raakten niet gewond.

NEW YORK (ANP) - De aandelenbeurzen in New York gingen dinsdag verder omhoog, na de stevige winsten een dag eerder. De toonaangevende Dow-Jonesindex eindigde opnieuw op een recordniveau. Het is ook de laatste handelsdag van het tweede kwartaal en de eerste helft van dit jaar. Wall Street heeft in die periodes flinke koerswinsten behaald, ondanks de onrust door de oorlog in het Midden-Oosten.

De Dow eindigde 0,3 procent hoger op 52.319,20 punten. Op maandag sloot de graadmeter met daarin de dertig grootste Amerikaanse bedrijven voor het eerst boven de 52.000 punten. Over de eerste helft van dit jaar is de Dow met meer dan 8 procent gestegen.

De S&P 500 won dinsdag 0,8 procent op 7499,36 punten. De index van 500 grote beursgenoteerde ondernemingen won in de eerste jaarhelft eveneens meer dan 8 procent. De Nasdaq eindigde 1,5 procent in de plus op 26.213,72 punten, na de forse winst op maandag. De technologiebeurs boekte sinds begin dit jaar een winst van ongeveer 11 procent.

DEN HAAG (ANP) - Farmers Defence Force gaat bij boeren peilen of er draagvlak is voor actie en hoeveel mensen willen meedoen, zegt Mark van den Oever, voorman van de boerenactiegroep. Daarna wordt bepaald hoe en wanneer de actie eruitziet, zei hij dinsdag in een vlog.

"We gaan nu niet naar Den Haag, omdat het reces is en er niemand aanwezig is. We kiezen een moment dat ons het beste uitkomt, niet een tijdstip dat voor Den Haag het meest geschikt is", aldus Van den Oever. Hij is woedend over de plannen van het kabinet voor de landbouwsector.

Meerdere boerenorganisaties waarschuwden afgelopen zondag dat de stikstofplannen van het kabinet zullen leiden tot "ongekende juridische chaos en onteigening" en "einde oefening" betekenen voor veel veehouders in Nederland.

'Frontale aanval'

Het pakket maatregelen werd vrijdag gepresenteerd door landbouwminister Jaimi van Essen. De actiegroepen, waaronder Agractie, Dutch Dairymen Board en de Nederlandse Melkveehouders Vakbond, spreken van een "frontale aanval" op de agrarische sector. Volgens de organisaties worden er met de plannen onmogelijke offers geëist en bieden ze geen enkel economisch perspectief voor de agrarische sector.

Ook land- en tuinbouworganisatie LTO Nederland reageerde vrijdag zeer kritisch op de plannen. "Pijnlijke maatregelen waarvan volstrekt onduidelijk is hoe ze aansluiten en optellen tot de doelen die gehaald moeten worden", zei LTO-voorzitter Ger Koopmans.

Hoe vermogens in box 3 worden belast, blijft nog langer onduidelijk. De Eerste Kamer stelt de stemming over een voorstel tot vermogensaanwasbelasting uit, omdat de senaat zekerheid wil dat er uiteindelijk een vermogenswinstbelasting volgt.

Accusations of influence-peddling can muddy what is really going on.

