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#lmms

8 posts5 participants0 posts today
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Kevin Karhan :verified:

@mosgaard @amadeus if you just want distraction-free editing, you may want to look at #VScodium [1], #neovim [2] or even #NvChad [3] for editing depending on how you feel like and what suits you best.

  • I recommend using #Markdown for Text until you want to turn it into something printable (unless you know #LaTeX), but noone's gonna judge you if you prefer @libreoffice to get a script written.

If you want or need to switch computers rather often, consider buying a SATA (or NVMe) - SSD with DRAM-Cache and a matching external enclosure and install your #distro of choice on that instead, as unlike #Windows, basically all #Linux distros allow installations on external drives.
-Don't forget to use #FullDiskEncryption!

If you need to share your work with others or sync it across devices, consider @nextcloud / #nextcloud.

  • If you don't have any admin already in your organization.and it's permissible but you don't want to setup your own, consider @monocles / #monoclesOcean and @Stuxhost for a fully-managed Nextcloud at reasonable prices.

As for #audio I'm shure you know #audacity and #LMMS...

If you use the terminal rather often, consider setting up some nifty aliases to make things faster.

  • For example if you want to just check if something is reachable, i.e. internet / network connection works, consider adding function isup() { ping -a -b -c 1 -D "$@"; } to your .bash_aliases file in your $HOME directory so if you use i.e. isup duckduckgo.com it'll do a single run of ping to reach said domain/FQDN/IP...

But the final #ProTip I can give you is to #backup your $HOME-directory under /home/yourusername because in it's hidden subdirectories, espechally $HOME/.config/ are usually all the settings for your applications stored so in case you need to setup a new machine or restore one from backups, this is where all the minor changes of yours to make your system work best for you are being stored.

  • You may need to press Ctrl+H IN THE File Manager to see hidden files.

  • For backups, tools like #DéjàDup make it easy to setup, backup and restore your files as you want or need, including encryption and deduplication.

I hope that'll help you not only get started but also get the maximum efficiency out of your distro as a creative tool without fuss.

-1
-2

YouTubeNeovim in 100 SecondsBy Fireship
Public
cagibidev

I remixed the (unreleased) underground music from Warhead Stroll (game I made for one of the Ludum Dares in 2021).
Lately I'm trying to use midi/mod musics for my games to make them smaller. This is not one of those, but it feels good to go back to it anyway. Skilled tracker veterans could probably even arrange something like that I dunno.
#LMMS #IndieGame

00:00/01:28
Public
Tilda Moose, citizen

I'm super glad to be rid of M$ win7 and fully back with #UbuntuStudio, breathing new life into my 10 year old Dell desktop pc. Missing the luxury of Ableton's familiar workflow, but quickly filling the gap with #LMMS and #Ardour. Already got a dance track sketched in just a few days, most of which has been spent on familiarisation with the unknown. Now I'm the production bottleneck; sample libraries vs original recordings, self doubt as a composer, the usual. Composition encouragement welcome :)

Public
Tero Keski-Valkama

Training #AIs, whether #LLMs or #LMMs, is all about data.

They perform tasks within the distribution of their training data, and in the same level of competence.

This also applies to reinforcement learning; if you look behind the scenes, what happens is supervised learning with extra steps. The error is still backpropagated back through the network, but the objectives are slightly different. Instead of direct task performances to imitate, we'll get the feedback from exploration and rewards, basically the most successful explorations can be understood as the data.

So, the data is where the buck stops when an #AI makes a misjudgement. When designing data pipelines, refinement processes and exploratory games for your AIs, you can forget about everything you know about the mechanistic aspects of Transformer architectures, and just simply focus on how to improve the data.

The data is better if it can be used to train better models. Better models have higher competence in skills, higher volume of relevant knowledge, and higher coverage in task generalism and flexibility. Hence the best data represents exactly those aspects maximally.

Human level is not the gold standard and neither is raw real-world data. We can design processes which refine the data without apparent limits, and make that data alive through AIs trained with it.

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