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I recently joined the dark side - an agile consulting company (why and how is a long story). The first client I was assigned to was an international bank. The client wanted a web portal, that was at its core, just a massive web form for their users to perform data entry.
My company pitched and won the project even though they didn't have a single developer on their bench. The entire project team (including myself) was fast tracked through interviews and hired very rapidly so that they could staff the project (a fact I found out months later).
Although I had ~8 years of systems programming experience, my entire web development experience amounted to 12 weeks (a part time web dev course) just before I got hired.
I introduce to you, my team ...
Scrum Master. 12 years experience on paper.
Rote memorised the agile manifesto and scrum textbooks. He constantly went “We should do X instead of (practical thing) Y, because X is the agile way.” Easily pressured by the client to include ridiculous (real time chat in a form filling webpage), and sometimes near impossible features (undo at the keystroke level). He would just nag at the devs until someone mumbled ‘yes' just so that he would stfu and go away.
UX Designer. 3 years experience on paper ... as business analyst.
Zero professional experience in UX. Can’t use design tools like AI / photoshop. All he has is 10 weeks of UX bootcamp and a massive chip on his shoulder. The client wanted a web form, he designed a monstrosity that included several custom components that just HAD to be put in, because UX. When we asked for clarification the reply was a usually condescending “you guys don’t understand UX, just do <insert unhandled edge case>, this is intended."
Developer - PHD in his first job.
Invents programming puzzles to solve where there are none. The user story asked for a upload file button. He implemented a queue system that made use of custom metadata to detect file extensions, file size, and other attributes, so that he could determine which file to synchronously upload first.
Developer - Bootlicker. 5 years experience on paper.
He tried to ingratiate himself with the management from day 1. He also writes code I would fire interns and fail students for. His very first PR corrupted the database. The most recent one didn’t even compile.
Developer - Millennial fratboy with a business degree. 8 years experience on paper.
His entire knowledge of programming amounted to a single data structures class he took on Coursera. Claims that’s all he needs. His PRs was a single 4000+ line files, of which 3500+ failed the linter, had numerous bugs / console warnings / compile warnings, and implemented 60% of functionality requested in the user story. Also forget about getting his attention whenever one of the pretty secretaries walked by. He would leap out of his seat and waltz off to flirt.
Developer - Brooding loner. 6 years experience on paper.
His code works. It runs, in exponential time. Simply ignores you when you attempt to ask.
Developer - Agile fullstack developer extraordinaire. 8 years experience on paper.
Insists on doing the absolute minimum required in the user story, because more would be a waste. Does not believe in thinking ahead for edge conditions because it isn’t in the story. Every single PR is a hack around existing code. Sometimes he hacks a hack that was initially hacked by him. No one understands the components he maintains.
Developer - Team lead. 10 years of programming experience on paper.
Writes spaghetti code with if/else blocks nested 6 levels deep. When asked "how does this work ?”, the answer “I don’t know the details, but hey it works!”. Assigned as the team lead as he had the most experience on paper. Tries organise technical discussions during which he speaks absolute gibberish that either make no sense, or are complete misunderstandings of how our system actually works.
The last 2 guys are actually highly regarded by my company and are several pay grades above me. The rest were hired because my company was desperate to staff the project.
There are a 3 more guys I didn’t mention. The 4 of us literally carried the project. The codebase is ugly as hell because the others merge in each others crap. We have no unit tests, and It’s near impossible to start because of the quality of the code. But this junk works, and was deployed to production. Today is it actually hailed as a success story.
All these 3 guys have quit. 2 of them quit without a job. 1 found a new and better gig.
I’m still here because I need the money. There’s a tsunami of trash code waiting to fail in production, and I’m the only one left holding the fort.
Why am I surrounded by morons?
Why are these retards paid more than me?
Why are they so proud when all they produce is trash?
How on earth are they still hired?
And yeah, FML.8 -
When I was at university in my last semester of my bachelor's, I was doing a game programming paper and our last assignment was to group up and make a game. So I go with one of the guys I know and this other dude since his previous game was really neat. Then two randoms joined that from my first impressions of their games wasn't much at all (one guy made four buttons click and called it a game in Java when we had to make games in c++ and the other guy used an example game and semi modded it.
Anyways we get to brain storming, totally waste too much time getting organised because the guy that volunteered (4 buttons guy) was slow to getting things sorted. Eventually we get to making the game and 4 buttons guy hasn't learnt how to use git, I then end up spending 3 hours over Skype explaining to him how to do this. He eventually learns how to do things and then volunteers to do the AI for the game, after about a week (this assignment is only 5 weeks long) he hasn't shown any progress, we eventually get to our 3rd week milestone no progress from him and the modder, with only three classes left we ask them both to get stuff done before a set deadline (modder wanted to do monsters and help 4 buttons with AI) both agreed and deadline rolls up and no work is shown at all, modest shows up extremely late and shows little work.
4 buttons guy leaves us a Skype message the day of our 2nd to last class,, saying he dropped the paper...
Modder did do some work but he failed to read all the documentation I left him (the game was a 2d multiplayer crafting game, I worked so hard to make a 2d map system with a world camera) he failed to read everything and his monsters used local coordinates and were stuck on screen!
With about a week left and not too many group meetings left we meet up to try and get stuff done, modder does nothing to help, the multiplayer is working my friend has done the crafting and weapon system and the map stuff is working out well. We're missing AI and combat, with our last few hours left we push to get as much stuff done, I somehow get stuck doing monster art, AI is done by the other two and I try to getting some of the combat and building done.
In the end we completely commented all of modders work because well it made us look bad lol. He later went to complain to my free claiming I did it and was a douchebag for doing so. We had to submit our developer logs and the three of us wrote about how shitty it was to deal with these two.