Qualcomm is finally getting serious about AI infrastructure, but its push into the datacenter hinges on the success of an ambitious near-memory compute architecture designed to deliver better inference economics than today's GPUs. Announced during its 2026 investor day last week, the tech will see Qualcomm stack layer upon layer of DRAM on top of its XPUs to form a single unified compute and memory module it's calling high-bandwidth compute (HBC). “We offer all of the performance advantages of SRAM, but with the density and the memory capacity that HBM (high-bandwidth memory) stacks offer,” Tony Pialis, Qualcomm’s EVP of datacenter, claimed during last week's investor presentation. This technology is set to launch next year as part of Qualcomm’s AI250-series of Dragonfly rack systems, and marks a distinct shift in Qualcomm’s AI infrastructure strategy. The handset giant is no stranger to AI accelerators. Essentially every Snapdragon processor sold today ships with an NPU on board. But in the datacenter, the company has struggled to garner the same excitement as Nvidia, AMD, and even startups like Cerebras. Compared to the big two’s GPUs, Qualcomm’s AI-series accelerators haven’t compared that favorably, but that could soon change as the company looks to make its mark on the datacenter. With the AI250, the SoC maker is claiming 768 GB of memory capacity and up to 133 TB/s of effective memory bandwidth per card. For reference, Nvidia's Groq 3 LPUs offer just 500 MB of SRAM and 150 TB/s of bandwidth. If that seems too good to be true, that’s because it is. Qualcomm is leaning heavily on the word “effective.” We know that because for the AI200-based Dragonfly systems rolling out this year, they claimed 414 TB/s of “effective” memory bandwidth across all 56 chips. On its face, that seems more realistic, but actually achieving that with 8800 MT/s LPDDR5x alone would require a 6,720-bit-wide bus, which it almost certainly does not possess. Qualcomm insists that this is the "pure physical bandwidth of the LPDDR interface," but declined to offer any specifics as to how it's somehow managed to achieve what Nvidia needed eight HBM3e stacks to do. In any case, according to Qualcomm’s marketing materials, with the move to HBC, the AI250 will offer 18x the effective bandwidth of the AI200, while the forthcoming AI300 will deliver 54x the bandwidth. Given the context, these seem like outlandish claims, but these "effective" multipliers are really a feature of Qualcomm's HBC architecture. Unpacking high-bandwidth compute Amplifying “effective” bandwidth isn’t the only party trick from these HBC-based accelerators. Qualcomm claims that by moving some of the XPU’s compute under the DRAM, it can significantly reduce the amount of power its chips consume. On a conventional datacenter GPU, data is rapidly shuffled between HBM and the compute dies. Even using advanced packaging technologies like TSMC’s CoWoS, the power required to move this data back and forth is significant. By stacking the DRAM directly on top of some of the logic and connecting them using through-silicon vias (TSVs), the path from compute to memory is shortened considerably. "Imagine working in the same building that you live in so you only travel up and down," Pialis said. "What does that mean for the highways and the roads that connect the suburbs to the city? Guess what? The roads are clear. The value this brings to the industry is lower power consumption, less heat, and that expensive road of silicon interposer that HBM solutions use is no longer needed." Performing bandwidth-bound operations on the base die also has the benefit of reducing the amount of data that needs to be shuttled to and from the HBC to the SoC. In effect, memory bandwidth is amplified. This is why Qualcomm is using “effective bandwidth" so liberally. Compared to doing all of that work on a conventional GPU or XPU with distinct HBM and compute dies, the effective bandwidth would be significantly higher, which also achieves better density than SRAM-only designs, like Nvidia’s LPUs or Cerebras’ dinner plate sized accelerators. With that said, Qualcomm probably won’t be running its entire AI software stack on HBC. Higher memory bandwidth primarily benefits decode, when the entirety of the model’s active weights are streamed autoregressively from memory one token after another. Decode isn’t particularly compute-intensive. As such, doing decode partially or entirely in HBC starts to make a lot of