Yeah, I agree. I do use Flatpaks, Snaps, and Appimages sometimes if I can’t find a suitable deb repo/package. Flatpak is the best out of the three because they do try to avoid too much duplication through runtimes. I also use Docker quite a bit, which has similar issues (and benefits).

I assume the “kill it” comment was a little tongue-in-cheek. On small SBCs, like a Pi, or old hardware, it could be a problem. I’ve seen people with flatpaks taking up 30GB of space, which is significant. I’m not sure how much RAM it wastes. I assume running 6 different applications that have loaded 6 different versions of Qt libraries would also use significantly more RAM than just loading the system’s shared Qt libraries once.

Wastes RAM and disk space (compared to package-manager installed applications) by storing more libraries on disk and loading them into RAM rather than just using the libraries already installed on the distro. It’s probably better than Snap and Appimage though.

I think some apps allow it, not sure though. You can also move to an instance defederated from .ml if that instance is more aligned with what you’d like to see. You can also just subscribe to communities and not browse “All.”

This is more complicated than some corporate infrastructures I’ve worked on, lol.

Yeah, the image bytes are random because they’re already compressed (unless they’re bitmaps, which is not likely).

camelCase for non-source-code files. I find camelCase faster to “parse” for some reason (probably just because I’ve spent thousands of hours reading and writing camelCase code). For programming, I usually just use whatever each language’s standard library uses, for consistency. I prefer camelCase though.

OSMC’s Vero V looks interesting. Pi 4 with OSMC or Librelec could work. I’m probably going to do something like this pretty soon. I just set up an *arr stack last week, and just using my smart TV with the jellyfin app installed ATM.

My PC running the Jellyfin server can’t transcode some videos though; probably going to put an Arc a310 in it.

I think most projects left Sourceforge after they started putting adware into they’re downloads.

I’ve used this before: https://github.com/wilicc/gpu-burn?tab=readme-ov-file

Yeah, it may be a driver issue, Nvidia/pytorch handles OOM gracefully on my system.

That seems strange. Perhaps you should stress-test your GPU/system to see if it’s a hardware problem.

SD works fine for me with: Driver Version: 525.147.05 CUDA Version: 12.0

I use this docker container: https://github.com/AbdBarho/stable-diffusion-webui-docker

You will also need to install the nvidia container toolkit if you use docker containers: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

I’ve had unattended upgrades running on a home server for a couple years and haven’t had any issues.

They’re good for media centers, since the support 4k HDR. Can also use Moonlight to stream games from a PC. GPIO is useful, but I guess the PI is overpowered for most GPIO use cases at this point.

I like the Turris Omnia and (highly configurable) Turris Mox. They come with OpenWrt installed.

Some automotive infotainment systems run on Linux.

Old dual-core Pentium, lol (Haswell I think, or something from around that time), 16GB RAM. 5 16TB SATA hard disks.

IDK, looks like 48GB cloud pricing would be 0.35/hr => $255/month. Used 3090s go for $700. Two 3090s would give you 48GB of VRAM, and cost $1400 (I’m assuming you can do “model-parallel” will Llama; never tried running an LLM, but it should be possible and work well). So, the break-even point would be <6 months. Hmm, but if Severless works well, that could be pretty cheap. Would probably take a few minutes to process and load a ~48GB model every cold start though?

ZFS on TrueNAS SCALE (enables RAID-like functionality, along with many other features).

Ext4 or NTFS on everything else, simply because it’s default and I don’t use any advanced features.

This is likely just stock manipulation. Interview was in June, and just now released the day before TSMCs earnings report.