Yeah I think around the Pentium 200mhz point was the sweet spot. Powerful enough to do a lot of things, but not so powerful that software can be as inefficient and wasteful as it is today.
Omg the comments are so out of hand. I regularly do code reviews on colleagues who use AI to write code (some whilst protesting, but still). The comments are usually the worst part.
The thing writes entire novels in the summary that do nothing but confuse and add cognitive load. It adds comments to super obvious things, describing what the code does instead of why. Yes AI I can read code, I know assigning a variable a value is how shit works. And I have still got PTSD from those kinds of comments from a legacy system I worked on for years that did the exact same, except the comments and the code didn't match up, so it was a continuous guess which one was the intended one.
It also likes to put responses to the prompt in the comments. So for example when it assigned A to a variable and it was supposed to be B, when you point this out it adds a comment saying something like: This is supposed to be B not A. But when you read those comments after the fact, it makes zero sense. Like of course it should be B? Why should it ever be A?
And it often generates a bunch of markdown docs which are plain drivel, luckily most devs just delete those before I see them.
My personal experience is in 30% of cases the AI is just plain wrong and the result is nonsense, delete that shit and try again. In the 70% that does have some kind of answer there is ALWAYS at least one big issue and usually multiple. It's a 50/50 if the code is workable with some kinks to work out, or if it is seriously flawed and needs a lot of work. For experienced devs it can be a helpful thing if they have writers block, to give them something to be angry about, showing them how they can do better. But for inexperienced devs it's just plain terrible, the code is shit and the dev doesn't even know. And worse still the dev doesn't learn. I try to sit down with them, explain the shortcomings and how to do better. But they don't learn, they just know what stuff to write in the prompt, in order to not get me on their case. Or they will say stuff like: but it works right? Facepalm
That company I do work for also tried getting their sysadmins and devops people to use AI. Till one day there was a permissions issue, which admittedly was pretty complicated, where they ended up solving it with AI. The team was happy, the upper management was happy, high fives all around. Till the grumpy old sysadmin who has 40 years of experience takes a look and hits the big ol' red alarm button of doom. Full investigation later, the AI had fucked up and created a huge hole in the security. There was zero evidence it had been exploited, but that doesn't matter. All the work still needed to be done, all the paperwork filed, proper agencies informed, because the security issue was there. Management eased up on AI usage for those people real fast.
It's so weird how people in charge want to use AI, but aren't even really sure of what it is and what it isn't. And they don't listen to what the people with actual knowledge have to say. In their minds we are probably all just covering our asses to not be out of a job.
But for real if anyone in management is listening, take it from an old asshole who has done this job since the 80s: AI fucking sucks!
And their products are so fucking shit. Today I wanted to shit post in a Discord server I'm a part of. I felt like if I put effort into it, it wouldn't really be a shit post any more. The idea was minimum effort for a few laughs and we move on. So I loaded up ChatGPT and asked it to generate the meme image. I thought even if it messed up the text, I would just generate it without the text and put the text in with gimp or something.
I put in the prompt, it spewed a lot of nonsense about what I meant and how it was going to generate the image. If I would just say "Generate it", it would generate the image. So I did, it then said I needed to be signed in for image generation. OK fine, I signed in with a Gmail account I only ever use for spam, just for occasions such as this. It was happy to start generating.
It hung on generating for a while, until it said done in the status thing top right, but nothing in the chat. I refreshed the page, which gave me the option to prompt again. I asked where is the generated image? It said here it is and presented a gray box. It said if you see a gray box you uploaded it wrong? Wtf are you talking about? I didn't upload anything. It said it could try generating again. Same exact result, crashing on generation, refresh yielding a new different gray box.
Like for fucks sake, the one thing I thought it would be good at, low effort shitposting, it failed at. Why the fuck does this company have such a large market cap?
I can't wait for this whole AI debacle to be over and done with. Nobody is ever going to pay for your buggy ass bullshit generator.
Also just because the code works, doesn't mean it's good code.
I've had to review code the other day which was clearly created by an LLM. Two classes needed to talk to each other in a bit of a complex way. So I would expect one class to create some kind of request data object, submit it to the other class, which then returns some kind of response data object.
What the LLM actually did was pretty shocking, it used reflection to get access from one class to the private properties with the data required inside the other class. It then just straight up stole the data and did the work itself (wrongly as well I might add). I just about fell of my chair when I saw this.
So I asked the dev, he said he didn't fully understand what the LLM did, he wasn't familiar with reflection. But since it seemed to work in the few tests he did and the unit tests the LLM generated passed, he thought it would be fine.
Also the unit tests were wrong, I explained to the dev that usually with humans it's a bad idea to have the person who wrote the code also (exclusively) write the unit tests. Whenever possible have somebody else write the unit tests, so they don't have the same assumptions and blind spots. With LLMs this is doubly true, it will just straight up lie in the unit tests. If they aren't complete nonsense to begin with.
I swear to the gods, LLMs don't save time or money, they just give the illusion they do. Some task of a few hours will take 20 min and everyone claps. But then another task takes twice as long and we just don't look at that. And the quality suffers a lot, without anyone really noticing.
I printed a large complex part once, only to see I overlooked another thing that got in the way of my part. Instead of changing my design and re-printing it (which would take hours), I walked over to the mill and milled off a section of my print so it would fit properly. Plopped it on, fits like a glove, design king status achieved!
And thus Nvidia keeps the money faucet running. Sorry AI companies, we've just created the latest and greatest. We know you have invested trillions already, but you need the hot new thing or the competition gets it and you are obsolete. Time to invest some more!
Then blow a raspberry on that tummy and watch them be confused, disgusted and offended at the same time. Only do this to cats who will tolerate it tho, otherwise you're gonna get a face full of claws.
Yeah I think around the Pentium 200mhz point was the sweet spot. Powerful enough to do a lot of things, but not so powerful that software can be as inefficient and wasteful as it is today.