sense because it also avoids the thermal constraints associated with burying the compute under multiple layers of DRAM. Qualcomm tells us that the AI250 can be used as a standalone AI accelerator, but notes it is heavily optimized around addressing bandwidth bottlenecks. So, in addition to being a dedicated inference chip, it can be used in disaggregated inference architectures that use GPUs or other Qualcomm parts for prompt processing and the AI250 to speed up memory intensive decode operations. Peak FLOPS are notably missing from Qualcomm’s AI250 disclosures — the company declined to share specifics upon our request. Is HBC actually a competitive advantage? While Qualcomm is early among chip designers to make a fuss about near-memory or HBC, it’s not the first, nor is the technology beyond the means of Nvidia or AMD. In fact, both Nvidia and AMD are rumored to be working with HBM suppliers and TSMC to develop custom base dies to boost the performance of their next-gen chips, though it's still not clear how much, if any, compute has been integrated into them. Qualcomm tells us its HBC "uses LPDDR memory in a purpose-built near-memory computing architecture that combines compute and highly-accelerated memory bandwidth within a 3D-stacked silicon design. While both HBC and HBM use stacked-memory concepts, HBC is a distinct architecture designed to address AI’s data-movement bottleneck by bringing compute and memory closer together, increasing memory bandwidth efficiency and improving energy efficiency for AI inference workloads. HBM has more stacks of DRAM, uses 2.5D interposer to route more wires, and does not do computing in the base logic die." AI chip startup d-Matrix is also developing accelerators that will use 3D stacked DRAM to extend their in-memory compute capabilities. The underlying technology described by Pialis may not be as unique as Qualcomm would like investors to believe, but it shows the company hasn’t missed the boat. However, Qualcomm’s ability to work with Nvidia and AMD may end up doing more to sell customers on its tech than anything. As we previously wrote, in a disaggregated AI world, Nvidia can be both a friend and an enemy. Qualcomm finds its Mojo In addition to teasing its upcoming AI250 and AI300 accelerators, Qualcomm’s investor day also coincided with the acquisition of AI software startup Modular. Modular was founded by Tim Davis and Chris Lattner, the latter of whom you may recognize as the creator of LLVM, Clang, the Swift programming language, and the multi-level intermediate representation (MLIR) compiler infrastructure. At Modular, Lattner and crew developed Mojo, a low-level programming interface for GPUs, which offered a high-performance alternative to Nvidia’s CUDA or AMD’s HIP and ROCm stacks. The big idea is that users should be able to write highly performant AI apps that’ll run regardless of the underlying hardware. For Qualcomm, Mojo presents an opportunity to sidestep the CUDA moat, which has dogged AMD for so long. With Mojo, Qualcomm’s customers won’t need to choose one platform; they can develop their apps and run them on whatever compute is handy at the time. It’s not all or nothing either. Modular should help to support heterogeneous deployments similar to what Nvidia is doing with Groq’s LPU tech, where GPUs might be used for prefill and AI250s are used for decode in whatever ratio makes the most sense for that specific application. However, the acquisition doesn’t just buy Qualcomm a vendor-neutral programming model. The folks buying these systems are primarily concerned with one AI workload in particular: LLM model serving. For this, Modular developed a serving platform called Max. Max is a bit like SGLang or vLLM in that it’ll run interchangeably on AMD or Nvidia hardware, but because it’s built atop Mojo, it, at least in theory, shouldn’t require nearly as much hand tuning. The offering should help Qualcomm compete in a landscape where software has become even more important than the hardware it runs on, if it manages to close the acquisition this year without regulators stepping in. In any case, we won’t have to wait much longer to see the HBC in action. After launching its AI200-series racks later this year, Qualcomm plans to push its first-gen HBC-based AI250 out the door beginning in 2027, while its second-gen HBC platform is slated for 2028. While you wait, why not read up on Qualcomm’s new datacenter CPU, which we explored in more detail last week. ®

