(#jjwbgpa) @starletvania@yarn.girlonthemoon.xyz Yes this thing is on 😅
#gcop4xa
Problems are Solved by Method\" 🇦🇺👨💻👨🦯🏹♔ 🏓⚯ 👨👩👧👧🛥 -- James Mills (operator of twtxt.net / creator of Yarn.social 🧶)
If this user/feed is violating this Pod's (yarn.meff.me) community guidelines as set out in the Abuse Policy, please report them immediately!
You are also free to Unfollow or Mute this user or feed. Muting will also remove that user/feed's content from your view and you will no longer see content from that user/feed anywhere.
@prologic does not follow you (they may not see your replies!)
(#jjwbgpa) @starletvania@yarn.girlonthemoon.xyz Yes this thing is on 😅
(#6yqdbla) @movq@www.uninformativ.de Bahahahaha 🤣
(#6yqdbla) @movq@www.uninformativ.de So no Mosaic support either? 🤣
I’m finding this very interesting… An evolved neural network that plays the game of tic-tac-toe and so far is a pretty decent player. Here is a visualization of it’s evolved “brain” that underwent GA (genetic algorithm) training with classification learning + self-play.
(#3sp2kka) @kat@yarn.girlonthemoon.xyz That would be cool! 😎
(#3sp2kka) @bender@twtxt.net Well it’s really just for other fellow humans that might not know better and what Microsoft does with your hard™ work 🤣
Please don’t upload my code on Github!
I’m thinking about putting this up on all my projects and even on the front page of my Gitea instance 🤔
(#i3akiua) For context, this is a funny
Interaction between an engineer and copilot on Microsoft’s core programming Language 🤣🤯
(#67mw3uq) Fuck 🤣 Building and learning about machine learning and evolutionary processes is hard™ 🤣
prologic@JamessMacStudio
Sun May 25 21:44:41
~/tmp/neurog
(main) 130
$ go build ./cmd/ttt/... && ./ttt
Generation 27 | Fitness: 0.486111 | Nodes: 44 | Conns: 82
… experimenting with building and training a tic-tac-toe game, which evolves a. neural net that learn to paly the game against the best evolved champions 😅
(#cxqthjq) @kat@yarn.girlonthemoon.xyz Authelia is great 👌 Nice choice! 🙌
(#da7zlha) Ultimately, Go sits in the sweet spot on the complexity vs performance chart:
See Rob Pyke’s presentation on Expressiveness of Go
(#da7zlha) One of the nicest things about Go is the language itself, comparing Go to other popular languages in terms of the complexity to learn to be proficient in:
25
keywords (Stack Overflow); CSP-style concurrency (goroutines & channels)30
keywords (TutorialsPoint); GIL-bound threads & multiprocessing (Wikipedia)35
keywords (Initial Commit); GIL-bound threads, asyncio
& multiprocessing (Wikipedia, DEV Community)50
keywords (Stack Overflow); threads + java.util.concurrent
(Wikipedia)82
keywords (Stack Overflow); std::thread
, atomics & futures (en.cppreference.com)38
keywords (Stack Overflow); single-threaded event loop & async/await
, Web Workers (Wikipedia)42
keywords (Stack Overflow); GIL-bound threads (MRI), fibers & processes (Wikipedia)(#da7zlha) @bender@twtxt.net Here’s a short-list:
(#da7zlha) @bender@twtxt.net What’s not to like? 😅
(#zy4an6a) @bender@twtxt.net There is no aim. Just learning 😅 That way I can actually speak and write with authority when it comes to these LLM(s) a bit more 🤣 Or maybe I just happen to become that random weirdo genius that invents Skynet™ 😂
(#zy4an6a) This is one of my attempts:
$ go build ./cmd/xor/... && ./xor
Generation 95 | Fitness: 0.999964 | Nodes: 9 | Conns: 19
Target reached!
Best network performance:
[0 0] → got=0 exp=0 (raw=0.000) ✅
[0 1] → got=1 exp=1 (raw=0.990) ✅
[1 0] → got=1 exp=1 (raw=0.716) ✅
[1 1] → got=0 exp=0 (raw=0.045) ✅
Overall accuracy: 100.0%
Wrote best.dot – render with ```dot -Tpng best.dot -o best.png`
Over the past few weeks I’ve been experimenting with and doing some deep learning and researching into neutral networks and evolutionary adaptation of them. The thing is I haven’t gotten very far. I’ve been able to build two different approaches so far with limited results. The frustrating part is that these things are so “random” it isn’t even funny. Like I can’t even get a basic ANN + GA to evolve a network that solves the XOR pattern every time with high levels of accuracy. 😞
(#dyrkrka) @sorenpeter@darch.dk Also not very readable. Quite cryptic really 😅 I have no idea how this works 🤦♂️
(#utajxsa) > My vision with this newsletter is to have a slower medium for communicating about my art as well as ideas and projects I’m working on regarding how we can use digital technology to our own benefits instead of being exploited by big tech.
Twtxt not sloe enough for you? 🤣
(#drl6faa) @thecanine@twtxt.net I think I know what you mean now.
(#utajxsa) @sorenpeter@darch.dk What will you be writing about? What’s your target audience? 🤔
(#fn3x3eq) @bender@twtxt.net Appreicate it 🙏
https://youtu.be/1GN3xBuAgrI?si=ezBYJeSOFgtBdjEu – Can someone please just fire Trump already? What a fucking idiot?! The man is a lunatic 🤦♂️
(#drl6faa) @thecanine@twtxt.net I admit I’m a little unclear of your position. What do you mean by “not the right approach”? What’s your position here? 🤔 – I have a funny feeling we actually algin, just getting our wires all mixed up in communicating it 🤣
Hey y’all 👋 I am told my “participation” is drastically down of ,ate So sorry 😞 Busy quite a busy few weeks at work with a reorg and lots of complex things happening in real live too 😅 – Hope everything is doing well 🤗