Running a fucking conda environment on windows (an update environment from the previous one that I normally use) gets to be a fucking pain in the fucking ass for no fucking reason.

First: Generate a new conda environment, for FUCKING SHITS AND GIGGLES, DO NOT SPECIFY THE PYTHON VERSION, just to see compatibility, this was an experiment, expected to fail.

Install tensorflow on said environment: It does not fucking work, not detecting cuda, the only requirement? To have the cuda dependencies installed, modified, and inside of the system path, check done, it works on 4 other fucking environments, so why not this one.

Still doesn't work, google around and found some thread on github (the errors) that has a way to fix it, do it that way, fucking magic, shit is fixed.

Very well, tensorflow is installed and detecting cuda, no biggie. HAD TO SWITCH TO PYHTHON 3,8 BECAUSE 3.9 WAS GIVING ISSUES FOR SOME UNKNOWN FUCKING REASON

Ok no problem, done.

Install jupyter lab, for which the first in all other 4 environments it works. Guess what a fuckload of errors upon executing the import of tensorflow. They go on a loop that does not fucking end.

The error: imPoRT eRrOr thE Dll waS noT loAdeD

Ok, fucking which one? who fucking knows.

I FUCKING HATE that the main language for this fucking bullshit is python. I guess the benefits of the repl, I do, but the python repl is fucking HORSESHIT compared to the one you get on: Lisp, Ruby and fucking even NODE in which error messages are still more fucking intelligent than those of fucking bullshit ass Python.

Personally? I am betting on Julia devising a smarter environment, it is a better language already, on a second note: If you are worried about A.I taking your job, don't, it requires a team of fucktards working around common basic system administration tasks to get this bullshit running in the first place.

My dream? Julia or Scala (fuck you) for a primary language in machine learning and AI, in which entire environments, with aaaaaaaaaall of the required dlls and dependencies can be downloaded and installed upon can just fucking run. A single directory structure in which shit just fucking works (reason why I like live environments like Smalltalk, but fuck you on that too) and just run your projects from there, without setting a bunch of bullshit from environment variables, cuda dlls installation phases and what not. Something that JUST FUCKING WORKS.

I.....fucking.....HATE the level of system administration required to run fucking anything nowadays, the reason why we had to create shit like devops jobs, for the sad fuckers that have to figure out environment configurations on a box just to run software.

Fuck me man development turned to shit, this is why go mod, node npm, php composer strict folder structure pipelines were created. Bitch all you want about npm, but if I can create a node_modules setting with all of the required dlls to run a project, even if this bitch weights 2.5GB for a project structure you bet your fucking ass that I would.

"YOU JUST DON'T KNOW WHAT YOU ARE DOING" YES I FUCKING DO and I will get this bullshit fixed, I will get it running just like I did the other 4 environments that I fucking use, for different versions of cuda and python and the dependency circle jerk BULLSHIT that I have to manage. But this "follow the guide and it will work, except when it does not and you are looking into obscure github errors" bullshit just takes away from valuable project time when you have a small dedicated group of developers and no sys admin or devops mastermind to resort to.

I have successfully deployed:
Java
Golang
Clojure
Python
Node
PHP
VB/C# .NET
C++
Rails
Django

Projects, and every single fucking time (save for .net, that shit just fucking works on a dedicated windows IIS server) the shit will not work with x..nT reasons. It fucking obliterates me how fucking annoying this bullshit is. And the reason why the ENTIRE FUCKING FIELD of computer science and software engineering is so fucking flawed.

But we can't all just run to simple windows bs in which we have documentation for everything. We have to spend countless hours on fucking Linux figuring shit out (fuck you also, I have been using Linux since I was 18, I am 30 now) for which graphical drivers for machine learning, cuda and whatTheFuckNot require all sorts of sys admin gymnasts to be used.

Y'all fucked up a long time ago. Smalltalk provided an all in one, easily rollable back to previous images, easily administered interfaces for this fileFuckery bullshit, and even though the JVM and the .NET environments did their best to hold shit down, and even though we had npm packages pulling the universe inside, or gomod compiling shit into one place NOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO we had to do whatever the fuck we wanted to feel l337 and wanted.