Sophisticated AI models tend to require a lot of memory and take up a lot of storage space. One of the ways to reduce that footprint involves a process called quantization, which changes how model weights are represented and stored. But quantization has its drawbacks. Andrés Mac Allister, CEO and founder of The SEMQ Group, believes there's another way to make machine learning more efficient and less resource intensive. Instead of compressing model weights (specifically embeddings), he contends you can separate the semantics (the meaning) from how that meaning is represented. Model weights, including embeddings (which map tokens to vectors), are the numbers in a machine learning model that determine how strongly one piece of information relates to another. Taken all together, they reflect learned behavior. These parameters are commonly represented in Full-Precision (FP32), which requires 4 bytes per parameter. A 7B parameter model at FP32 would need about 28 GB of disk space and memory. To save space, the model might be quantized at FP16/BF16, which requires 2 bytes per parameter. The resulting model would need about 14 GB of disk space and memory. And there are smaller quantization options like FP8, INT8/Q8, Q6, Q5, Q4, Q3, and Q2, each of which reduces the storage and memory footprint while also reducing precision – the answers get worse. SEMQ stands for Symbolic Embedding Multi-Quantization. As described in a paper published earlier this year, SEMQ "replaces raw vectors with fixed-dimensional symbolic structures that preserve relational properties, such as relative similarity ordering and neighborhood structure, while decoupling representation from metrics, indexing, and execution semantics." Essentially, Mac Allister has devised a way to construct a semantic abstraction layer that decouples the meaning captured in embeddings – vectors representing data – from the way that data is represented. The operative idea is that semantic relationships depend primarily on the relative orientation of embedding vectors, so the absolute magnitude of those vectors becomes less important to preserve. That's less data to store. The potential impact to businesses running AI workloads depends on the portion of infrastructure costs attributable to semantic state. "An embedding is usually represented as a long vector of floating-point numbers," Mac Allister explained in an email to The Register. "In conventional embedding systems, semantic state is typically stored as a sequence of high-precision numerical coordinates. Those coordinates jointly encode both magnitude and direction in the embedding space. "Our original question was whether a substantial part of the useful semantic information could instead be represented through the structural relationship among components, how they move relative to one another, which regions they occupy and what directional configuration they form in the overall space." To this end, SEMQ aims to represent relative geometry rather than an enumeration of independent floating-point magnitudes. "That matters because semantic systems generally care about relationships, similarity, neighborhood, continuity, retrieval behavior, change over time, rather than only about preserving each raw numeric value in isolation,' said Mac Allister. "The result is a portable representation of semantic state that can be reproduced, audited, compared and transferred across processes." According to Mac Allister, initial validation tests that focused on converting the embedding-based semantic state into a deterministic .semq representation, restoring it, and evaluating the stability of retrieval and classification operations have shown good results. "For example, in one benchmark using the Banking77 dataset from MTEB and the all-MiniLM-L6-v2 embedding model, the FP32 baseline achieved 92.26 percent accuracy. SEMQ achieved 92.27 percent effectively matching the FP32 baseline within 0.03 percentage points." SEMQ thus did substantially better than 4-bit quantization, which registered 56.05 percent accuracy, 36.22 percentage points less than FP32. "These are not claims that conventional quantization is universally ineffective but they show that, in this particular semantic classification setting, preserving the relevant semantic structure is materially different from simply reducing numerical precision," said Mac Allister. Applying SEMQ can be done at the point of data ingestion – organizations can use the SDK on the vectors generated by their embedding model on their documents to encode that data as an .semq artifact – or at query time to load, query, compare, restore, and verify that encoding. "That means a team can adopt SEMQ without replacing its LLM, embedding model, vector database or agent framework," said Mac Allister. "It can initially run alongside the existing stack as a sidecar layer, then become the representation used for selected retrieval or memory workloads." Potential use cases, he said, include making embeddings or memory state portable across systems, reproducing semantic state across different runs or machines; auditing model changes; reducing dependence on opaque or hard-to-reproduce stateful pipelines; and diffing semantic state. He added that the SEMQ can be extended to runtime cognitive state. "In our research, .semq files have been used to snapshot and restore transformer KV-cache state across process boundaries," he said. "That is not a pre-training workflow either: but a runtime-state workflow for pausing, transferring and resuming an active model session." Mac Allister isn't yet ready to talk about specific customers. He said his company is working through a Founding Design Partnership Program with organizations exploring applications in enterprise AI, retrieval, agent memory, and auditable AI workflows. This includes some AI infrastructure hyperscalers and some companies operating at the AI application layer. "We signed NDAs with all of them, so I cannot name all of the organizations publicly yet," he said. "What I can say is that the interest has come from teams dealing with AI systems where reproducibility, state, lower infrastructure overhead, and the ability to inspect semantic behavior are operationally important. So this is a big problem for big companies." ®

Thomas Hawk posted a photo:

Thomas Hawk posted a photo:

With a strong second place in the Austrian Grand Prix on Sunday, pushing George Russell’s Mercedes for victory, Max Verstappen gave Red Bull by far their best showing of the year. This was an encouraging reward for the team for bringing to the Red Bull Ring the third evolution of their RB22 model.