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@kubikpixel@chaos.social
2026-06-01 05:25:45

«KI-Modelle sind anfällig für wiederholte Angriffe:
Laut Forschern von Cisco versagen KI-Modelle bei realistischen Multi-Turn-Angriffen und lassen an Sicherheits-Benchmarks auf Basis weniger Prompts zweifeln.»
Der moderne Widerspruch ist die KI oder was ist es sonnst? So klug wie KI angeboten wird ist es einfach nicht.
🤖

@heiseonline@social.heise.de
2026-04-29 13:13:00

Iran-Krieg treibt laut Bericht Platinenpreise hoch
Der wichtigste Lieferant von Polyphenylenether hat nach einem Angriff offenbar die Auslieferungen eingestellt. Das betrifft alle elektronischen Geräte.

@marcel@waldvogel.family
2026-03-31 18:26:31

«"Wir brauchen keine Leute, die sich erst dann an Kriegen beteiligen, wenn wir sie bereits gewonnen haben!", hatte Trump am 7. März erklärt.»
Notiz an Trump: Die Nato ist ein Verteidigungs-, kein Angriffsbündnis. (Aber die Message käme bei Trump aber sowieso nicht an. Jegliches "Bündnis" ist für ihn eine Beziehung zu Untertanen.)

@tanyakaroli@expressional.social
2026-06-01 06:30:16

Nå, så fik man da lige lidt ekstra morgenmotion! 🏃‍♀️
Jeg skal til SDU i dag og havde planlagt bus til Hovedbanen i god tid, med hele 15 minutter til afgang. Bortset fra trafikhelvedet på Amager! Lige omkring Christianshavns Vold panikkede jeg over det og hoppede af bussen. For at nå til Hovedbanen i tide måtte jeg så smålŸbe resten af vejen (2 km) - og undervejs kunne jeg så konstatere at jeg snildt kunne have taget mindst et stop til, for der var busbane det næste stykke 🤦‍♀️
Nu sidd…

@andres4ny@social.ridetrans.it
2026-03-31 17:34:37

Great job microsoft. You're killing it!

A colorful (but angry? why?) unicorn head, with the message "This page is taking too long to load. Sorry about that. Please try refreshing and contact us if the problem persists."

Below that, a bunch of GitHub links (as this is a github page).
@tezoatlipoca@mas.to
2026-03-31 15:11:32

boss: we want to train a ServiceBot on our #documentation
me: here you go <gives #PDFs>
boss: ServiceBot says these PDFs are too big
me: isn't parsing vast amounts of #data to answer questions and dist…

@cowboys@darktundra.xyz
2026-04-29 10:39:35

2026's Costco-value late-round NFL draft picks, plus examining the 49ers' confidence nytimes.com/athletic/7240037/2

@raiders@darktundra.xyz
2026-04-29 10:43:21

2026's Costco-value late-round NFL draft picks, plus examining the 49ers' confidence nytimes.com/athletic/7240037/2

@arXiv_csCL_bot@mastoxiv.page
2026-03-31 10:12:22

Training data generation for context-dependent rubric-based short answer grading
Pavel \v{S}indel\'a\v{r}, D\'avid Slivka, Christopher Bouma, Filip Pr\'a\v{s}il, Ond\v{r}ej Bojar
arxiv.org/abs/2603.28537 arxiv.org/pdf/2603.28537 arxiv.org/html/2603.28537
arXiv:2603.28537v1 Announce Type: new
Abstract: Every 4 years, the PISA test is administered by the OECD to test the knowledge of teenage students worldwide and allow for comparisons of educational systems. However, having to avoid language differences and annotator bias makes the grading of student answers challenging. For these reasons, it would be interesting to compare methods of automatic student answer grading. To train some of these methods, which require machine learning, or to compute parameters or select hyperparameters for those that do not, a large amount of domain-specific data is needed. In this work, we explore a small number of methods for creating a large-scale training dataset using only a relatively small confidential dataset as a reference, leveraging a set of very simple derived text formats to preserve confidentiality. Using these methods, we successfully created three surrogate datasets that are, at the very least, superficially more similar to the reference dataset than purely the result of prompt-based generation. Early experiments suggest one of these approaches might also lead to improved model training.
toXiv_bot_toot

@eichkat3r@hessen.social
2026-04-29 06:36:05

LPG hat das planziel für die kartoffelproduktion übererfüllt
deswegen wurde in der mensa knollenwoche angeordnet