Tootfinder

Rätselhaftes aus dem ewigen Eis: Der ANITA-Detektor in der Antarktis hat Signale aufgefangen, die Physiker weltweit vor ein Rätsel stellen. 🧊❓
Zum Artikel: https://heise.de/-10447878?wt_mc=sm.red.ho.mastodon.mastodon.m…

Detektor in der Antarktis empfängt geheimnisvolle Signale
Ein über der Antarktis schwebender Detektor hat zwei Signale erfasst, die sich nicht mit dem Standardmodell der Teilchenphysik erklären lassen.

this might be one of the _least_ specific (but not completely non-specific) paragraphs in any specification i've ever read

Apache Flink is uniquely positioned to serve as the backbone for AI agents, equipping them with the powerful new tool of stream processing. Join Steffen Hoellinger at this year's Berlin Buzzwords to explore how Flink jobs can be transformed into “Agents”—autonomous, goal-driven entities that dynamically interact with data streams, trigger actions, and adapt their behaviour based on real-time insights.
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Didacta-Verband zu Schülerdaten: "Sehen die Gefahr der Stigmatisierung"
Schüler-ID und Bildungsverlaufsregister bieten laut dem neuen Präsidenten des Didacta-Verbands große Chancen. Ein hohes Datenschutzniveau sei aber wichtig.

Maximally-Informative Retrieval for State Space Model Generation
Evan Becker, Benjamin Bowman, Matthew Trager, Tian Yu Liu, Luca Zancato, Wei Xia, Stefano Soatto
https://arxiv.org/abs/2506.12149

Maximally-Informative Retrieval for State Space Model Generation
Given a query and dataset, the optimal way of answering the query is to make use all the information available. Modern LLMs exhibit impressive ability to memorize training data, but data not deemed important during training is forgotten, and information outside that training set cannot be made use of. Processing an entire dataset at inference time is infeasible due to the bounded nature of model resources (e.g. context size in transformers or states in state space models), meaning we must resor…

🔍 Game of Life
Entdeckt das faszinierende „Game of Life“! Aus einfachen Regeln entstehen komplexe Muster. Probiert die interaktive Simulation selbst aus und lasst Strukturen entstehen!
⏲ Uhrzeit: 17:00-24:00 Uhr
🗓️ Datum: 21.06.2025
🧑‍🔬 Veranstalter: Max-Planck-Institut für Dynamik und Selbstorganisation
📍 Veranstaltungsort: @…

Turns out the reason that the GPU accelerated level detector made the CDR slower is that I was working on test data loaded from a file, and not moving the data from CPU to GPU before starting the filter graph. So of *course* it was slower, due to the unnecessary data movement.
But that's unrealistic since on a real high-performance scope driver (e.g. thunderscope) the first thing we typically do is push data from CPU to GPU to do the int-float conversion there.
Time to repea…

sp_hospital: Hospital ward dynamic contacts (2010)
This dataset contains the temporal network of contacts between patients, patients and health-care workers (HCWs) and among HCWs in a hospital ward in Lyon, France, from Monday, December 6, 2010 at 1:00 pm to Friday, December 10, 2010 at 2:00 pm. The study included 46 HCWs and 29 patients.
This network has 75 nodes and 32424 edges.
Tags: Social, Offline, Unweighted, Temporal, Metadata

hiv_transmission: HIV transmission network (1988-2001)
A set of networks of HIV transmissions between people through sexual, needle-sharing, or social connections, based on combining 8 datasets collected from 1988 to 2001. Metadata includes test results of several diseases, as well as demographic variables such as age, ethnicity, and gender. Networks come in two flavors: egodyads and altdyads. Egodyads are the network among study-participants and their direct partners. Altdyads are the…