to clarify:

The developers of the Alpine Linux-based postmarketOS mobile distribution today that they’re now supporting the systemd init system alongside OpenRC and other alternative init systems.

and:

postmarketOS currently supports the Sxmo, Phosh, GNOME Shell on Mobile, and KDE Plasma Mobile UIs. While the Sxmo images will stay with OpenRC, the GNOME and KDE Plasma Mobile images will be built on top of systemd

this is the ad-free version, which is available with the exact same (if I'm correct) features on F-Droid for free, along with the source code on GitHub.

the versions on the Play Store (paid version and free version with ads) likely just help pay the developer for their work

and as others have said already, free software is free as in freedom, not free beer.

you could use Termux::API to get stats (battery percentage, notifications, calls, some other stuff) of your phone from your PC.

this video gives good examples

also didn't know you could pipe text into lolcat like that

oh ok

I do appreciate the fact that more private Piped links are provided instead of direct YouTube links (my bad btw), although direct ways of saying thank you (messaging developers, sending donations, providing feedback) would be more useful and productive

thanks for the advice. I'm also not a fan of those type of comments too lol

yeah, the training environment was a basic bullet hell "game" (really just bullets being fired at the player and at random directions) to teach the neural network basic bullet dodging skills

• the white dot with 2 surrounding squares is the player and the red dots are bullets
• the data input from the environment is at the top-left and the confidence levels for each key (green = pressed) are at the bottom-left
• the scoring system is basically the total of all bullet distances

• this was one of the training sessions
• the fitness does improve but stops improving pretty quickly
• the increase in validation error (while training error decreased) is indicated overfitting
  • it's kinda hard to explain here but basically the neural network performs well with the training data it is trained with but doesn't perform well with training data it isn't (which it should also be good at)

oh another restic user

yeah restic is a very good choice

it even works with incremental backups so you don't waste as much space as other solutions

I always find it interesting to see how optimization algorithms play games and to see how their habits can change how we would approach the game.

me too! there aren't many attempts at machine learning in this type of game so I wasn't really sure what to expect.

Humans would usually try to find the safest area on the screen and leave generous amounts of space in their dodges, whereas the AI here seems happy to make minimal motions and cut dodges as closely as possible.

yeah, the NN did this as well in the training environment. most likely it just doesn't understand these tactics as well as it could so it's less aware of (and therefore more comfortable) to make smaller, more riskier dodges.

I also wonder if the AI has any concept of time or ability to predict the future.

this was one of its main weaknesses. the timespan of the input and output data are both 0.1 seconds - meaning it sees 0.1 seconds into the past to perform moves for 0.1 seconds into the future - and that amount of time is only really suitable for quick, last-minute dodges, not complex sequences of moves to dodge several bullets at a time.

If not, I imagine it could get cornered easily if it dodges into an area where all of its escape routes are about to get closed off.

the method used to input data meant it couldn't see the bounds of the game window so it does frequently corner itself. I am working on a different method that prevents this issue, luckily.

that's ok. we all make mistakes

Falling Lightblocks is a brilliant open-source Tetris clone for Android, with different gamemodes, multiplayer, leaderboards and a "campaign" mode. definitely worth your time

another cave story user on fedi!! very cool

i know someone with that exact bg too lol

despite being a good paint editor for Windows, it is unfortunately not open source or source released (I thought it was as well):

However, citing issues with the open source code being plagiarised by others that had rebranded the software as their own and bundled user content without their permission, the availability of the source code was restricted

In November 2009, the software was made proprietary, restricting the sale or creation of derivative works of the software.

the developer talks more about it here and here

wow this is great

oh that's cool

the body of the post has the ringtone attached. I might need to edit it to make it viewable through Photon but you can also view it on a browser

good bot

currently, yes, but this is more an investigation into how well a neural network could play a bullet hell game

very few bullet hell AI programs rely on machine learning and virtually all of the popular ones use algorithms.

but it is interesting to see how it mimics human behaviour, skills and strategies and how different methods of machine learning perform and why

(plus I understand machine learning more than the theory behind those bullet hell bots.)

thanks for this!! there's so much info on this comment

i'm currently using Logseq w/ Syncthing but i'll be looking at Org Mode and DokuWiki

one problem ive seen with these game ai projects is that you have to constantly tweak it and reset training because it eventually ends up in a loop of bad habits and doesnt progress

you're correct that this is a recurring problem with a lot of machine learning projects, but this is more a problem with some evolutionary algorithms (simulating evolution to create better-performing neural networks) where the randomness of evolution usually leads to unintended behaviour and an eventual lack of progression, while this project instead uses deep Q-learning.

the neural network is scored based on its total distance between every bullet. so while the neural network doesn't perform well in-game, it does actually score very good (better than me in most attempts).

so is it even possible to complete such a project with this kind of approach as it seems to take too much time to get anywhere without insane server farms?

the vast majority of these kind of projects - including mine - aren't created to solve a problem. they just investigate the potential of such an algorithm as a learning experience and for others to learn off of.

the only practical applications for this project would be to replace the "CPU" in 2 player bullet hell games and maybe to automatically gauge a game's difficulty and programs already exist to play bullet hell games automatically so the application is quite limited.