Fuck all of you, fuck this field, fuck setting boxes for ML/AI and fuck every single OS in existence

@linuxxx’s recent post inspired me to try out linux again and see if I want to use it as my primary OS. My past experience with linux has always been endless fiddling with settings or drivers or whatnot, so I was wondering if you’ve got advice on what level of complexity is appropriate in solutions. E.g. if using the terminal and changing a bunch of config files is normal, or if that is generally unsustainable on the long term.

Thanks, I can’t wait to see how this experiment goes 😄

I have a hdd left, in the mood of trying out a new os. Any new/hot os's to try?

Btw: my main os is xubuntu.

I am having an introspective moment as a junior dev.

I am working in my 3rd company now and have spent the avg amount of time i would spent in a company ( 1- 1.5 years)

I find myself in similar problems and trajectories:

1. The companies i worked for were startups of various scales : an edtech platform, an insurance company (branch of an mnc) and a b2b analytics company

2. These people hire developers based on domain knowledge and not innovative thinking , and expect them to build anything that the PMs deem as growth/engagement worthy ( For eg, i am bad at those memory time optimising programming/ ds/algo, but i can make any kind of android screen/component, so me and people like me get hired here)

3. These people hire new PMs based on expertise in revenue generation and again , not on the basis of innovative thinking, coz most of the time these folks make tickets to experiment with buttons and text colors to increase engagement/growth

4. The system goes into chaos mode soon since their are so many cross operating teams and the PMs running around trying to boss every dev , qa and designer to add their changes in the app.

5. meanwhile due to multiple different teams working on different aspects, their is no common data center with up to date info of all flows, products and features. the product soon becomes a Frankenstein monster.

6. Thus these companies require more and more devs and QAs which are cogs in the system then innovative thinkers . the cogs in the system will simply come, dimwittingly add whatever feature is needed and goto home.

7. the cogs in system which also start taking the pain of tracking the changes and learning about the product itself becomes "load bearing cogs" : i.e the devs with so much knowledge of the product that they can be helpful in every aspect of feature lifecycle .

8. such devs find themselves in no need for proving themselves , in no need for doing innovative work and are simply promoted based on their domain knowledge and impact.

My question is simply this : are we as a dev just destined to be load bearing cogs?

we are doing the work which ideally a manager should be doing, ie maintaining confluence docs with end to end technical as well as business logic info of every feature/flow.

So is that the only definition of a Software Engineer in a technical product?

then how come innovations happen in companies like meta Microsoft google open ai etc?

if i have to guess as a far observer, i would say their diversity in different fields helps them mix and match stuff and lead to innovative stuff.

For eg, the android os team in google has helped add many innovative things in google cloud product and vice versa.

same is with azure and windows . windows is now optomissed to run in cloud machines when at one point it was just a horrible memory hogging and slow pc OS

for small companies, 1 ideology/product/domain is their hero ideology/product/domain .

an insurance company tries to experiment with stuff related to insurances,health,vehicles,and the best innovations they come up with is "lets give user a discount in premium if they do 5000 steps a day for an year".

edtech would say "lets do live streaming for children apart from static videos"

but Android team at google said , "since ai team is doing so well, lets include ai in various system apps and support device level models" ~ a much larger innovation as 2 domains combined to make a product

The small companies are not aiming to be an innovative product, they are just aiming to be a monopoly product. and this is kinda sad

Spent a couple of hours setting up an old laptop with opensuse leap and trying to learn the basics of using it so I can simulate a small network (my desktop, a couple of old laptops for specific tasks, and my school laptop) with that laptop as the ‘hub’ Put syncthing on there as a pseudo-cloud system, teamviewer for remote access, and did all required updates for the OS. But literally no idea where to go from there What all should/can I do with this setup useful or otherwise. This is meant to be a learning experiment with a hope for some usefulness from it