Tootfinder

Here is the whole spoof piece, written after I went to the Coliseum to see a revival of Jonathan Miller’s 1986 production of the Mikado. It was originally posted on my blog in 2008: https://www.dcscience.net/2008/02/23/theyll-none-of-em-be-missed/

The Custom #Tenant Code Nightmare (And How to Wake Up) 🏗️
🔥 Managing dozens of customer branches wastes 40% of development time on merges instead of features
🎨 Custom Views: Use fallback patterns
or customer-specific directories for branding without logic changes
⚙️ Custom Services: Swap implementations via dependency injection - same interface, different providers
…

Anthony Pompliano's ProCap raised $750M , including $235M in convertible debt, and is going public via a SPAC; the new firm aims to hold up to $1B in bitcoin (MacKenzie Sigalos/CNBC)
https://www.cnbc.com/2025/06/23/pompliano-procap-spac-bitcoin.html…

Pompliano’s ProCap raises over $750 million, goes public via SPAC as bitcoin treasury bubble grows
Led by investor and podcast host Anthony Pompliano, ProCap raised more than $750 million in its funding round, including $235 million in convertible debt.

foursquare_friendships: Foursquare global friendships (2013)
A network of user friendships on Foursquare, from April 2012 to September 2013. The 'old' and 'new' dataset correspond to two snapshots taken before and after the check-in data collection period.
This network has 114324 nodes and 607333 edges.
Tags: Social, Online, Unweighted

wandklexe ahoi!
#Kundenglücklichmachungsposteinlieferungsgeräusch

@…
Nash Rambler (I think) spotted at 0:46
My parents owned a Nash in the late fifties, replaced it with a Chevy Corvair in 1960 or so. I wasn’t yet ten so no real memories (and no photos, which is odd bc my father was a shutterbug).

Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework
Hongyi Tang, Zhihao Zhu, Yi Yang
https://arxiv.org/abs/2507.16414 http…

Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework
The performance of large language models (LLMs) is closely tied to their training data, which can include copyrighted material or private information, raising legal and ethical concerns. Additionally, LLMs face criticism for dataset contamination and internalizing biases. To address these issues, the Pre-Training Data Detection (PDD) task was proposed to identify if specific data was included in an LLM's pre-training corpus. However, existing PDD methods often rely on superficial features like …

Tag 5
Ein Phänomen auf der Strecke ist der Kalterer See. Trotz seines Namens ist er - weil er so flach ist - besonders warm. Wir haben Trotz Regenwetter gebadet. Übrigens an der einzigen frei zugänglichen Stelle am See. Quartier etwas entfernt in Auer.
#MeinRadUrlaub2025 #KaltererSee

🇺🇦 Auf radioeins läuft...
Talking Heads:
🎵 Road To Nowhere
#NowPlaying #TalkingHeads
https://josephebean.bandcamp.com/track/12-talking-heads-road-to-nowhere-v-110
https://open.spotify.com/track/6JTCH5tFwpTXIyPeWRaUK7

Detecting LLM-Generated Short Answers and Effects on Learner Performance
Shambhavi Bhushan, Danielle R Thomas, Conrad Borchers, Isha Raghuvanshi, Ralph Abboud, Erin Gatz, Shivang Gupta, Kenneth Koedinger
https://arxiv.org/abs/2506.17196

Detecting LLM-Generated Short Answers and Effects on Learner Performance
The increasing availability of large language models (LLMs) has raised concerns about their potential misuse in online learning. While tools for detecting LLM-generated text exist and are widely used by researchers and educators, their reliability varies. Few studies have compared the accuracy of detection methods, defined criteria to identify content generated by LLM, or evaluated the effect on learner performance from LLM misuse within learning. In this study, we define LLM-generated text wit…