Tootfinder

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Orchestral Manoeuvres In The Dark:
🎵 The New Stone Age
#OrchestralManoeuvresInTheDark
https://orchestralmanoeuvresinthedark.bandcamp.com/track/the-new-stone-age
https://open.spotify.com/track/4P9BeQkwwcWIuioP8YzeQD

TIL about the Octobass as a result of my random YouTube-live-music feed stumbling into a performance of Gounod’s “Messe Solonelle” which is pretty good and, well, has an octobass in the orchestra.
#music

Slm-mux: Orchestrating small language models for reasoning
Chenyu Wang, Zishen Wan, Hao Kang, Emma Chen, Zhiqiang Xie, Tushar Krishna, Vijay Janapa Reddi, Yilun Du
https://arxiv.org/abs/2510.05077

Slm-mux: Orchestrating small language models for reasoning
With the rapid development of language models, the number of small language models (SLMs) has grown significantly. Although they do not achieve state-of-the-art accuracy, they are more efficient and often excel at specific tasks. This raises a natural question: can multiple SLMs be orchestrated into a system where each contributes effectively, achieving higher accuracy than any individual model? Existing orchestration methods have primarily targeted frontier models (e.g., GPT-4) and perform sub…

Par #orchestredeparis @orchestredeparis@instagram.com
Billie Eilish, Chopin, Charles Aznavour... Le portrait musical de Yuja Wang in french ✨
Les 12 et 13 novembre Š la @philharmoniedeparis (https://www.instagram.co…

Orchestrating Human-AI Teams: The Manager Agent as a Unifying Research Challenge
Charlie Masters, Advaith Vellanki, Jiangbo Shangguan, Bart Kultys, Jonathan Gilmore, Alastair Moore, Stefano V. Albrecht
https://arxiv.org/abs/2510.02557

Orchestrating Human-AI Teams: The Manager Agent as a Unifying Research Challenge
While agentic AI has advanced in automating individual tasks, managing complex multi-agent workflows remains a challenging problem. This paper presents a research vision for autonomous agentic systems that orchestrate collaboration within dynamic human-AI teams. We propose the Autonomous Manager Agent as a core challenge: an agent that decomposes complex goals into task graphs, allocates tasks to human and AI workers, monitors progress, adapts to changing conditions, and maintains transparent s…

Open Webinar IIP – 14 ottobre 2025 – COMPLIANCE ORCHESTRA! Strumenti e armonie di conformitŠ integrata
https://www.istitutoitalianoprivacy.it/2025/10/05/open-webinar-iip-14-ottobre-2025-compli…

Towards Carbon-Aware Container Orchestration: Predicting Workload Energy Consumption with Federated Learning
Zainab Saad, Jialin Yang, Henry Leung, Steve Drew
https://arxiv.org/abs/2510.03970

Towards Carbon-Aware Container Orchestration: Predicting Workload Energy Consumption with Federated Learning
The growing reliance on large-scale data centers to run resource-intensive workloads has significantly increased the global carbon footprint, underscoring the need for sustainable computing solutions. While container orchestration platforms like Kubernetes help optimize workload scheduling to reduce carbon emissions, existing methods often depend on centralized machine learning models that raise privacy concerns and struggle to generalize across diverse environments. In this paper, we propose a…

Scaling Homomorphic Applications in Deployment
Ryan Marinelli, Angelica Chowdhury
https://arxiv.org/abs/2510.02376 https://arxiv.org/pdf/2510.02376

Scaling Homomorphic Applications in Deployment
In this endeavor, a proof-of-concept homomorphic application is developed to determine the production readiness of encryption ecosystems. A movie recommendation app is implemented for this purpose and productionized through containerization and orchestration. By tuning deployment configurations, the computational limitations of Fully Homomorphic Encryption (FHE) are mitigated through additional infrastructure optimizations Index Terms: Reinforcement Learning, Orchestration, Homomorphic Encryp…

iDDS: Intelligent Distributed Dispatch and Scheduling for Workflow Orchestration
Wen Guan, Tadashi Maeno, Aleksandr Alekseev, Fernando Harald Barreiro Megino, Kaushik De, Edward Karavakis, Alexei Klimentov, Tatiana Korchuganova, FaHui Lin, Paul Nilsson, Torre Wenaus, Zhaoyu Yang, Xin Zhao
https://arxiv.org/abs/2510.02930

iDDS: Intelligent Distributed Dispatch and Scheduling for Workflow Orchestration
The intelligent Distributed Dispatch and Scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the Large Hadron Collider, iDDS has evolved into an experiment-agnostic pla…

Next-Generation Event-Driven Architectures: Performance, Scalability, and Intelligent Orchestration Across Messaging Frameworks
Jahidul Arafat, Fariha Tasmin, Sanjaya Poudel, Ahsan Habib Tareq
https://arxiv.org/abs/2510.04404

Next-Generation Event-Driven Architectures: Performance, Scalability, and Intelligent Orchestration Across Messaging Frameworks
Modern distributed systems demand low-latency, fault-tolerant event processing that exceeds traditional messaging architecture limits. While frameworks including Apache Kafka, RabbitMQ, Apache Pulsar, NATS JetStream, and serverless event buses have matured significantly, no unified comparative study evaluates them holistically under standardized conditions. This paper presents the first comprehensive benchmarking framework evaluating 12 messaging systems across three representative workloads: e…