@azonenberg@ioc.exchangeCan anybody get me some waveform captures (in native ngscopeclient .scopesession format, or any of the supported binary/CSV waveform formats we can import) for CAN-FD?
There's a six year old ticket against libscopehal for adding FD support to the CAN protocol decoder but I don't have anything around that speaks it which makes developing a decode tricky.
@nic@geno.social"How proprietary formats have become Microsoft’s main tool for lock-in"
Why DOCX, XLSX, and PPTX are Microsoft's most effective lock-in tool:
https://blog.documentfoundation.org/blog/2026/07/17/microsofts-main-tool-for-lock-in/…
@jake4480@c.imNew blog post on the importance of owning physical (and digital) media, when possible: https://spacetimetech.wordpress.com/2026/06/28/the-importance-of-owning-physical-and-digital-media-when-possible
@Mediagazer@mstdn.socialGoogle says it is testing new ad formats in search results and AI Mode, including Conversational Discovery ads, Highlighted Answers, and AI-powered Shopping ads (Anu Adegbola/Search Engine Land)
https://searchengineland.com/google-tests-ne…
@Techmeme@techhub.socialGoogle says it is testing new ad formats in search results and AI Mode, including Conversational Discovery ads, Highlighted Answers, and AI-powered Shopping ads (Anu Adegbola/Search Engine Land)
https://searchengineland.com/google-tests-ne…
@vosje62@mastodon.nl/2
New ad formats built with Gemini coming to Google Search - #Google
https://blog.google/products/ads-commerce/google-marketing-live-search-ads/
@matthiasott@mastodon.social@… @… Yes, in their screenshots on the blog post about new ad formats, they are labelled as “sponsored.“ Although I don’t know how they might do that inline within a written answer, I suppose they would need to – or perhaps mark …
@marcel@waldvogel.familyWho would expect anything else?
#Enshittification #Google #AI
@NFL@darktundra.xyzMock draft: Non-PPR formats are a throwback to run... https://www.espn.com/fantasy/football/story/_/page/FFMockDraft26-49349495/fantasy-football-mock-draft-non-ppr-10-teams
@Techmeme@techhub.socialInstagram is testing horizontal video on Instagram for TV, plans to experiment with longer-form storytelling and episodic series, and launches on Samsung TV (Katie Kilkenny/The Hollywood Reporter)
https://www.hollywoodreporter.com/tv/tv-ne
@fanf@mendeddrum.orgfrom my link log —
Faster zlib/DEFLATE decompression on arm64 and x86.
https://dougallj.wordpress.com/2022/08/20/faster-zlib-deflate-decompression-on-the-apple-m1-and-x86/
saved 2022-08-20
@datascience@genomic.socialThe {esquisse} package makes it easy to plot your data in different ways with a drag and drop interface: #rstats
@bthalpin@mastodon.socialFor "reasons" I've been increasingly using ffplay to play music from the command line (e.g., formats that make mplayer & vlc glitch), so I wrote a script to make it play playlists:
while read p; do
ffplay -nodisp -autoexit $p
done < $1
3 LOC, no AI!
@Mediagazer@mstdn.socialInstagram is testing horizontal video on Instagram for TV, plans to experiment with longer-form storytelling and episodic series, and launches on Samsung TV (Katie Kilkenny/The Hollywood Reporter)
https://www.hollywoodreporter.com/tv/tv-ne
@bourgwick@heads.socialanother album of lost #eno songs, along with the pre-"another green world" demos. https://www.moredarkthanshark.org/eno_int_blitz-nov83.html
@Techmeme@techhub.socialTwitch rolls out Dual Format, a feature that lets creators stream horizontally and vertically simultaneously, and 2K streaming for partners and affiliates (Cheyenne MacDonald/Engadget)
https://www.engadget.com/2184452/twitch-cr
@nfdi4culture@nfdi.socialHier kommen noch ein paar Lesetipps aus unserem Culture Information Portal 🌞
📙Erfolgreicher Auftakt des neuen NFDI4Culture-Jour-fixe-Formats mit dem FID-Netzwerk: https://nfdi4culture.de/id/E6854
📗Workshop zum Performing Arts Thesaurus (PAT):
@adulau@infosec.exchangeThe GCVE Lab is an open space for experimenting with new ideas, tools, formats, and services related to the Global CVE Allocation System initiative.
The lab allows the GCVE community to explore promising concepts without immediately imposing the stability, compatibility, and operational requirements expected from the core GCVE infrastructure.
Open to comments/ideas.
