If you want a device to do NFC payments you'll need to look somewhere other than GrapheneOS. (Believe me, I've tried everything)

https://discuss.grapheneos.org/d/475-wallet-google-pay

Coarse Salt. Add just enough water to move it around + a little dish soap and shake. Works like a charm.

Amazing work! I'm very excited to see mobile Linux reach a usable state for every day processing. Thank your for your time and energy. It is valuable and going to good use.

Why the Pixel 3a? Is there anything special about it (or not special, which might mean my old 3XL is good for more than gathering dust?)

How can I get involved? I know my way around C and would love to pitch in.

"Chuff" in the context of rock climbing = bad, made an effort but didn't get very far / fell a lot

Even in the US, state-level representation hardly counts as local. Neighborhoods, towns, counties, etc. all have people representing them.

It's cool to care about and build up your community.

Even faster -- tailscale. For a cheeky way to play with your friends make a burner account with a shared login to get on the same tailnet for free. On the endpoints, turn off tailscale-ssh and any of their other "features" you don't need.

I immediately thought this was salt. Maybe I'm the monster.

GrapheneOS! I've been using it for a few years. Never going back.

Is this some Network Allowed problem that I'm too Network Not Allowed to understand?

I'm a big fan of buying power tools twice. I happen to go Ryobi for the first round but Harbor Freight / Northern Tool are probably similar.

If you can stand the fuss, buy corded tools and skip the brand loyalty that comes with batteries.

The biggest killer of cheaper power tools is generally heat. There are plastic components in the drive train. They hold up great to short jobs, but heat is their kryptonite. If you let a Ryobi tool cool down whenever you notice it getting warm to the touch it'll last a long time. If you need to run a tool for hours at a time then skip the fuss and go straight to a more brand with a good reputation like DeWalt, Makita, Bosch, or Milwaukee.

Red boxes fit all brands :)

assuming you mean *can't

if cordless: batteries

else: brand cuckery

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:

Please don't assume anything, it's not healthy.

Explicitly stating assumptions is necessary for good communication. That's why we do it in research. :)

it depends on the license of that binary

It doesn't, actually. A binary alone, by definition, is not open source as the binary is the product of the source, much like a model is the product of training and refinement processes.

You can't just automatically consider something open source

On this we agree :) which is why saying a model is open source or slapping a license on it doesn't make it open source.

the main point is that you can put closed source license on a model trained from open source data

1. Actually the ability to legally produce closed source material depends heavily on how the data is licensed in that case
2. This is not the main point, at all. This discussion is regarding models that are released under an open source license. My argument is that they cannot be truly open source on their own.

Quite aggressive there friend. No need for that.

You have a point that intensive and costly training process plays a factor in the usefulness of a truly open source gigantic model. I'll assume here that you're referring to the likes of Llama3.1's heavy variant or a similarly large LLM. Note that I wasn't referring to gigantic LLMs specifically when referring to "models". It is a very broad category.

However, that doesn't change the definition of open source.

If I have an SDK to interact with a binary and "use it as [I] please" does that mean the binary is then open source because I can interact with it and integrate it into other systems and publish those if I wish? :)

Do you plan to sue the provider of your "open source" model? If so, would the goal be to force the provider to be in full compliance with the license (access to their source code and training set)? Would the goal be to force them to change the license to something they comply with?

You would be obligated, if your goal were to be complying with the spirit and description of open source (and sleeping well at night, in my opinion).

Do you have the source code and full data set used to train the "open source" model you're referring to?

My point precisely :)

A pre-trained model alone can't really be open source. Without the source code and full data set used to generate it, a model alone is analogous to a binary.

If I license a binary as open source does that make it open source?

Those bar mittens are killer too.

https://barmitts.com/

What makes it open source?

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.

I don't mean to join the broken record crew here, but is this better than Syncthing in some way?

It's been my most used feature on my Garmin Instinct 2X tbh. Glad I don't have to carry a separate gadget.

Is there a reason you're not considering running this in a VM?

I could see a case where you go for a native install on a virtual machine, attach a virtual disk to isolate your library from the rest of the filesystem, and then move that around (or just straight up mount that directory in the container) as needed.

That way you can back up your library separately from your JF server implementation and go hog wild.

Syntax-wise, it's meant to be identical. I got on board when they were the only ones that enabled rootless (without admin privileges) mode. That's no longer the case since rootless docker has been out for a while.

I'm personally a fan of the red hat docs and how-to's on podman over the mixed bag of tech bro medium articles I associate with docker.

At the end of the day this is a bit of a Pokemon starter question. If your top priority is to get a reasonably common and straightforward job done just pick one and see where it takes you! :)

Syncthing is my answer though I appreciate it doesn't get to the root of your question.

There are local backups that include your system settings, text messages, contacts, call history and (optionally) apps. The one thing I want is the ability to pick a directory for the local backup so I can make it work with syncthing without jumping through hoops.

It's also compatible with Nextcloud and WebDAV if those are options for you.

I miss my pixel 5 :(

Chiming in to note that GNSS communications are actually receive only. A typical phone can't physically broadcast a strong enough signal into mid-earth orbit (where most of those satellites typically are) to achieve the "pinging GPS satellites" issue.

Note this only refers to how that signal physically hits your phone. Once your position is deduced and digitized there's an entirely different attack surface.

The other concerns (especially cell tower data tracking) are valid though.

What would you tout?

Echoing this but change if to since :/