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movq
www.uninformativ.de
 (43w ago)

Maybe you’ll enjoy this as well:

I still have one of my first modems, a Creatix LC 144 VF:

I think this was the modem that I used when I first connected to the internet, but I’m not sure.

I plugged it in again and it still works:


The firmware appears to be from 1994, which sounds about right. I don’t think we had internet access before that. We certainly did use local mailboxes, though. (Or BBS’s, as you might call them.)

I now want to actually use that modem again. For the moment, I can only use a phone to dial into it, I lack a second modem to actually establish a connection. Here’s a video:

Not spectacular, but the modem does answer after me entering ATA.

I bought another cheap old modem on eBay and am now waiting for it to arrive. Once it’s here, I want to simulate an actual dial-up session, hopefully from OS/2 or Windows 3.x.

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prologic
twtxt.net
 (44w ago)
↳ In-reply-to » @kat I don’t like Golang much either, but I am not a programmer. This little site, Go by example might explain a thing or two.

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:

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kat
yarn.girlonthemoon.xyz
 (44w ago)
↳ In-reply-to » i wish it was realistic for me to learn golang but every single time i try to comprehend any go code i'm like What the fuck am i looking at. why is all of this so short and condensed GIVE ME VERBOSE CODE

@movq@www.uninformativ.de i feel like when i read go code i’m reading some algebra shit where every part is 1-5 letters long and then there’s weird symbols like := and it’s just infinitely harder for me to parse and infer meaning from lol. it’s such a me problem

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prologic
twtxt.net
 (44w ago)
↳ In-reply-to » 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. 😞

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`

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