#gcve #cve #cybersecurity
https://discourse.ossbase.org/t/gcve-lab-proposal/1117
https://gcve.eu
@… @…
@lil5@social.linux.pizza
@arXiv_physicsmedph_bot@mastoxiv.pageCOBRA2026: a large-scale multicenter pelvic cone-beam computed tomography projection dataset
Adrian Thummerer, Simon Rit, Florian Kamp, Matteo Maspero, Martjin P. W. Intven, Thomas G. Bon\'e, Christopher Kurz, Guillaume Landry, Thomas Baudier, Mustafa Kadhim, Julius Arnold, Michael Rauter, Barbara Kn\"ausl, Lukas Zimmermann
https://arxiv.org/abs/2607.20037 https://arxiv.org/pdf/2607.20037 https://arxiv.org/html/2607.20037
arXiv:2607.20037v1 Announce Type: new
Abstract: The COBRA2026 dataset is a large-scale, multicenter resource of raw radiotherapy cone-beam computed tomography (CBCT) acquisitions created for the development and evaluation of conventional and learning-based reconstruction and image-correction methods. It contains data from 867 patients undergoing pelvic radiotherapy at six European centers, acquired using Elekta and Varian imaging systems. For each case, the dataset includes raw projection data, acquisition geometry, calibration and correction information, clinically reconstructed CBCT images, and corresponding planning CT images. Vendor-specific files were anonymized and converted into open formats. Planning CT images were deformably registered to the daily CBCT anatomy, and matched projections were simulated using the corresponding acquisition geometry. All cases underwent visual quality control, and cases with substantial processing or registration errors were excluded. The approximately 950 GB dataset is divided into training, validation, and test sets containing 692, 52, and 123 cases, respectively. Projection stacks and volumetric images are provided as compressed MetaImage files, with geometry and metadata supplied in XML and YAML formats. COBRA2026 supports research on full- and sparse-view reconstruction, low-dose imaging, artifact and scatter correction, motion compensation, and synthetic CT generation. The dataset is released under the CC BY-NC 4.0 license, indexed on Zenodo (doi:10.5281/zenodo.21322350), and accompanied by openly available preprocessing and baseline reconstruction code. It also forms the basis of the COBRA2026 reconstruction challenge.
toXiv_bot_toot
@Mediagazer@mstdn.socialRoseBerry Media launches vertical streamer Epis, featuring originals and versions of BBC, Fremantle, and All3Media shows adapted for vertical viewing (Scott Roxborough/The Hollywood Reporter)
https://www.hollywoodreporter.com/tv/tv-ne
@arXiv_csPF_bot@mastoxiv.pageThe Brain That Goes Quiet: Serving a Large Model's Knowledge at 131 Tokens per Second on an 8 GB Laptop by Removing the Large Model from the Runtime Path
Myeong Jun Jo
https://arxiv.org/abs/2606.12154 https://arxiv.org/pdf/2606.12154 https://arxiv.org/html/2606.12154
arXiv:2606.12154v1 Announce Type: new
Abstract: In earlier work I showed that a 35B-class Mixture-of-Experts model can be loaded and executed on a consumer laptop with 8 GB of GPU memory. That result solved a placement problem and immediately exposed a different one: even correctly placed, the large model needed roughly four seconds to answer, because it was still being invoked at every query. This paper documents what happened when I stopped invoking it. During an offline phase, the large model reads source documents and writes verified answer entries into a structured knowledge store; at runtime, only a lightweight router, a deterministic renderer, and a 1B-class model are active. On the same 8 GB laptop, end-to-end response time fell from approximately 4,465 ms to 518 ms, effective end-to-end throughput rose from 15.7 to 131 tokens per second, and the small model's streaming decode rate held at 226-237 tokens per second with a time-to-first-token of 29-62 ms. The bottleneck is structural: three different large models (Qwen, Gemma, and GLM class) all showed the same multi-second runtime cost, and all three produced usable knowledge stores offline. On a 563-entry store built from seventeen real documents, keyword routing collapsed to 1.5% top-1 accuracy while BM25-based routing reached 92.8% (99.4% top-3), and a confidence gate raised effective top-1 to 98.0% by escalating 12.3% of queries. Exact-match fidelity of the small model ranged from 9/9 to 0/9 across envelope formats carrying identical content. A 16-case verification gate blocked all ten corrupted entries while admitting all six supported ones.
toXiv_bot_toot
@arXiv_csGR_bot@mastoxiv.pageFast Wave-optics Rendering of Multiplane Images for 3D Holographic Displays
Brian Chao, Dario Seyb, Nathan Matsuda, Oliver Cossairt, Yang Zhou, Douglas Lanman, Gordon Wetzstein, Grace Kuo, Changwon Jang
https://arxiv.org/abs/2607.19731 https://arxiv.org/pdf/2607.19731 https://arxiv.org/html/2607.19731
arXiv:2607.19731v1 Announce Type: new
Abstract: Recent advances in neural rendering have unlocked unprecedented capabilities in 3D reconstruction and novel view synthesis, giving rise to applications such as virtual fly-throughs of a 3D scene reconstructed from a set of sparse, casually captured images. However, these renderings are viewed on a computer screen or conventional VR headsets as 2D images, greatly limiting the perceptual realism and immersiveness of such experiences. The rapid development in novel 3D scene representations calls for dedicated rendering algorithms that convert these readily-available 3D contents into formats that are compatible with emerging 3D display technologies, such as holographic displays. In this paper, we propose a wave-optics rendering pipeline that works with multiplane images (MPIs) for efficient and high-quality hologram synthesis. Our MPI-based computer-generated holography algorithm greatly outperforms state-of-the-art primitive-based CGH algorithms in terms of runtime, achieving speedups up to 250,000x while achieving comparable image quality, and significantly outperforms conventional layer-based CGH algorithms in terms of image quality. We validate our method extensively on a wide variety of 3D scene datasets both in simulation and through experimentally captured results, showing exceptional 3D focal stack and 4D light field reconstruction performance without sacrificing efficiency.
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@Techmeme@techhub.socialSony says all new PlayStation games from both first- and third-party developers will be sold in digital formats from January 2028, ending physical game discs (Stephen Totilo/Game File)
https://www.gamefile.news/p/sony-drops-playstation-discs-2028-ps3-vit…