We tried out best not to isolate ourselves from them and definitely tried to help but we were swamped with our other assignments and what we had to work on.
In the end leaving and not helping right when the deadline is close was what I call the most shittiest thing team mates can do, I think sticking together even if we were to fail was at least a lot better.3 -
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 existence2 -
*cracks knuckles*
Boy was I happy to see this when I opened devRant up.
So for starters, more group projects are necessary. Many reasons why. To begin with, it allows for more complex programs than getting some input and printing some shit out. It also develops interpersonal skills (I hate people too, but when you go out to look for work you'll be with them, so better get used to it soon). If a platform like GitHub is used, it's easy to track who did what, and see what each person in the group did, so it should be fairly easy to discourage lazy asses.
Beyond that, stop giving us half completed assignments and asking us to fill in a function/method. Yes, it will take longer. But one doesn't learn to program by doing the minimum required work, you've got to crash and burn a lot in order to git gud. So ffs, let us do all the work. We're like AI, we learn through reinforcement learning.
Stop giving us a spec to follow. We'll do plenty of that in the future, right now we need to make mistakes, not be held by the hand all the way. Let us do dumb shit so you can fail us and tell us our code is repulsive, and this other way was better. Explain why. That's how people learn, not by telling us what each function should return, what can and can't be used, etc. And if you can't come up with a scenario in which what you're teaching is useful, then maybe you're not teaching us the right material.
I'll leave it at that for today... But I'll be back 😈 -
The hype of Artificial Intelligence and Neutral Net gets me sick by the day.
We all know that the potential power of AI’s give stock prices a bump and bolster investor confidence. But too many companies are reluctant to address its very real limits. It has evidently become a taboo to discuss AI’s shortcomings and the limitations of machine learning, neural nets, and deep learning. However, if we want to strategically deploy these technologies in enterprises, we really need to talk about its weaknesses.
AI lacks common sense. AI may be able to recognize that within a photo, there’s a man on a horse. But it probably won’t appreciate that the figures are actually a bronze sculpture of a man on a horse, not an actual man on an actual horse.
Let's consider the lesson offered by Margaret Mitchell, a research scientist at Google. Mitchell helps develop computers that can communicate about what they see and understand. As she feeds images and data to AIs, she asks them questions about what they “see.” In one case, Mitchell fed an AI lots of input about fun things and activities. When Mitchell showed the AI an image of a koala bear, it said, “Cute creature!” But when she showed the AI a picture of a house violently burning down, the AI exclaimed, “That’s awesome!”
The AI selected this response due to the orange and red colors it scanned in the photo; these fiery tones were frequently associated with positive responses in the AI’s input data set. It’s stories like these that demonstrate AI’s inevitable gaps, blind spots, and complete lack of common sense.
AI is data-hungry and brittle. Neural nets require far too much data to match human intellects. In most cases, they require thousands or millions of examples to learn from. Worse still, each time you need to recognize a new type of item, you have to start from scratch.
Algorithmic problem-solving is also severely hampered by the quality of data it’s fed. If an AI hasn’t been explicitly told how to answer a question, it can’t reason it out. It cannot respond to an unexpected change if it hasn’t been programmed to anticipate it.
Today’s business world is filled with disruptions and events—from physical to economic to political—and these disruptions require interpretation and flexibility. Algorithms alone cannot handle that.
"AI lacks intuition". Humans use intuition to navigate the physical world. When you pivot and swing to hit a tennis ball or step off a sidewalk to cross the street, you do so without a thought—things that would require a robot so much processing power that it’s almost inconceivable that we would engineer them.
Algorithms get trapped in local optima. When assigned a task, a computer program may find solutions that are close by in the search process—known as the local optimum—but fail to find the best of all possible solutions. Finding the best global solution would require understanding context and changing context, or thinking creatively about the problem and potential solutions. Humans can do that. They can connect seemingly disparate concepts and come up with out-of-the-box thinking that solves problems in novel ways. AI cannot.
"AI can’t explain itself". AI may come up with the right answers, but even researchers who train AI systems often do not understand how an algorithm reached a specific conclusion. This is very problematic when AI is used in the context of medical diagnoses, for example, or in any environment where decisions have non-trivial consequences. What the algorithm has “learned” remains a mystery to everyone. Even if the AI is right, people will not trust its analytical output.
Artificial Intelligence offers tremendous opportunities and capabilities but it can’t see the world as we humans do. All we need do is work on its weaknesses and have them sorted out rather than have it overly hyped with make-believes and ignore its limitations in plain sight.
Ref: https://thriveglobal.com/stories/...6 -
I’ve been looking for a job recently since I am a student and starting my career.
I have a bunch of experience and I like to think I have pretty broad knowledge of programming concepts (web dev, ML, AI, software development).
I see these job postings for jobs that I know I am qualified for.
- I got my research published (which is related to the jobs I’ve been applying for)
- I have great grades
- I have a clear track record of doing well in teams (life long athlete)
- I am a complete geek for new tech and libraries so I always learn them super fast
- I have side projects that aren’t just shit I’ve done in school
- my past jobs show that I am an efficient worker who has real experience
However, I always fucking fail the coding challenges.
I’m never asked questions like “how to reverse a linked list”, just obscure questions that I don’t know how to study for.
What the fuck am I supposed to do? It’s not even like I get close to the answers. I usually get a couple test cases and then fail the rest of them, or I can’t figure out a solution to solve them.
This is all really disheartening and I fucking hate it I absolutely fucking hate it and when I am trying to hire people in the future, I’m never going to make them do coding challenges bc they’re fucking stupid3
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