Tootfinder

Shocked, I'm shocked! Well, not that shocked.
https://flipboard.com/@gothamist/gothamist-igeoft02z/-/a-N3M9gpszT3G9Dz67HpEV4g:a:3807498986-/0

Mayor Adams fumbles NYC bike storage program, councilmembers say
Mayor Eric Adams has slighted cyclists yet again, City Councilmembers say. Local lawmakers have criticized the mayor in recent weeks for failing to …

What do y’all do with the Nintendo Switch when you get the Switch 2? Sell it? Put it in storage?
Switch 2 will presumably play most of the Switch 1 games but local multiplayer across generations will not work easily, I guess? Why would I keep it in any capacity?

Community Detection in Energy Networks based on Energy Self-Sufficiency and Dynamic Flexibility Activation
Philipp Danner, Hermann de Meer
https://arxiv.org/abs/2506.19412

Community Detection in Energy Networks based on Energy Self-Sufficiency and Dynamic Flexibility Activation
The global energy transition towards distributed, smaller-scale resources, such as decentralized generation and flexible assets like storage and shiftable loads, demands novel control structures aligned with the emerging network architectures. These architectures consist of interconnected, self-contained clusters, commonly called microgrids or energy communities. These clusters aim to optimize collective self-sufficiency by prioritizing local energy use or operating independently during wide-ar…

@… I’m using Digital Ocean for static file hosting and it’s legit. $5/month for practically infinite storage.
Thinking of switching to Exoscale though, because it’s local and I might be able to get it even cheaper.

LEANN: A Low-Storage Vector Index
Yichuan Wang, Shu Liu, Zhifei Li, Yongji Wu, Ziming Mao, Yilong Zhao, Xiao Yan, Zhiying Xu, Yang Zhou, Ion Stoica, Sewon Min, Matei Zaharia, Joseph E. Gonzalez
https://arxiv.org/abs/2506.08276

LEANN: A Low-Storage Vector Index
Embedding-based search is widely used in applications such as recommendation and retrieval-augmented generation (RAG). Recently, there is a growing demand to support these capabilities over personal data stored locally on devices. However, maintaining the necessary data structure associated with the embedding-based search is often infeasible due to its high storage overhead. For example, indexing 100 GB of raw data requires 150 to 700 GB of storage, making local deployment impractical. Reducing…

Optimizing Cloud-to-GPU Throughput for Deep Learning With Earth Observation Data
Akram Zaytar, Caleb Robinson, Girmaw Abebe Tadesse, Tammy Glazer, Gilles Hacheme, Anthony Ortiz, Rahul M Dodhia, Juan M Lavista Ferres
https://arxiv.org/abs/2506.06235

Optimizing Cloud-to-GPU Throughput for Deep Learning With Earth Observation Data
Training deep learning models on petabyte-scale Earth observation (EO) data requires separating compute resources from data storage. However, standard PyTorch data loaders cannot keep modern GPUs utilized when streaming GeoTIFF files directly from cloud storage. In this work, we benchmark GeoTIFF loading throughput from both cloud object storage and local SSD, systematically testing different loader configurations and data parameters. We focus on tile-aligned reads and worker thread pools, usin…

Trying to use old USB hard drives I found in a drawer as additional local backup storage is not going well.
One disconnects after some time. Another stays connected but has a bad block.

Machine Intelligence on Wireless Edge Networks
Sri Krishna Vadlamani, Kfir Sulimany, Zhihui Gao, Tingjun Chen, Dirk Englund
https://arxiv.org/abs/2506.12210

Machine Intelligence on Wireless Edge Networks
Deep neural network (DNN) inference on power-constrained edge devices is bottlenecked by costly weight storage and data movement. We introduce MIWEN, a radio-frequency (RF) analog architecture that ``disaggregates'' memory by streaming weights wirelessly and performing classification in the analog front end of standard transceivers. By encoding weights and activations onto RF carriers and using native mixers as computation units, MIWEN eliminates local weight memory and the overhead of analog-t…

Robust Distributed Phase Retrieval for Multi-View Compressive Networked Sensing With Outliers
Ming-Hsun Yang
https://arxiv.org/abs/2505.24651 https://

Robust Distributed Phase Retrieval for Multi-View Compressive Networked Sensing With Outliers
This work examines the multi-view compressive phase retrieval problem in a distributed sensor network, where each sensor device, limited by storage and sensing capabilities, can access only intensity measurements from an unknown part of the global sparse vector. The goal is to enable each sensor to recover its observable sparse signal when measurements are corrupted by outliers. To achieve reliable local signal recovery with limited data access, we propose a distributed reconstruction algorithm…

"World’s largest 1 MW/100 MWh sand battery commissioned in Finland"
#Finland #Energy #Battery #Renewables

World’s largest 1 MW/100 MWh sand battery commissioned in Finland
Finnish startup Polar Night Energy has commissioned the world’s largest sand battery in Pornainen, southern Finland. The industrial-scale system delivers 1 MW of thermal power with 100 MWh storage capacity, covering up to a month’s summer heat demand and nearly a week’s winter demand for the local district heating network.