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Not an article, but it does seem to be the mission statement.

"To blend in among fellow players, cloaked and in disguise; without anybody noticing or rejecting our presence. We fulfill an intellectual challenge; a fun game of cat and mouse. We are the hunted of over three years."

https://web.archive.org/web/20090402125324/http://villavu.co...

Counting down the days until someone gets full linux on old ipads!

4 is also available on the archive! https://openlibrary.org/books/OL4272985M/Elementary_Basic

Being able to process it later on the computer would definitely be great! That's kinda what I already do via notes but it's fairly painful to match up the photos I took to the notes and times.

I'll certainly keep this in mind though.

Me!

I agree and I've been thinking about making something similar to Every Door but that takes advantage of AI to let you snap a photo or just send a voice note and then have the appropriate tags generated for review based on some very strict schemas. Would something like that be of interest to you?

Also open to feedback from anyone.

One thing I'm still trying to figure out is how this compares to something like gliner. If you're just doing classification in what situations would you choose kev vs gliner?

How long does it typically take for something like this to become available on openrouter?

I have an idea for a use case for this, and I'm wondering if you think it makes sense or if you have any thoughts on the approach.

I'm a big fan of OpenStreetMap, and I enjoy editing it from my computer. From my phone, I find it quite tedious trying to make sure I type in the phone number exactly correctly and double-check it, or find and select the right field from the large list of fields available in Upredor.

Generally, how it works is I see a restaurant, and there's a sign. I know that it says, "Cash only. Here's the phone number. Here's the opening hours." What would be really cool is if I could just speak to the phone and say, "Hey, here's the information about this place." It would automatically use your location to detect what places are nearby and maybe even detect which place you're talking about, and then tell you, "Okay, here are the changes I think you're proposing to make, or these things you stated are the ones that would create a diff." This would be limited to just perhaps the 20 most common keys in some predefined set of values for most of them. Like cuisine=x should just match to the most common not make up new ones.

Of course, this is something a large language model could do, but having it run on device would be a lot nicer and cheaper.

Any more you can share? Is he actively doing a search? I didn't see anything about it in the repo.

Do you have any examples of forks maintained by LLMs and how they do it?

I can improve the UI to my taste but if the maintainer doesn't have time/money to maintain a big ol vibe coded PR for some very opinionated change isn't going to do much.

That would appear to leave me with the choice of just using it for myself (lame) or I then have a public fork to maintain :(

If there's basically no shot of it getting up streamed I think I'd rather make something from scratch to suit my needs without the extras.

Anyway, I hope the AI overlords help us fund more maintainers soon!

Every Door is definitely one of the easier ones and I like it but dang I wish the dev could get more funding to make it a nicer UX. Between the glitchy raster tiles and need to click load data all the time I feel it gets tiring fast.

I've considered building a separate app that's similar but oriented around the idea of using voice of pictures to update things (with AI extracting and formatting the data for you to review). But alas making yet another tool isnt ideal.

I guess they got that message so they're porting to rust!

https://docs.litellm.ai/blog/litellm-rust-launch

Not another language because the performance issues are limited to the code being sync. Anyway, a gradual migration was a must as well.

This is the first I hear of Litestar and I think it does seem very values aligned. I fastapi was picked simply because it was already known by the team and had a very thriving ecosystem. That being said, the hard part is getting off the old sync web.py stuff. Once everything is in async land moving to another framework if needed is relatively trivial. Thanks for sharing that though I'll keep an eye on it!

I have been volunteering with the Internet Archive via Open Library for about half a decade now. Sending money is awesome and they're also always looking for volunteers! There are so many projects going on for Open Library and staff has quite a few volunteers but right now especially I think it would be awesome to have a few more experienced folks joining to help (many volunteers are students).

Here's just a few things we could use more experienced folks to help on:

- Solr performance, it currently gets quite slow under load and there are two read replicas but we think there may be some ways to improve it besides adding more replicas. You can run a full production copy of solr based on the dumps... But the current workflow to do this is kinda broke so I had AI fix it up but we haven't been able to verify if it's a fully working/good solution.

- We're doing big redesigns of major parts of the frontend. If your down to help for that Lokesh had many tickets open and guidelines and welcomes PRs.

- I'm currently migrating us from web.py to fastapi and could certainly use more experienced help for trickier ones.

Anyway, if you're actually willing to help all you gotta do is join our community call tomorrow at 9am PST and share your interests. We'll you on to something you like quickly :)

https://docs.openlibrary.org/everyone/community-call.html#co...

That's fair but also think about the ewaste.

I'm still hoping one of these mega AI LLMs will figure out how to install Linux on the many old iPads that become nearly useless after Apple stops updating them and you can't install new apps.