Absolutely wild! My close to a decade old thinkpad is now our htpc. Still plenty fast too!
fatboy93
joined 2 years ago
While I really get what you're saying, the unfortunate situation is that they are always a secondary fiddle to money
Did you try openrgb? Just curious!
https://openrgb-wiki.readthedocs.io/en/latest/Logitech-Keyboards/
Just don't get xiaomi if you're in the US. I used to have one when I moved from India last year and majority of the bands were unsupported, so I was stuck on 2G-3G speeds.
I'd love to have a compact list option as well!
Just saw this post a few minutes back and downloaded it.
Not sure if its my phone (samsung s22+) or something, but comments keep dropping and I need to reopen the post for the comments to show up.
I've started forwarding the calls to Google voice or if i accidentally pick the call, i use bixby's auto answer.
Either eay the call drops in a hot second.
I fell in love with the webapp first and now I like the android native app!
Ofcourse you'd want to lump in priests with teachers.
Boost gives me so much joy to use.
I'm just going to cheat here a bit and use chatGPT to summarize this, since I don't want to do the calculation wrong. Hope it makes sense. I'm just excited to share this!
########## Integrated GPU #########
Total inference time = Load time + Sample time + Prompt eval time + Eval time
Total inference time = 26205.90 ms + (6.34 ms/sample * 103 samples) + 29234.08 ms + 118847.32 ms
Total inference time = 26205.90 ms + 653.02 ms + 29234.08 ms + 118847.32 ms
Total inference time = 174940.32 ms
So, the total inference time is approximately 174940.32 ms.
########## Discrete GPU 6800M ######### Total inference time = Load time + Sample time + Prompt eval time + Eval time
Total inference time = 60188.90 ms + (3.58 ms/sample * 103 samples) + 7133.18 ms + 13003.63 ms
Total inference time = 60188.90 ms + 368.74 ms + 7133.18 ms + 13003.63 ms
Total inference time = 80594.45 ms
So, the total inference time is approximately 80594.45 ms. #####################################
Taking the difference Discrete - Integrated : 94345.87 ms.
Which is close to about 53% faster or about 1.5 minutes faster. The integrated GPU takes close to 175 seconds and the discrete finishes in about 81 seconds.
I do think that adding more RAM at some point could definitely help in improving the loading times, since the laptop has currently about 16Gb RAM.
Probably if you split tunnel the vpn connection from mullvad to your torrent application and not run the vpn for the entire laptop's network stack this could be done.
Alternatively, dockerize the entire vpn+torrent (+jellyfin) setup? That way the container gets the vpn but you can still access using your host ip for jellyfin.