Tootfinder

https://www.theregister.com/2025/10/29/afp_ai_commissioner_barrett_speech/
“Australia’s Federal Police (AFP) is working on an AI to interpret emojis and the slang used online by Generation Z and Generation Alpha, so it can understand them when they disc…

Australian police building AI to translate emoji used by ‘crimefluencers’
: Five Eyes intel alliance has created a team to target these scum who prey on kids

Our brains are shrinking

AI video generation startup Higgsfield raised a $50M Series A led by GFT Ventures (Amit Chowdhry/Pulse 2.0)
https://pulse2.com/higgsfield-50-million-series-a-raised-to-transform-ai-video-creation/

Higgsfield: $50 Million Series A Raised To Transform AI Video Creation
Higgsfield.ai, a rapidly growing company specializing in AI for video creation, has announced the successful close of its $50 million Series A funding round. The investment was led by GFT Ventures and joined by a group of firms, including BroadLight Capital, NextEquity Partners, AI Capital Partners, Menlo Ventures, Alpha Square Group, and other strategic backers. 

The Influence of Magnetic Complexity of Active Regions on Solar Wind Properties During Solar Cycles 23 and 24
Xinzheng Shi, Hui Fu, Zhenghua Huang, Limei Yan, Qi Liu, Lidong Xia
https://arxiv.org/abs/2510.08975

The Influence of Magnetic Complexity of Active Regions on Solar Wind Properties During Solar Cycles 23 and 24
Linking solar wind properties to the activities and characteristics of its source regions can enhance our understanding of its origin and generation mechanisms. Using the Mount Wilson magnetic classification (MWMC), we categorize all active regions (ARs) between 1999 and 2020 into three groups: alpha, beta, and complex ARs. Subsequently, we classify the near-Earth AR solar wind into the corresponding three types based on the magnetic type of ARs. Our results show that alpha, beta, and complex A…

An Adaptive Multi Agent Bitcoin Trading System
Aadi Singhi
https://arxiv.org/abs/2510.08068 https://arxiv.org/pdf/2510.08068…

An Adaptive Multi Agent Bitcoin Trading System
This paper presents a Multi Agent Bitcoin Trading system that utilizes Large Lan- guage Models (LLMs) for alpha generation and portfolio management in the cryptocur- rencies market. Unlike equities, cryptocurrencies exhibit extreme volatility and are heavily influenced by rapidly shifting market sentiments and regulatory announcements, making them difficult to model using static regression models or neural networks trained solely on historical data [53]. The proposed framework overcomes this by…