sunstoned

Second this ^

I have one and it's fine, but not directly supported by OpenWRT. Looks like Beryl and Slate are though

Well that's odd!

Here you go:

Those bar mittens are killer too.

https://barmitts.com/

Excellent notes. If I could add anything it would be on number 4 -- just. add. imagery. For the love of your chosen deity, learn the shortcut for a screenshot on your OS. Use it like it's astro glide and you're trying to get a Cadillac into a dog house.

The little red circles or arrows you add in your chosen editing software will do more to convey a point than writing a paragraph on how to get to the right menu.

Believe what you will. I'm not an authority on the topic, but as a researcher in an adjacent field I have a pretty good idea. I also self host Ollama and SearXNG (a metasearch engine, to be clear, not a first party search engine) so I have some anecdotal inclinations.

Training even a teeny tiny LLM or ML model can run a typical gaming desktop at 100% for days. Sending a query to a pretrained model hardly even shows up on HTop unless it's gigantic. Even the gigantic models only spike the CPU for a few seconds (until the query is complete). SearXNG, again anecdotally, spikes my PC about the same as Mistral in Ollama.

I would encourage you to look at more explanations like the one below. I'm not just blowing smoke, and I'm not dismissing the very real problem of massive training costs (in money, energy, and water) that you're pointing out.

https://www.baeldung.com/cs/chatgpt-large-language-models-power-consumption

I don't disagree, but it is useful to point out there are two truths in what you wrote.

The energy use of one person running an already trained model on their own hardware is trivial.

Even the energy use of many many people using already trained models (ChatGPT, etc) is still not the problem at hand (probably on the order of the energy usage from a typical search engine).

The energy use in training these models (the appendage measuring contest between tech giants pretending they're on the cusp of AGI) is where the cost really ramps up.

Amazing! I've used that before but just to look for packages offline. I'll definitely check that out.

Love the example here!

I'm still learning about available references (ex config.services.navidrome.settings.Port). What resources did you find to be the best for learning that kind of thing?

I'll accept RTFM if that's applicable :)

Based

Or dust if you want it fastest with a pretty graph

Excellent distinction! That makes a lot of sense, thank you

Hm.. if I'm reading the README correctly this is a LAN only drop mechanism between a phone and a laptop. Syncthing does that already, albeit with a cumbersome number of features and config for that use case. If that's not accurate I'm sure you'll let me know :)

I would love to see this develop an airdrop-esque Bluetooth / PAN phone to phone feature though! Especially if a compatible iOS app were available that would be really slick.