Tootfinder

Moral rot within journalism makes it hard for ethical practitioners to do their jobs, as they watch successful people in the field displaying malleable ethics (Marisa Kabas/The Handbasket)
https://www.thehandbasket.co/p/moral-rot-elite-journalism-nuzzi-lizz…

Moral rot in elite journalism is killing the whole field
The Nuzzi/RFK Jr. mess and the revelation of Esptein's journo pals lay bare a profound moral absence at the heart of our free press.

A protest does not become a rebellion merely because the protestors advocate for myriad legal or policy changes, are well organized, call for significant changes to the structure of the U.S. government, use civil disobedience as a form of protest, or exercise their Second Amendment right to carry firearms as the law currently allows.
Nor does a protest become a rebellion merely because of sporadic and isolated incidents of unlawful activity or even violence committed by rogue particip…

"Not Guilty"
A not-at-all-subtle reminder to Trump that he's just the president — and that means his power is limited. And: The Seventh Circuit keeps troop deployment blocked in Illinois.

My latest blog entry is an off-the-cuff interview of ChatGPT about the meaning of consciousness.
Philosophical Dialogues with AI, by @…
https://

Philosophical Dialogues with AI
Wherein I explore some aspects of moral philosophy with ChatGPT-5

Berlin-based Mirelo, whose AI models can interpret video content to add matching sound effects, raised a $41M seed led by Index and a16z, after a $3M pre-seed (Anna Heim/TechCrunch)
https://techcrunch.com/2025/12/15/mirelo-raises-41m…

Mirelo raises $41M from Index and a16z to solve AI video's silent problem | TechCrunch
Mirelo, a German startup that is building AI to add synced sound effects to videos, has raised a $41 million seed round led by Index Ventures and Andreessen Horowitz.

Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
Yuxiang Mai, Qiyue Yin, Wancheng Ni, Pei Xu, Kaiqi Huang
https://arxiv.org/abs/2509.14276

Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
In recent years, diversity has emerged as a useful mechanism to enhance the efficiency of multi-agent reinforcement learning (MARL). However, existing methods predominantly focus on designing policies based on individual agent characteristics, often neglecting the interplay and mutual influence among agents during policy formation. To address this gap, we propose Competitive Diversity through Constructive Conflict (CoDiCon), a novel approach that incorporates competitive incentives into coopera…

Mooi artikel.
#wijers #feeks

De feeks, de heks en het lek - Reporters Online
De val van informateur Hans Wijers begon met één lek en eindigde in een morele storm die groter werd dan […]

Laughlin charge pumping from interplay of chiral Dirac and chiral Majorana modes
Zhan Cao, Yang Feng, Zhi-Hai Liu, Ke He
https://arxiv.org/abs/2509.14512 https://

Laughlin charge pumping from interplay of chiral Dirac and chiral Majorana modes
Laughlin charge pumping has provided critical insights into the topological classification of individual materials, but remains largely unexplored in topological junctions. We explore Laughlin charge pumping in junctions composed of a chiral topological superconductor sandwiched between two quantum anomalous Hall insulators, driven by an adiabatically varying magnetic flux. Here, charge pumping can be mediated merely by chiral Dirac modes or by the interplay of chiral Dirac and chiral Majorana …

Sam Altman says OpenAI is "not the elected moral police of the world" after receiving backlash for saying ChatGPT will allow "erotica for verified adults" (Ashley Capoot/CNBC)
https://www.cnbc.com/2025/10/15/altman-open-ai-moral-police-ero…

Sam Altman says OpenAI isn't 'moral police of the world' after erotica ChatGPT post blows up
OpenAI CEO Sam Altman said his company is "not the elected moral police of the world" after receiving backlash over his decision to allow erotica on ChatGPT.

LEED: A Highly Efficient and Scalable LLM-Empowered Expert Demonstrations Framework for Multi-Agent Reinforcement Learning
Tianyang Duan, Zongyuan Zhang, Songxiao Guo, Dong Huang, Yuanye Zhao, Zheng Lin, Zihan Fang, Dianxin Luan, Heming Cui, Yong Cui
https://arxiv.org/abs/2509.14680

LEED: A Highly Efficient and Scalable LLM-Empowered Expert Demonstrations Framework for Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) holds substantial promise for intelligent decision-making in complex environments. However, it suffers from a coordination and scalability bottleneck as the number of agents increases. To address these issues, we propose the LLM-empowered expert demonstrations framework for multi-agent reinforcement learning (LEED). LEED consists of two components: a demonstration generation (DG) module and a policy optimization (PO) module. Specifically, the DG module …

Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
Simin Li, Zheng Yuwei, Zihao Mao, Linhao Wang, Ruixiao Xu, Chengdong Ma, Xin Yu, Yuqing Ma, Qi Dou, Xin Wang, Jie Luo, Bo An, Yaodong Yang, Weifeng Lv, Xianglong Liu
https://arxiv.org/abs/2509.15103

Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
Partial agent failure becomes inevitable when systems scale up, making it crucial to identify the subset of agents whose compromise would most severely degrade overall performance. In this paper, we study this Vulnerable Agent Identification (VAI) problem in large-scale multi-agent reinforcement learning (MARL). We frame VAI as a Hierarchical Adversarial Decentralized Mean Field Control (HAD-MFC), where the upper level involves an NP-hard combinatorial task of selecting the most vulnerable agen…