Tootfinder

Gerade sollte ich in einer radiologischen Praxis in #Karlsruhe mit meinem Handy einen individuellen QR-Code scannen, um einen Patientinnenfragebogen auszufüllen.

Anscheinend hätte das dann innerhalb des Praxis-W-LANs die Daten übertragen.

Trotzdem frage ich mich, wie sicher so etwas ist.
Ich habe darauf bestanden, die Daten über ein Praxis-Tablet einzugeben (plöt…

Veranstaltungstipp für Karlsruher: Die Tage der Demokratie im Triangle Space des KIT.
#Karlsruhe

Heute!

Attenuation Models for Extensive Air Showers Derived from Simulations
Fiona Ellwanger (Institute for Astroparticle Physics, Karlsruhe Institute of Technology, Karlsruhe, Germany), Darko Veberi\v{c} (Institute for Astroparticle Physics, Karlsruhe Institute of Technology, Karlsruhe, Germany)
https://arxiv.org/abs/2508.16360

Attenuation Models for Extensive Air Showers Derived from Simulations
At ultra-high energies, the flux of cosmic rays is too low for direct measurements to be meaningful. When a cosmic ray enters the atmosphere, it initiates an extensive air shower, producing a cascade of secondary particles that propagate toward the ground. Large arrays of surface detectors are used to measure these secondary particles upon arrival. The signal detected at a specific reference distance from the shower core serves as a proxy for the shower size and, consequently, as a reliable e…

Bewegliche Mikrospiegel: Deutsches Start-up denkt AR-Displays neu
Das Karlsruher Start-up Gixel entwickelt ein AR-Display, das gängige Lösungen in zentralen Aspekten übertreffen soll.
https://www.

AI Models Exceed Individual Human Accuracy in Predicting Everyday Social Norms
Pontus Strimling, Simon Karlsson, Irina Vartanova, Kimmo Eriksson
https://arxiv.org/abs/2508.19004

AI Models Exceed Individual Human Accuracy in Predicting Everyday Social Norms
A fundamental question in cognitive science concerns how social norms are acquired and represented. While humans typically learn norms through embodied social experience, we investigated whether large language models can achieve sophisticated norm understanding through statistical learning alone. Across two studies, we systematically evaluated multiple AI systems' ability to predict human social appropriateness judgments for 555 everyday scenarios by examining how closely they predicted the ave…

Affective Polarization across European Parliaments
Bojan Evkoski, Igor Mozeti\v{c}, Nikola Ljube\v{s}i\'c, Petra Kralj Novak
https://arxiv.org/abs/2508.18916 https://…

Affective Polarization across European Parliaments
Affective polarization, characterized by increased negativity and hostility towards opposing groups, has become a prominent feature of political discourse worldwide. Our study examines the presence of this type of polarization in a selection of European parliaments in a fully automated manner. Utilizing a comprehensive corpus of parliamentary speeches from the parliaments of six European countries, we employ natural language processing techniques to estimate parliamentarian sentiment. By compar…

Man stelle sich vor, man würde 30% der Fahrbahnen für Autos dichtmachen. Aber für Autoverkehr gibt es keine Obergrenzen, nur Mindestleistungen und vor allem Geld wie in ein Fass ohne Boden.
https://www.swr.de/swraktuell/baden-wuertt

Weniger Bahnen, längere Wartezeiten ohne Alternative: Karlsruhe muss wegen Finanzkrise Nahverkehr kürzen
Karlsruhe muss bei den Finanzen hart durchgreifen. Die Verkehrsbetriebe beraten am 23. Juli ein im vergangenen Jahr bekannt gewordenes Sparkonzept. Der Gemeinderat entscheidet im Herbst.

Scalable Engine and the Performance of Different LLM Models in a SLURM based HPC architecture
Anderson de Lima Luiz, Shubham Vijay Kurlekar, Munir Georges
https://arxiv.org/abs/2508.17814

Scalable Engine and the Performance of Different LLM Models in a SLURM based HPC architecture
This work elaborates on a High performance computing (HPC) architecture based on Simple Linux Utility for Resource Management (SLURM) [1] for deploying heterogeneous Large Language Models (LLMs) into a scalable inference engine. Dynamic resource scheduling and seamless integration of containerized microservices have been leveraged herein to manage CPU, GPU, and memory allocations efficiently in multi-node clusters. Extensive experiments, using Llama 3.2 (1B and 3B parameters) [2] and Llama 3.1 …

Diesen Samstag! Wenn ihr nicht den ganzen Tag Zeit habt, kommt zu einem Teil der Veranstaltung. #Karlsruhe #KA2607