Tootfinder

Wir waren kürzlich in Argiroupoli auf# Kreta. Im Ort ansässig ist eine ältere Oma und betreibt ein Café. Über dem Eingang kann man dieses Schild lesen. Berührend. So können oder konnten wir Deutsche wohl auch sein … Und so sollten wir auch weiterhin zu Fremden sein, die offen und freundlich gegenüber uns sind und sich anständig benehmen. Daran müssen wir uns dringend gerade in diesen Zeiten erinnern. Mehr zum Kreta-Aufenthalt im Blog >

Expert analyst questions George Pickens' commitment ahead of Cowboys vs Giants game https://www.sportingnews.com/us/nfl/dallas-cowboys/news/expert-analyst-questions-george-pickens-commitment…

#rsyslog is dead: https://www.rsyslog.com/rsyslog-goes-ai-first-a-new-chapter-begins/ 🤢

rsyslog Goes AI First — A New Chapter Begins - rsyslog
After 24 months of focused evaluation and careful experimentation, we’re excited to announce a major shift in the evolution of rsyslog: we’re going AI First. This marks the beginning of a strategic transformation in how we design, develop, and support rsyslog and its ecosystem. While today’s post is just a short announcement, it lays the […]

Neue Forschung zeigt, dass #ElNiño-Ereignisse, verstärkt durch den #Klimawandel, tropische #Insekten wie #Schmetterlinge

Climate-fuelled El Niño events are devastating butterflies, beetles and other tropical insects
The research suggests the life-support system underpinning the tropics is at serious risk in a warmer world.

Am Plötzenseer Kolk, einer Bucht des Schifffahrtskanals, liegt eine Siedlung an Hausbooten mit Blick auf das Weddinger Nordufer.
#meinwedding #berlinwedding #wedding65

The street names in this part of Queens, New York City, seems deliberately confusing. 🤨🗺️
(Map © #OpenStreetMap contributors, ODbL 1.0)
#NYC #NewYorkCity

From my lunch walk (this is actually right outside the @… offices)
#Oslo

FMT$^{x}$: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
Soheil Espahbodini Nia
https://arxiv.org/abs/2509.08521 https://

FMT$^{x}$: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
Path planning in dynamic environments remains a core challenge in robotics, especially as autonomous systems are deployed in unpredictable spaces such as warehouses and public roads. While algorithms like Fast Marching Tree (FMT$^{*}$) offer asymptotically optimal solutions in static settings, their single-pass design prevents path revisions which are essential for real-time adaptation. On the other hand, full replanning is often too computationally expensive. This paper introduces FMT$^{x}$, a…

Data-driven generative simulation of SDEs using diffusion models
Xuefeng Gao, Jiale Zha, Xun Yu Zhou
https://arxiv.org/abs/2509.08731 https://arxiv.org/pdf…

Data-driven generative simulation of SDEs using diffusion models
This paper introduces a new approach to generating sample paths of unknown stochastic differential equations (SDEs) using diffusion models, a class of generative AI models commonly employed in image and video applications. Unlike the traditional Monte Carlo methods for simulating SDEs, which require explicit specifications of the drift and diffusion coefficients, our method takes a model-free, data-driven approach. Given a finite set of sample paths from an SDE, we utilize conditional diffusion…

Echoes of Automation: The Increasing Use of LLMs in Newsmaking
Abolfazl Ansari, Delvin Ce Zhang, Nafis Irtiza Tripto, Dongwon Lee
https://arxiv.org/abs/2508.06445 https://

Echoes of Automation: The Increasing Use of LLMs in Newsmaking
The rapid rise of Generative AI (GenAI), particularly LLMs, poses concerns for journalistic integrity and authorship. This study examines AI-generated content across over 40,000 news articles from major, local, and college news media, in various media formats. Using three advanced AI-text detectors (e.g., Binoculars, Fast-Detect GPT, and GPTZero), we find substantial increase of GenAI use in recent years, especially in local and college news. Sentence-level analysis reveals LLMs are often used …