All the sources are in the body of the post. Windows being in free fall is at least questionable to me, because in the source, StatCounter, windows usage has mostly been replaced by ‘unknown’.

They claim it is an open-source model but at least for now it has a custom unspecified license. I hope they change that before the actual release because right now I wouldn’t even call it open-weight

Looks good! I did see multiple places that were listed as 100% vegan even though they were tagged ‘diet:vegan=yes’ and not ‘diet:vegan=only’. I know for a fact these places aren’t vegan only, so is it possible to see how a listing was established?

There is an existing OSM based map https://veggiekarte.de/ that also has filtering options. The biggest issue is that OSM doesn’t have much detail on POIs and they’re often out of date. Even in Western Europe where most other stuff is up to date. Mostly because POIs require on the ground surveys which only a handful of contributors can do in more than one region.

So, please consider contributing to OSM using simple apps like StreetComplete or EveryDoor if you have some spare time.

Also the organisation managing the IT systems used for research and education: https://www.surf.nl/en/how-does-mastodon-work

Found it by looking up dark mode Firewatch wallpapers.

Edit: Didn’t find higher resolutions of this specific one. But here are slightly different but higher resolutions variants: https://imgur.com/a/jvkoP

And the second one in this list

https://unsloth.ai/docs/models/qwen3.6#mtp-guide
Unsloth made a guide and has graphs with comparisons

You can also contribute to OpenStreetMap in your area using simple apps like StreetComplete or EveryDoor. This has a way lower barrier to entry than contributing code in my opinion. And it has the immediate benefit of a better local map for a LOT of services that are built on top of OSM.

As long as the moderation follows their rules, and it is always as transparent as shown in this example, I don’t see an issue with this.

My only concern is that LLMs are very good at recognising biases in questions and are more likely to confirm them than push back. So the LLM might pay too much attention to small/possible infringements. But this depends heavily on the model, the prompt, and the reader.

I’m really not fond of the profiling by automated means, but it seems like an inevitable consequence of the design of the threadiverse. Everything is public and easily accessible by anyone that would like to profile you.

I certainly disapprove of moderation based on ideology. Moderation should be based on quality of the content and if it fits in the publicly readable rules. Definitely not some hidden analytics or if the user completely fits in the in-group of the moderator.

I will admit that this might be a good way to find and filter out LLM based bots that are only there to promote or manipulate the conversation. But it should still be done according to public rules.

Is this post written by an LLM?

I trust them as much as Google, Meta, or any other big tech company. I won’t use their cloud services, but I do run there local models.