Tootfinder

Leuk als je iets tegenkomt wat nog volledig nieuw voor je is, in dit geval SCION ( Scalability, Control, and Isolation On Next‑Generation Networks).
https://www.cwi.nl/nl/nieuws/nlnet-en-cwi-presenteren-eerste-openbare-scion-verbinding-in-…

NLnet en CWI presenteren eerste openbare SCION-verbinding in Nederland
NLnet en het Centrum Wiskunde & Informatica (CWI) lanceren een demonstratie van de eerste openbare verbinding in Nederland met het SCION-netwerk - een nieuwe, veiligere internetarchitectuur, op 14 augustus 2025.

I forgot to mention why I was thinking about Solid. It’s because I was scrolling through the NLnet-sponsored projects and saw a lot of them.
https://nlnet.nl/project/current.html

Three-year Program in Logic and Debate. The Art of Reasoning in the Nālandā Tradition https://networks.h-net.org/group/announcements/20122261/three-year-program-logic-and-debate-art-reasoning-nalanda-tradition…

🇺🇦 #NowPlaying on #BBC6Music's #AmbientFocus
Nailah Hunter:
🎵 Soil: Song From Silence
#NailahHunter
https://nailahhunter.bandcamp.com/album/soil-song-from-silence
https://open.spotify.com/track/1QvRfhVSjCli5o4o8mB1wN

🇺🇦 #NowPlaying on BBCRadio3's #ThroughTheNight
Wilhelm Kienzl, Benjamin Butterfield, Peter Neelands, The Canadian Children's Opera Chorus, Canadian Opera Company Orchestra & Richard Bradshaw:
🎵 Selig sind, die Verfolgung leiden (from Act 2 of 'Der Evangelimann')

Damn, do I want this job! https://nlnet.nl/foundation/jobs/assessor.html

Large Language Model-Empowered Channel Prediction and Predictive Beamforming for LEO Satellite Communications
Zhixiong Chen, Hyundong Shin, Arumugam Nallanathan, Jonathon Chambers
https://arxiv.org/abs/2510.10561

Large Language Model-Empowered Channel Prediction and Predictive Beamforming for LEO Satellite Communications
Accurate channel prediction and effective beamforming are essential for low Earth orbit (LEO) satellite communications to enhance system capacity and enable high-speed connectivity. Most existing channel prediction and predictive beamforming methods are limited by model generalization capabilities and struggle to adapt to time-varying wireless propagation environments. Inspired by the remarkable generalization and reasoning capabilities of large language models (LLMs), this work proposes an LLM…

Efficient LLM Inference over Heterogeneous Edge Networks with Speculative Decoding
Bingjie Zhu, Zhixiong Chen, Liqiang Zhao, Hyundong Shin, Arumugam Nallanathan
https://arxiv.org/abs/2510.11331

Efficient LLM Inference over Heterogeneous Edge Networks with Speculative Decoding
Large language model (LLM) inference at the network edge is a promising serving paradigm that leverages distributed edge resources to run inference near users and enhance privacy. Existing edge-based LLM inference systems typically adopt autoregressive decoding (AD), which only generates one token per forward pass. This iterative process, compounded by the limited computational resources of edge nodes, results in high serving latency and constrains the system's ability to support multiple users…

5G Core Fault Detection and Root Cause Analysis using Machine Learning and Generative AI
Joseph H. R. Isaac, Harish Saradagam, Nallamothu Pardhasaradhi
https://arxiv.org/abs/2508.09152

5G Core Fault Detection and Root Cause Analysis using Machine Learning and Generative AI
With the advent of 5G networks and technologies, ensuring the integrity and performance of packet core traffic is paramount. During network analysis, test files such as Packet Capture (PCAP) files and log files will contain errors if present in the system that must be resolved for better overall network performance, such as connectivity strength and handover quality. Current methods require numerous person-hours to sort out testing results and find the faults. This paper presents a novel AI/ML-…

🇺🇦 #NowPlaying on #BBC6Music's #6MusicArtistCollection
The White Stripes:
🎵 Dead Leaves and the Dirty Ground
#TheWhiteStripes
https://neilanthony.bandcamp.com/track/dead-leaves-and-the-dirty-ground-the-white-stripes
https://open.spotify.com/track/2ewjgFhHDTE8BkV8kzpiX2