Tootfinder

Very good and useful historical overview of England's role in making the mess that is the middle east, from Scottish historian @DalrympleWill [X]. Britain’s colonial legacy played a key role in creating this injustice. The suffering in Gaza didn’t start yesterday, it was engineered long ago.

Deep Recommender Models Inference: Automatic Asymmetric Data Flow Optimization
Giuseppe Ruggeri, Renzo Andri, Daniele Jahier Pagliari, Lukas Cavigelli
https://arxiv.org/abs/2507.01676

Deep Recommender Models Inference: Automatic Asymmetric Data Flow Optimization
Deep Recommender Models (DLRMs) inference is a fundamental AI workload accounting for more than 79% of the total AI workload in Meta's data centers. DLRMs' performance bottleneck is found in the embedding layers, which perform many random memory accesses to retrieve small embedding vectors from tables of various sizes. We propose the design of tailored data flows to speedup embedding look-ups. Namely, we propose four strategies to look up an embedding table effectively on one core, and a framew…

🇺🇦 #NowPlaying on #BBC6Music's #6MusicsIndieForever
Ladyhawke:
🎵 My Delirium
#Ladyhawke
https://saviorself070598.bandcamp.com/track/my-delirium-tribute-to-that-dog-mix-featuring-ladyhawke
https://open.spotify.com/track/1YhzlKAGZCgFmu3maqDQtl

Delirium often goes underreported, making it hard for #AI to predict accurately. Our review of 120 studies found common data issues that hurt model reliability. We created a step-by-step guide to help build fairer, more accurate models—so we eventually can detect #delirium earlier and im…

🇺🇦 Auf radioeins läuft...
Todd Terje:
🎵 Delorean Dynamite
#NowPlaying #ToddTerje
https://gattuso.bandcamp.com/track/todd-terje-delorean-dynamite-mashup-mix
https://open.spotify.com/track/7A2i8hTjReDm8WD6WqTaZm

Report: Swiss deep tech startups have created over $100B in total enterprise value, with 60% of VC funding in Switzerland from 2019 to 2025 going to deep tech (Cate Lawrence/Tech.eu)
https://tech.eu/2025/06/26/switzerlands-100b-deeptech-engine-comes-…

Switzerland’s $100B deeptech engine comes Into focus
Today, the launch of The Swiss Deep Tech Report 2025 spotlights how Switzerland has quietly become one of the world’s most advanced and efficient deeptech ecosystems. Curated in close collaboration with Dealroom.co, Startupticker and venture capital firms Founderful and Kickfund, the report is the first of its kind to map the full scope of Switzerland’s deeptech performance - from research institutions and patents to venture activity and late-stage outcomes. With over 1500 Swiss deeptech …

De senaste två åren ungefär så har det varit en hel del debatt kring talangutveckling här i Sverige och det här och några efterföljande avsnitt kommer vi att gå igenom några av de mer kontroversiella delarna kring det här. https://tyngre.se/podcast/tyngre…

Talangutveckling del 1 - potential, nivåindelning och selektering | Podcast
Hur hittar vi framtidens stjärnor – och riskerar vi att sålla bort dem för tidigt? I första delen av en serie om talangutveckling diskuterar Jacob och Wille sel

From ⁨⁨⁨⁨⁨#AnnafromUkraine⁩⁩⁩⁩⁩ @AnnafromUkraine@youtube.com
BUNKER LUNATIC'S DELIRIUM: #PUTIN ABOUT RUSSIA ECONOMY & UKRAINE Vlog 1080: War in #Ukraine

Quantum vs. semiclassical description of in-QGP quarkonia in the quantum Brownian regime
Aoumeur Daddi-Hammou, St\'ephane Delorme, Jean-Paul Blaizot, Pol Bernard Gossiaux, Thierry Gousset
https://arxiv.org/abs/2506.19194

Quantum vs. semiclassical description of in-QGP quarkonia in the quantum Brownian regime
In this work, we explore the range of validity of the semiclassical approximation of a quantum master equation designed to describe the $c\bar{c}$ dynamics in a quark gluon plasma at various temperatures, in the quantum Brownian regime. We perform a comparative study of various properties, e.g. the charmonia yield, of the Wigner density obtained with the Lindblad equation and with the associated semiclassical Fokker-Planck equation. The semiclassical description is found to reproduce with a rem…

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Bruno Aristimunha, Dung Truong, Pierre Guetschel, Seyed Yahya Shirazi, Isabelle Guyon, Alexandre R. Franco, Michael P. Milham, Aviv Dotan, Scott Makeig, Alexandre Gramfort, Jean-Remi King, Marie-Constance Corsi, Pedro A. Vald\'es-Sosa, Amit Majumdar, Alan Evans, Terrence J Sejnowski, Oren Shriki, Sylvain Chevallier, Arnaud Delorme

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-based competition comprising two challenges. First, the Transfer Challenge asks participants to build and test a model that can zero-shot decode new tasks and new subjects from their EEG data. Second, the Psychopathology factor prediction Challenge asks participants to infer subject measures of mental health from EEG da…