

Same, 8 heads is way overkill for my simple 0.4/0.6/0.8mm nozzle swap use case but I wanted to build something. :)


Same, 8 heads is way overkill for my simple 0.4/0.6/0.8mm nozzle swap use case but I wanted to build something. :)
I am happy if someone uses AI first to come up with a coherent message, bug report, or question.
LLMs do not add anything of value to bug reports, they add unecessary padding requiring me to filter out the marketing speech to get down to the issue. I would much rather have the raw brain dump of theirs.
If somebody sends me their ChatGPT text I now ask them to send me their prompt instead so I don’t have to waste my time on their lengthy text that has the same amount of information as the original.
I am annoyed if it’s ill-researched/understood nonsense, AI assisted or not.
Being coherent is rarely the problem in bug reports, it’s the user not properly typing out what the actual issue is.
I have gotten bullet point list bug reports that read like they were written by an insane person that were more useful than a nicely written ChatGPT message with 0 information in it.


CoreELEC can do it on Dolby Vision certified devices if you’re looking for a open source solution.
Fedora 43 with the Rawhide kernel.
gpt-oss is pretty much unusable without custom system prompt.
Sycophancy turned to 11, bullet points everywhere and you get a summary for the summary of the summary.
Of course, self hosted with llama-swap and llama.cpp. :)
I have a Strix Halo machine with 128GB VRAM so I’m definitely going to give this a try with gpt-oss-120b this weekend.


Yes, that’s still a bit annoying unfortunately.
Editing the fstab to properly mount a network share also currently has no UI available in KDE and has to be done manually.


but to discover it on my other linux machine is always a chore that involves editing a few config files and just kinda randomly poking around until it works.
What’s your desktop environment? On KDE you can just enter smb://serverhost/path in the Dolphin navigation bar and it will open it.


Indeed. Connections to my Tor bridge dropped by 80% when Iran disconnected.


I bought a used Tesla model 3 just before Elon started donating to the GOP and I’m going to disconnect the WiFi and 5G antennas this weekend
If it’s old enough you can even strip out the entire connectivity module or the physical SIM.


The first one I think is a fundamental limitation in that display preferences by default is per-user. Maybe this makes it work for you? https://feddit.online/post/1350756/comment/6636228
I don’t really have this problem anymore since I got rid of my projector which advertised a resolution it couldn’t handle. Had to login into the void since the login screen never showed up. Looks like this might be fixable nowadays.
The 24h clock might be similar - check your system-wide locale.
The locale is set to American English but the time format is set to German, something the lock screen can handle but SDDM cannot. I also tried applying the Plasma settings to SDDM a few times but it doesn’t really change anything.


It always chooses the default highest resolution, (which may not work on some devices with faulty EDID), does not respect the Wayland/X11 choice, has a long pause when going from login screen to desktop and does not support 24h clocks.
Just to name a few.


How drunk are these guys?
Ask the dude that renamed Twitter to X (formerly Twitter).


PipePipe/NewPipe also have support for streaming directly from CCC.
Same, still got the devkit 1 and 2 in my cellar.
Really looking forward to the Steam Frame to finally get standalone VR without Meta involvement.
AND per app focus stealing prevention settings.
It does? BRB, putting Steam on the lowest level possible so I can turn everything else back up.


The EU store ships from the EU with warranty, support, etc. for quite a hefty premium. I ordered from the global store which ships from Hong Kong. Paid ~500€ a year ago (including taxes).
As a side note, Qwen3.6-27B is much more capable than Qwen3.6-35B, even though it is much slower.
https://huggingface.co/unsloth/Qwen3.6-27B-GGUF
For coding tasks where you don’t mind waiting, you should be able to barely squeeze in the 8-bit quantized version with 32 GB RAM + 8 GB VRAM and have a pretty competent local model. 4-bit quants work but they have issues with complex tool calls.
If you use the MTP branch of llama.cpp (and a suitable model) you can even double or triple your token generation speed: https://github.com/ggml-org/llama.cpp/pull/22673
For easier tasks, disable reasoning for instant responses.