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Been trying out [SiYuan](https://github.com/siyuan-note/siyuan) as a local alternative and love it so far. The files are single-line JSONs so not as ideal as Obsidian .md files, but it seems to be trivial to export to various human-friendly formats.


I use the two together with no issues. Micromamba works great for conda dependencies that’s not on PyPi (for many reasons), and everything else I go for uv.


FWIW since cherry’s switch patents expired there has been a ton of great keyboards from China. I got a PMO Wave 75 and loved it.

Mine is same as the green one in this post: https://www.reddit.com/r/MechanicalKeyboards/comments/1h8011...


Has there been recent developments in the style detection and deanonymization tools you mentioned? I would assume many would not work well given the high usage of LLMs nowadays.


A few years back a journal editor maticulously reviewed all dashes in our manuscript and pointed out places where em dashes should have been used. Since then I started noticing different dashes everywhere around the internet.


Adding dependencies to the script directly was a game-changer. I was able to write a script for a friend with no coding background at all and everything ran smoothly on his machine. No more rabbit holes of bundling Python packages and setting up environments!


Support was added for this a few versions back and made life much easier!


Does uv handle cases where dependencies go beyond Python? For example, many bioinformatics-related conda packages would come with external binaries written in C++ or other languages. Would uv be able to pull from conda?


Cool work! Curious if this can be applied back in LLMs as a discrete diffusion model with partial masking.


This is so neat! MOO has been a integral part of my work yet it has never occurred to be that Pareto optimization could be applied in kart picking.


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