Tootfinder

@… @… You folks are making it hard to not be there!

I really miss the Windows Disk Defragmenter. It was so soothing.
So I made my own. And you can run this one as many times as you like; it’ll generate you a new (fake) file system to defragment every time.
Enjoy, folks.

Folks in NZ are starting to realise the implications of the impending EOL of Microsoft Windows 10 for our education system. In its finite wisdom, our MinOfEd has effectively locked all schools into either the use of MS Windows or Google ChromeOS. Both have fundamental issues like endless license hassles, EOLing OSs, ending support for Window or ChromeOS on specific computer models, etc. And that doesn't even start to talk about digital colonisation & sovereignty (see

lol, basically every single example in this post shows how the LLM is just generating context that's not in the actual image. But somehow this is sold as being better than "classical" computer vision.
I don't know folks, if I actually wanted to do "data science", with focus on the "science" bit, I'd be disturbed by that. 🤷‍♂️
https://fosstodon.org/@Posit/114597245963405210

Extracting Information About Publication Venues Using Citation-Informed Transformers
Brian D. Zimmerman, Joshua Folkins, Olga Vechtomova
https://arxiv.org/abs/2506.08199

Extracting Information About Publication Venues Using Citation-Informed Transformers
Scientific document embeddings contain a variety of rich features which can be harnessed for downstream tasks such as recommendation, ranking, and clustering. We explore which tangible insights can be drawn from scientific document embeddings to understand trends in computer science research featured across nine well-known venues. We collect approximately 60,000 scientific documents published between 2015 and 2023 and analyze their embeddings, which we produce with the SPECTER pre-trained langu…