Cinco


Soldaat van Oranje

Bij de uitvaart van mijn laatste tante (89) halen we herinneringen op. Zoals aan die keer in de bioscoop met haar kleinkinderen bij Soldaat van Oranje.

In het midden

Horizontaal: 1. ‘A Boy Named __’, Johnny Cash 4. Nederland-__, sinds gisteren te koop 9. Duitse buurgemeente van Enschede 11. Spaanse bubbels 12. Een derde dans 14.

Sudoku

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.

De macht die Musk heeft, en krijgt, wordt zorgwekkend groot

Musk heeft niet alleen door zijn kapitaal veel macht. Hij krijgt die ook door zijn omgeving toebedeeld. En hij gebruikt die macht ook politiek. Op zijn eigen socialemediaplatform X – onderdeel van SpaceX – steunt en stimuleert hij bijvoorbeeld de uiterst rechtse stromingen in de Europese politiek.

FIFA neemt geen maatregelen tegen VAR-arbiter om omstreden handebaar, was ‘onvrijwillige, onbewuste beweging’

De disciplinaire commissie van de FIFA heeft de VAR-arbiter Shaun Evans vrijgesproken nadat hij ervan werd beschuldigd een handgebaar te hebben gemaakt dat wordt geassocieerd met…

Found Photograph

Thomas Hawk posted a photo:

Found Photograph

We Were Born Before the Wind

Thomas Hawk posted a photo:

We Were Born Before the Wind

Slashdot

News for nerds, stuff that matters

Google Chrome's Next Update Will Mark the End of Popular Ad Blockers

Google is removing Chrome's last remaining workarounds for Manifest V2 extensions, effectively ending support for legacy ad blockers such as the original uBlock Origin. 9to5Google reports: CyberNews points out a Chromium commit that removes support for the "kExtensionManifestV2Disabled" flag, which is referred to as "dead code" seeing as Chrome no longer supports Manifest V2 extensions. This removal acts as the final stop for many Manifest V2-based ad blocker extensions that were still in use today -- the flag was effectively a loophole to continue using these extensions.

A Googler on the commit explains: "MV2 extensions are no longer allowed in any supported version of Chrome, and we are removing support for them and the associated functionality. We won't be able to provide / maintain this functionality indefinitely due to the complexity and tech debt, as well as the security risks it entails (we've actually found a number of bugs that are specific to MV2 lately). Of course, other browsers can continue supporting these if they so desire."

This will also impact other Chromium-based browsers, though the comment notes that "other browsers can continue supporting these if they so desire." Neowin points out that Microsoft Edge and Opera are likely to follow suit. Chrome 150, set to be released later this month, will remove this flag, while other leftover bits of Manifest V2 will be removed in the v151 release.

Read more of this story at Slashdot.

The Register

Biting the hand that feeds IT — Enterprise Technology News and Analysis

A modest proposal: Reformat everything to make documents more palatable to AI

Websites are being redesigned for consumption by AI models, and now a coalition wants to extend the trend to digital documents. The LF AI & Data Foundation, under the Linux Foundation, has formed a working group to steer the development of DocLang, an AI-friendly document format that aims to help enterprises feed their files to AI systems. The DocLang group, founded by IBM, NVIDIA, Red Hat, ABBYY, HumanSignal, and Forgis, contends that existing formats like PDF, Markdown, HTML, and LaTeX are ill-suited for AI document parsing. In late 2024, IBM developed an open source toolkit called Docling to facilitate AI document parsing, not unlike Microsoft's MarkItDown or the Marker project. Docling provides a way to convert various file formats into structured AI-ready data. DocLang expands upon that foundation with a standard for exchanging structured output across different systems. "DocLang is designed to solve one of the foundational problems in enterprise AI: documents were built for humans, not machines," said Maxime Vermeir, VP of AI Strategy at AI automation biz ABBYY in a statement. "By introducing a minimal, standardized, and AI-native representation of document structure, layout, meaning and governance, DocLang creates a far more deterministic foundation for modern AI systems." The new DocLang format is necessary, the spec authors argue, because existing formats were designed for rendering and lose semantic information, structural relationships, or geometric context when AI models turn them into tokens. The specification explains that Markdown lacks sufficient scope, that HTML is excessively verbose, and that LaTeX allows too much ambiguity. Essentially, DocLang is optimized for LLM tokenizers through markup that maps between DocLang elements and LLM tokens on a 1-to-1 basis. The spec relies on a limited XML vocabulary that aligns with LLM tokenizers to produce optimized prompts. It is lossless, so the AI conversion doesn't do away with valuable info. It's designed to support common graphical elements like tables, formulas, charts, and multimodal content. And it's an open standard. DocLang could also help keep costs under control. According to AI Cost Check, having an AI model conduct an OCR scan on a PDF requires about 1,200 input tokens and 150 output tokens as a baseline. That's inconsequential to corporate AI customers on a one-off basis but demands attention at scale. And because AI models have highly variable token costs, companies may find they are spending more than they anticipated to have their AI system ingest PDFs, particularly if the documents are long and complicated or an expensive frontier model is used. "PDFs were designed for rendering, not understanding," said Jon Knisley, AI Value and Enablement Lead at ABBYY, in an email to The Register. "Every time a PDF enters an AI pipeline, structure, meaning and layout get lost, so the model's accuracy ends up bottlenecked by document quality rather than model quality. Teams compensate by building custom parsers at every integration point, which results in brittle, one-off work, and a new engineering sprint for every new document type." According to Knisley, that has measurable cost. "Ambiguous structure forces the model into guesswork, which drives up hallucination risk and burns tokens deciphering layout instead of extracting meaning," he explained. "With DocLang, customers can expect better accuracy, lower costs, fewer tokens consumed, faster performance and more consistent outputs. The exact savings depend on the use case and document complexity, but our initial benchmarks show 4x to more than 30x lower cost depending on the model evaluated." Knisley also cited governance advantages, noting that document provenance data and metadata can get stripped when documents gets moved. DocLang, he said, keeps that information attached. ABBYY, which offers AI document processing, has created the DocLang Interactive Benchmark to illustrate the potential token savings of feeding DocLang documents to AI models. A PDF of IBM's 2025 annual report, for example, results 8,421 input tokens and 512 output tokens while a DocLang version requires only 5,310 input tokens and 498 output tokens. What's more, the DocLang version results in lower latency (2.7s vs 4.2s) and delivers better quality (the AI missed one subsection and mangled a table merger in the PDF). "It's still early, and we won't overstate adoption," said Knisley. "The standard is open and free to build on, and the group is actively inviting more technology providers and enterprises to join. The early response has been encouraging, and we're optimistic about where it goes from here." ®