I think dwm can be compiled (and is very minimal so quick to compile) with different minimum widths and heights.

there's also dwl, which is supposed to be dwm but native Wayland rather than X, but I haven't tried it out

what's ram usage like?

in terms of the quality of writing you can get models from 20GB at a similar level to GPT-4 (good for creative writing but much worse if knowledge of something is required)

the model I use (~20GB) would know what rclone is but would most likely not know how to use it

EDIT: now that I think about it is was based off of some benchmark. personally I wouldn't say it performs at GPT-4 but maybe GPT-3.5

oh wow another colemak-dh user

but I'd avoid converting until you're able to touch-type. then you can show off to everyone w/ your weird-looking keyboard layout lol

you're right that abuse would be the biggest issue, made worse if people host ads for many people. ideally people would naturally host few ads in a similar fashion to smaller instances (ideally) federating with few instances? also didn't realise that so many webrings still exist until I searched them up

I did create a music NN and started coding an UNO NN, but apart from that, no

Gentoo

I'll try explain the idea more concisely:

• user wants to promote own website
• user creates ads (small banners and gifs) like these and hosts them on an instance of the software through their website
  • the server-side implementation would have an API to fetch the URL of the advertisements from to embed to the website (just simple image files or gifs)
• user asks other people (friends, others in the fediverse) to save their website on these peoples' own lists of websites that they are willing to host the ads for
  • people would host based off of similar content, interesting topics, and general goodwill as opposed to exposure (as very few personal websites get constant exposure to large audiences) and revenue (as this would be a willing move)
• the client-side implementation of those hosting other websites' ads would randomly pick a URL from the user's own list (similar to picking a random URL from a webring), use the API (something like /get_ad?) to retrieve the URL of a random ad from the promoting user and display that on their website
• "automatic" was a bad word choice, I'll change it now
• this wouldn't solve a problem, just automate the functions of webrings by giving every user their own decentralised "webring" (the list of websites) and displaying user-curated ads (probably at the bottom of the page where most banners are) as opposed to randomly picking from a webring
• those using personal websites would be the users, while visitors would be the audience.

should've made the wording more clearer in the post, my bad I guess. and to clarify, this is just an concept I thought about though and I don't actually have plans to develop this. (I've also edited the post with my final opinion on the subject.)

I'll just copy a previous reply:

the ads would ideally be limited to banners and gifs in the same style as these, with each user choosing whose ads they wish to host

no revenue or popularity (these are only for personal websites) would (hopefully) prevent users from hosting invasive ads. quite a few personal websites have banners linking to others, so this would be a more simpler approach

(although in principle, a whole project dedicated to automate this doesn’t sound good)>

looks great! love the pixel font. I should switch from dwm to dwl someday

another Terminus (and Catppuccin) user I see!
beautiful setup

no problem!

I'm in the same position because FlorisBoard will over time have all the features that HeliBoard has but HeliBoard has those already so I may switch too

yeah, my bad. edited the comment with more accurate info

and this does apply to creative writing, not knowledgeable stuff like coding

android only, but this app is great for time tracking. it does everything you list and much more, like individual activities that can be categorised, tags for activities, setting time goals, statistics to show time spent and streaks and so much more.

not sponsored but it really is worth a look

edit: also GPLv3 licensed

yeah, that was the main reason I wanted to apply it to old Reddit specifically, because it would have been easier with simpler theming and old Reddit is close to Lemmy's style too

I installed RES beforehand, but haven't used any of its features. I'll try this out first and maybe Stylish if that doesn't work. thanks!

okay thanks for the tip! I'm already using Stylish but I couldn't find a pre-made style for Lemmy.

I figured I could make my own but I didn't want to waste time doing something that could have been done already or could be done faster. at least I know I'm on the right track!

oh, I forgot about the API not being freely available; so an alternate frontend wouldn't be a proper solution?

going by the other comments, though, there are client-side options that can avoid API issues entirely by just re-styling the webpage. thanks for the info, though!

ah, I see. thanks

lol I understand the feeling

these simple type of ads used in the early internet was exactly the idea I was going for, having little involved to breach privacy or be used as an attack vector. more individual user ads was also what I was imagining, and looking at them, they are quite funny too