Tootfinder

Sometimes you’re just stuck in a

Jerry Jones head over heels for the new Cowboys back-up quarterback https://www.sportingnews.com/us/nfl/dallas-cowboys/news/jerry-jones-head-over-heels-new-cowboys-back-quarterback/685979ce251ec6285dbd4aca

At the Man vs. Machine hackathon, co-hosted by AI nonprofit METR to test if AI helps people code faster and better, the top prize went to an "AI-supported" team (Kylie Robison/Wired)
https://www.wired.com/story/san-francisco-hackathon-man-vs-machine/

Inside the Man vs. Machine Hackathon
At a weekend hackathon in San Francisco, more than 100 coders gathered to test whether they could beat AI—and win a $12,500 cash prize.

Found this going through my 8 year old iPad (image is from 2013 by @…)
What a difference 12 years makes, huhn?

Verfassungsgericht: Staatstrojaner sind bei "Alltagskriminalität" tabu
Die Polizei darf Staatstrojaner laut Bundesverfassungsgericht nicht einsetzen, wenn eine Tat mit Höchstfreiheitsstrafe von 3 Jahren oder weniger geahndet wird.

went to the Federated feed just for a laugh and instead discovered that Indivisible has an official mastodon account

What episode of #Baywatch are you watching today?

Beyond Distribution Shifts: Adaptive Hyperspectral Image Classification at Test Time
Xia Yue, Anfeng Liu, Ning Chen, Chenjia Huang, Hui Liu, Zhou Huang, Leyuan Fang
https://arxiv.org/abs/2509.08436

Beyond Distribution Shifts: Adaptive Hyperspectral Image Classification at Test Time
Hyperspectral image (HSI) classification models are highly sensitive to distribution shifts caused by various real-world degradations such as noise, blur, compression, and atmospheric effects. To address this challenge, we propose HyperTTA, a unified framework designed to enhance model robustness under diverse degradation conditions. Specifically, we first construct a multi-degradation hyperspectral dataset that systematically simulates nine representative types of degradations, providing a com…

AutoMLGen: Navigating Fine-Grained Optimization for Coding Agents
Shangheng Du, Xiangchao Yan, Dengyang Jiang, Jiakang Yuan, Yusong Hu, Xin Li, Liang He, Bo Zhang, Lei Bai
https://arxiv.org/abs/2510.08511

AutoMLGen: Navigating Fine-Grained Optimization for Coding Agents
Large language models (LLMs) have shown impressive performance in general programming tasks. However, in Machine Learning Engineering (MLE) scenarios such as AutoML and Kaggle competitions, achieving high performance depends heavily on expert intervention and repeated adjustments rather than simply generating correct code. When applied directly to these tasks, LLMs often lack fine-grained domain priors, and existing MLE approaches that use linear or tree-structured searches limit knowledge tran…

Cowboys, Bengals dubbed possible trade suitors for promising 26-year-old edge rusher https://www.sportingnews.com/us/nfl/dallas-cowboys/news/cowboys-bengals-trade-suitors-edge-rusher-jaelan-phillips/c7e0910c…